| Date | Title | Provider |
| 2000 |
A Digital Raster Graphic (DRG) is a raster image of a scanned USGS
topographic or planimetric map including the collar information, georeferenced to
the UTM grid.
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| U S Geological Survey |
| 2000 |
A Digital Raster Graphic (DRG) is a raster image of a scanned USGS
topographic or planimetric map including the collar information, georeferenced to
the UTM grid.
Metadata
|
Download
| More Options...
| U S Geological Survey |
| 2000 |
A Digital Raster Graphic (DRG) is a raster image of a scanned USGS
topographic or planimetric map including the collar information, georeferenced to
the UTM grid.
Metadata
|
Download
| More Options...
| U S Geological Survey |
| 2000 |
A Digital Raster Graphic (DRG) is a raster image of a scanned USGS
topographic or planimetric map including the collar information, georeferenced to
the UTM grid.
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|
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| U S Geological Survey |
| 2000 |
Digital Elevation Model (DEM) is the terminology adopted by the
USGS to describe terrain elevation data sets in a digital raster form. The
standard DEM consists of a regular array of elevations cast on a designated
coordinate projection system. The DEM data are stored as a series of
profiles in which the spacing of the elevations along and between each
profile is in regular whole number intervals. The normal orientation of
data is by columns and rows. Each column contains a series of elevations
ordered from south to north with the order of the columns from west to
east. The DEM is formatted as one ASCII header record (A-record),
followed by a series of profile records (B-records) each of which include
a short B-record header followed by a series of ASCII integer elevations
per each profile. The last physical record of the DEM is an accuracy record
(C-record).
7.5-minute DEM (30- by 30-meter data spacing, cast on Universal Transverse
Mercator (UTM) projection). Provides coverage in 7.5- by 7.5-minute
blocks. Each product provides the same coverage as a standard USGS
7.5-minute quadrangle without over edge. Coverage is for the Contiguous
United States, Hawaii, and Puerto Rico.
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|
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| U S Geological Survey |
| 2000 |
Digital Elevation Model (DEM) is the terminology adopted by the
USGS to describe terrain elevation data sets in a digital raster form. The
standard DEM consists of a regular array of elevations cast on a designated
coordinate projection system. The DEM data are stored as a series of
profiles in which the spacing of the elevations along and between each
profile is in regular whole number intervals. The normal orientation of
data is by columns and rows. Each column contains a series of elevations
ordered from south to north with the order of the columns from west to
east. The DEM is formatted as one ASCII header record (A-record),
followed by a series of profile records (B-records) each of which include
a short B-record header followed by a series of ASCII integer elevations
per each profile. The last physical record of the DEM is an accuracy record
(C-record).
7.5-minute DEM (30- by 30-meter data spacing, cast on Universal Transverse
Mercator (UTM) projection). Provides coverage in 7.5- by 7.5-minute
blocks. Each product provides the same coverage as a standard USGS
7.5-minute quadrangle without over edge. Coverage is for the Contiguous
United States, Hawaii, and Puerto Rico.
Metadata
|
Download
| More Options...
| U S Geological Survey |
| 2000 |
Digital Elevation Model (DEM) is the terminology adopted by the
USGS to describe terrain elevation data sets in a digital raster form. The
standard DEM consists of a regular array of elevations cast on a designated
coordinate projection system. The DEM data are stored as a series of
profiles in which the spacing of the elevations along and between each
profile is in regular whole number intervals. The normal orientation of
data is by columns and rows. Each column contains a series of elevations
ordered from south to north with the order of the columns from west to
east. The DEM is formatted as one ASCII header record (A-record),
followed by a series of profile records (B-records) each of which include
a short B-record header followed by a series of ASCII integer elevations
per each profile. The last physical record of the DEM is an accuracy record
(C-record).
7.5-minute DEM (30- by 30-meter data spacing, cast on Universal Transverse
Mercator (UTM) projection). Provides coverage in 7.5- by 7.5-minute
blocks. Each product provides the same coverage as a standard USGS
7.5-minute quadrangle without over edge. Coverage is for the Contiguous
United States, Hawaii, and Puerto Rico.
Metadata
|
Download
| More Options...
| U S Geological Survey |
| 2000 |
A Digital Raster Graphic (DRG) is a raster image of a scanned USGS
topographic or planimetric map including the collar information, georeferenced to
the UTM grid.
Metadata
|
Download
| More Options...
| U S Geological Survey |
| 2000 |
A Digital Raster Graphic (DRG) is a raster image of a scanned USGS
topographic or planimetric map including the collar information, georeferenced to
the UTM grid.
Metadata
|
Download
| More Options...
| U S Geological Survey |
| 2000 |
A Digital Raster Graphic (DRG) is a raster image of a scanned USGS
topographic or planimetric map including the collar information, georeferenced to
the UTM grid.
Metadata
|
Download
| More Options...
| U S Geological Survey |
| 2000 |
A Digital Raster Graphic (DRG) is a raster image of a scanned USGS
topographic or planimetric map including the collar information, georeferenced to
the UTM grid.
Metadata
|
Download
| More Options...
| U S Geological Survey |
| 2000 |
A Digital Raster Graphic (DRG) is a raster image of a scanned USGS
topographic or planimetric map including the collar information, georeferenced to
the UTM grid.
Metadata
|
Download
| More Options...
| U S Geological Survey |
| 2000 |
A Digital Raster Graphic (DRG) is a raster image of a scanned USGS
topographic or planimetric map including the collar information, georeferenced to
the UTM grid.
Metadata
|
Download
| More Options...
| U S Geological Survey |
| 2000 |
A Digital Raster Graphic (DRG) is a raster image of a scanned USGS
topographic or planimetric map including the collar information, georeferenced to
the UTM grid.
Metadata
|
Download
| More Options...
| U S Geological Survey |
| 2000 |
A Digital Raster Graphic (DRG) is a raster image of a scanned USGS
topographic or planimetric map including the collar information, georeferenced to
the UTM grid.
Metadata
|
Download
| More Options...
| U S Geological Survey |
| 2002 |
The Assessment Unit is the fundamental unit used in the National Assessment Project for the assessment of undiscovered oil and gas resources. The Assessment Unit is defined within the context of the higher-level Total Petroleum System. The Assessment Unit is shown here as a geographic boundary interpreted, defined, and mapped by the geologist responsible for the province and incorporates a set of known or postulated oil and (or) gas accumulations sharing similar geologic, geographic, and temporal properties within the Total Petroleum System, such as source rock, timing, migration pathways, trapping mechanism, and hydrocarbon type. The Assessment Unit boundary is defined geologically as the limits of the geologic elements that define the Assessment Unit, such as limits of reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are Assessment Units that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the Assessment Unit boundary.
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| U S Geological Survey |
| 2002 |
Cell maps for each oil and gas assessment unit were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in an assessment unit or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, dry, or the type of production of the wells located within the cell is unknown. The well information was initially retrieved from the IHS Energy Group, PI/Dwights PLUS Well Data on CD-ROM, which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary PI/Dwights PLUS Well Data. No proprietary data are displayed or included in the cell maps. The data from PI/Dwights PLUS Well Data were current as of October 2001 when the cell maps were created in 2002.
Metadata
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KMZ
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GeoJSON
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| U S Geological Survey |
| 2002 |
The Assessment Unit is the fundamental unit used in the National Assessment Project for the assessment of undiscovered oil and gas resources. The Assessment Unit is defined within the context of the higher-level Total Petroleum System. The Assessment Unit is shown here as a geographic boundary interpreted, defined, and mapped by the geologist responsible for the province and incorporates a set of known or postulated oil and (or) gas accumulations sharing similar geologic, geographic, and temporal properties within the Total Petroleum System, such as source rock, timing, migration pathways, trapping mechanism, and hydrocarbon type. The Assessment Unit boundary is defined geologically as the limits of the geologic elements that define the Assessment Unit, such as limits of reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are Assessment Units that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the Assessment Unit boundary.
Metadata
|
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|
Preview
|
KMZ
|
Spreadsheet
|
GeoJSON
|
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Image
or
Feature
|
Add to ArcGIS Pro
| More Options...
| U S Geological Survey |
| 2002 |
Cell maps for each oil and gas assessment unit were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in an assessment unit or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, dry, or the type of production of the wells located within the cell is unknown. The well information was initially retrieved from the IHS Energy Group, PI/Dwights PLUS Well Data on CD-ROM, which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary PI/Dwights PLUS Well Data. No proprietary data are displayed or included in the cell maps. The data from PI/Dwights PLUS Well Data were current as of October 2001 when the cell maps were created in 200
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| U S Geological Survey |
| 2020 |
This represents tidal waters of the Chesapeake Bay that are impaired for some part or all of the indicated Bay segment by toxic chemicals based on each state's implementation of the Clean Water Act.
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| U S Geological Survey |
| 1984 |
To better understand how the land is changing and to relate those changes to water quality trends, the USGS funded the production of a Chesapeake Bay Watershed Land Cover Data Series (CBLCD) representing four dates: 1984, 1992, 2001, and 2006. These data were produced by MDA Federal Inc., under contract to the USGS and were derived from Landsat 5 Thematic Mapper and Landsat 7 Enhanced Thematic Mapper satellite imagery. Each of the four datasets consists of 16 land use and land cover classes (Anderson, et al., 1976). The datasets are temporally comparable and encompass the entire Chesapeake Bay watershed and most intersecting counties.
The 2001 dataset represents the base layer for the Data Series and is composed of NOAA's 2001 Coastal Change Analysis Program (CCAP) dataset in the coastal and northern portion of the watershed coupled with USGS' 2001 National Land Cover Dataset in the western and southwestern portions of the watershed. MDA Federal's Cross Correlation Analysis (CCA) technique was used to produce updates (yr. 2006) and retrospective updates (yrs. 1984 and 1992) to the base layer. CCA identifies significant spectral changes between image pairs within the range of spectral values for each land cover class identified in the 2001 base layer. MDA Federal used Classification and Regression Trees to assign land cover classes to 1984, 1992, and 2006 pixels exhibiting significant deviations from their 2001 expected spectral values. MDA Federal used these methods to develop the 1996 and 2005 land cover change datasets for the Mid-Atlantic coastal area funded by NOAA CCAP.
Land use and land cover interpretations derived from Landsat satellite imagery are based on the sun's reflectance off the land surface, e.g., urban areas have different spectral reflectance characteristics than forests and herbaceous vegetation. For this reason, the data most accurately represent land cover (e.g., tree canopy) compared with land use or management (e.g., forests and pasture). Due to similarities in spectral reflectance characteristics, some land use and land cover classes are easily confused with each other. The spectral characteristics of low density residential areas, for example, may closely resemble the characteristics of forests in a neighborhood with mature trees or of cropland or pasture if large residential lots are composed mostly of lawns. Cropland and pasture may also have similar spectral qualities. Therefore, users should be cautioned against evaluating transitions between cropland and pasture based on the CBLCD. Users should be generally confident, however, that the overall spatial patterns of cropland and pasture in the Bay watershed are accurate because the USGS and NOAA used multi-season imagery to create the 2001 base layer and the data compare favorably with county-level cropland and pasture acreage estimates reported in the 2002 U.S. Census of Agriculture.
The USGS is in the process of interpreting and publishing statistics on the extent, type, and patterns of land cover change from 1984-2006 in the Bay watershed, major tributaries, and counties. The USGS will also be publishing land change forecasts based on observed trends in the CBLCD. These additional interpretations, statistics, and datasets will be publicly released over the coming year following publication.
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| U S Geological Survey |
| 1992 |
To better understand how the land is changing and to relate those changes to water quality trends, the USGS funded the production of a Chesapeake Bay Watershed Land Cover Data Series (CBLCD) representing four dates: 1984, 1992, 2001, and 2006. These data were produced by MDA Federal Inc., under contract to the USGS and were derived from Landsat 5 Thematic Mapper and Landsat 7 Enhanced Thematic Mapper satellite imagery. Each of the four datasets consists of 16 land use and land cover classes (Anderson, et al., 1976). The datasets are temporally comparable and encompass the entire Chesapeake Bay watershed and most intersecting counties.
The 2001 dataset represents the base layer for the Data Series and is composed of NOAA's 2001 Coastal Change Analysis Program (CCAP) dataset in the coastal and northern portion of the watershed coupled with USGS' 2001 National Land Cover Dataset in the western and southwestern portions of the watershed. MDA Federal's Cross Correlation Analysis (CCA) technique was used to produce updates (yr. 2006) and retrospective updates (yrs. 1984 and 1992) to the base layer. CCA identifies significant spectral changes between image pairs within the range of spectral values for each land cover class identified in the 2001 base layer. MDA Federal used Classification and Regression Trees to assign land cover classes to 1984, 1992, and 2006 pixels exhibiting significant deviations from their 2001 expected spectral values. MDA Federal used these methods to develop the 1996 and 2005 land cover change datasets for the Mid-Atlantic coastal area funded by NOAA CCAP.
Land use and land cover interpretations derived from Landsat satellite imagery are based on the sun's reflectance off the land surface, e.g., urban areas have different spectral reflectance characteristics than forests and herbaceous vegetation. For this reason, the data most accurately represent land cover (e.g., tree canopy) compared with land use or management (e.g., forests and pasture). Due to similarities in spectral reflectance characteristics, some land use and land cover classes are easily confused with each other. The spectral characteristics of low density residential areas, for example, may closely resemble the characteristics of forests in a neighborhood with mature trees or of cropland or pasture if large residential lots are composed mostly of lawns. Cropland and pasture may also have similar spectral qualities. Therefore, users should be cautioned against evaluating transitions between cropland and pasture based on the CBLCD. Users should be generally confident, however, that the overall spatial patterns of cropland and pasture in the Bay watershed are accurate because the USGS and NOAA used multi-season imagery to create the 2001 base layer and the data compare favorably with county-level cropland and pasture acreage estimates reported in the 2002 U.S. Census of Agriculture.
The USGS is in the process of interpreting and publishing statistics on the extent, type, and patterns of land cover change from 1984-2006 in the Bay watershed, major tributaries, and counties. The USGS will also be publishing land change forecasts based on observed trends in the CBLCD. These additional interpretations, statistics, and datasets will be publicly released over the coming year following publication.
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| U S Geological Survey |
| 2001 |
To better understand how the land is changing and to relate those changes to water quality trends, the USGS funded the production of a Chesapeake Bay Watershed Land Cover Data Series (CBLCD) representing four dates: 1984, 1992, 2001, and 2006. These data were produced by MDA Federal Inc., under contract to the USGS and were derived from Landsat 5 Thematic Mapper and Landsat 7 Enhanced Thematic Mapper satellite imagery. Each of the four datasets consists of 16 land use and land cover classes (Anderson, et al., 1976). The datasets are temporally comparable and encompass the entire Chesapeake Bay watershed and most intersecting counties.
The 2001 dataset represents the base layer for the Data Series and is composed of NOAA's 2001 Coastal Change Analysis Program (CCAP) dataset in the coastal and northern portion of the watershed coupled with USGS' 2001 National Land Cover Dataset in the western and southwestern portions of the watershed. MDA Federal's Cross Correlation Analysis (CCA) technique was used to produce updates (yr. 2006) and retrospective updates (yrs. 1984 and 1992) to the base layer. CCA identifies significant spectral changes between image pairs within the range of spectral values for each land cover class identified in the 2001 base layer. MDA Federal used Classification and Regression Trees to assign land cover classes to 1984, 1992, and 2006 pixels exhibiting significant deviations from their 2001 expected spectral values. MDA Federal used these methods to develop the 1996 and 2005 land cover change datasets for the Mid-Atlantic coastal area funded by NOAA CCAP.
Land use and land cover interpretations derived from Landsat satellite imagery are based on the sun's reflectance off the land surface, e.g., urban areas have different spectral reflectance characteristics than forests and herbaceous vegetation. For this reason, the data most accurately represent land cover (e.g., tree canopy) compared with land use or management (e.g., forests and pasture). Due to similarities in spectral reflectance characteristics, some land use and land cover classes are easily confused with each other. The spectral characteristics of low density residential areas, for example, may closely resemble the characteristics of forests in a neighborhood with mature trees or of cropland or pasture if large residential lots are composed mostly of lawns. Cropland and pasture may also have similar spectral qualities. Therefore, users should be cautioned against evaluating transitions between cropland and pasture based on the CBLCD. Users should be generally confident, however, that the overall spatial patterns of cropland and pasture in the Bay watershed are accurate because the USGS and NOAA used multi-season imagery to create the 2001 base layer and the data compare favorably with county-level cropland and pasture acreage estimates reported in the 2002 U.S. Census of Agriculture.
The USGS is in the process of interpreting and publishing statistics on the extent, type, and patterns of land cover change from 1984-2006 in the Bay watershed, major tributaries, and counties. The USGS will also be publishing land change forecasts based on observed trends in the CBLCD. These additional interpretations, statistics, and datasets will be publicly released over the coming year following publication.
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| U S Geological Survey |
| 2006 |
To better understand how the land is changing and to relate those changes to water quality trends, the USGS funded the production of a Chesapeake Bay Watershed Land Cover Data Series (CBLCD) representing four dates: 1984, 1992, 2001, and 2006. These data were produced by MDA Federal Inc., under contract to the USGS and were derived from Landsat 5 Thematic Mapper and Landsat 7 Enhanced Thematic Mapper satellite imagery. Each of the four datasets consists of 16 land use and land cover classes (Anderson, et al., 1976). The datasets are temporally comparable and encompass the entire Chesapeake Bay watershed and most intersecting counties.
The 2001 dataset represents the base layer for the Data Series and is composed of NOAA's 2001 Coastal Change Analysis Program (CCAP) dataset in the coastal and northern portion of the watershed coupled with USGS' 2001 National Land Cover Dataset in the western and southwestern portions of the watershed. MDA Federal's Cross Correlation Analysis (CCA) technique was used to produce updates (yr. 2006) and retrospective updates (yrs. 1984 and 1992) to the base layer. CCA identifies significant spectral changes between image pairs within the range of spectral values for each land cover class identified in the 2001 base layer. MDA Federal used Classification and Regression Trees to assign land cover classes to 1984, 1992, and 2006 pixels exhibiting significant deviations from their 2001 expected spectral values. MDA Federal used these methods to develop the 1996 and 2005 land cover change datasets for the Mid-Atlantic coastal area funded by NOAA CCAP.
Land use and land cover interpretations derived from Landsat satellite imagery are based on the sun's reflectance off the land surface, e.g., urban areas have different spectral reflectance characteristics than forests and herbaceous vegetation. For this reason, the data most accurately represent land cover (e.g., tree canopy) compared with land use or management (e.g., forests and pasture). Due to similarities in spectral reflectance characteristics, some land use and land cover classes are easily confused with each other. The spectral characteristics of low density residential areas, for example, may closely resemble the characteristics of forests in a neighborhood with mature trees or of cropland or pasture if large residential lots are composed mostly of lawns. Cropland and pasture may also have similar spectral qualities. Therefore, users should be cautioned against evaluating transitions between cropland and pasture based on the CBLCD. Users should be generally confident, however, that the overall spatial patterns of cropland and pasture in the Bay watershed are accurate because the USGS and NOAA used multi-season imagery to create the 2001 base layer and the data compare favorably with county-level cropland and pasture acreage estimates reported in the 2002 U.S. Census of Agriculture.
The USGS is in the process of interpreting and publishing statistics on the extent, type, and patterns of land cover change from 1984-2006 in the Bay watershed, major tributaries, and counties. The USGS will also be publishing land change forecasts based on observed trends in the CBLCD. These additional interpretations, statistics, and datasets will be publicly released over the coming year following publication.
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| U S Geological Survey |
| 2023 |
This dataset consists of Pennsylvania bridge over water locations that are being considered for flood data collection. The purpose of this effort is to identify potential locations in Pennsylvania where additional or updated water level data may be needed during or after major storm events. Criteria involved in the identification of potential locations for flood data collection includes locations of bridges over water, scour-critical bridges, densely populated areas, historical hurricane tracks, historical flood event data collection sites, counties with historical Federal Emergency Management Agency (FEMA) disaster declarations, Social Vulnerability Index data, and flood-related disaster data provided by FEMA (insurance claims, individual assistance applications, and repetitive loss records). Pre-identification of these locations in anticipation of a flood event ensures that areas of interest are being targeted and allows for expedited decision-making related to site selection, resulting in safer and more timely installation of equipment.
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| U S Geological Survey |
| 2016 |
In 2012, catchments were generated in the Delaware River Basin for 8-digit HUCs in the areas underlain by the Marcellus Shale (all of 02040101, 02040102, 02040103, 02040104; and headwater areas of 02040106 and 02040203) based on the National Hydrography Dataset (NHD) Strahler first- and second-order streams. There were areas that did not have a catchment generated so another methodology needed to be used in an attempt to fill in the 'gap areas'. A 900-cell, flow accumulation raster generated for the Pennsylvania StreamStats application was used as a surrogate stream layer with the same Strahler ordering system applied to help fill in the 'gap areas'. Points were manually placed at the downstream end of the Strahler Order 1 and 2 reaches using the surrogate streams as a guide. This manual point placement is different from the automated method used to develop the catchments generated from the NHD flowlines. The manual placement of the catchment pour points does not include a point downstream of a confluence, therefore, not as many catchments are generated in the 'gap-area' processing.
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| U S Geological Survey |
| 2016 |
In 2012, catchments were generated in the Delaware River Basin for 8-digit HUCs in areas underlain by the Marcellus Shale (all of 02040101, 02040102, 02040103, 02040104; and headwater areas of 02040106 and 02040203) based on the National Hydrography Dataset (NHD) Strahler first- and second-order streams. At that time, the remaining 8-digit HUCs were not included. The completion of HUCs 02040106 and 02040203, along with HUCs 02040105, 02040201, 02040202, 02040205, 02040206, and 02040207 were part of this current project.
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| U S Geological Survey |
| 2000 |
aerial photography of the Delaware Water Gap including the surrounding watersheds and tributaries
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| U S Geological Survey |
| 2000 |
Landuse for the Delaware Water Gap and Surrounding watersheds and tributaries
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| U S Geological Survey |
| 2023 |
As part of a study to quantify floodplain flood attenuation ecosystem services, datasets were developed representing a baseline (current floodplain condition) and counterfactual (floodplain flood storage removed) scenario for 18 sites in the Schuylkill River Watershed, Pennsylvania. This data release contains rasters (3-m resolution) of baseline and counterfactual flood depth grids for the 0.5, 0.2, 0.1, 0.04, 0.02, and 0.01 annual exceedance probability (AEP) scenarios in the Schuylkill River Watershed, Pennsylvania. Depth grid raster datasets were used as input for riverine flood modeling in the Federal Emergency Management Agency HAZUS Program to estimate damages to buildings under various flood intensities. The HAZUS Program is a tool to estimate damages and associated losses due to natural disasters like floods. The data release also contains polyline shapefiles of (1) six floodplain storage volume cross-sections for the 0.01 AEP baseline scenario flood inundation boundary at each USGS streamgage of interest and (2) water surface cross-sections extending across all areas of interest inundation boundaries based on the 0.01 counterfactual scenario boundary. Floodplain storage volume cross-sectional lines (Schuylkill_Volume_xns) were used in the approximation of average floodplain flood water storage capacity of each area of interest. Water surface cross-sections (Schuylkill_DepthGrid_xns) were used for water surface interpolation in depth grid processing
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| U S Geological Survey |
| 2002 |
The Assessment Unit is the fundamental unit used in the National Assessment Project for the assessment of undiscovered oil and gas resources. The Assessment Unit is defined within the context of the higher-level Total Petroleum System. The Assessment Unit is shown here as a geographic boundary interpreted, defined, and mapped by the geologist responsible for the province and incorporates a set of known or postulated oil and (or) gas accumulations sharing similar geologic, geographic, and temporal properties within the Total Petroleum System, such as source rock, timing, migration pathways, trapping mechanism, and hydrocarbon type. The Assessment Unit boundary is defined geologically as the limits of the geologic elements that define the Assessment Unit, such as limits of reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are Assessment Units that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the Assessment Unit boundary.
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| U S Geological Survey |
| 2002 |
Cell maps for each oil and gas assessment unit were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in an assessment unit or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, dry, or the type of production of the wells located within the cell is unknown. The well information was initially retrieved from the IHS Energy Group, PI/Dwights PLUS Well Data on CD-ROM, which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary PI/Dwights PLUS Well Data. No proprietary data are displayed or included in the cell maps. The data from PI/Dwights PLUS Well Data were current as of October 2001 when the cell maps were created in 2002.
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| U S Geological Survey |
| 2017 |
A breakthrough in water resources management occurred in 1961 when President Kennedy and the governors of Delaware, New Jersey, Pennsylvania, and New York for the first time signed concurrent compact legislation into law creating a regional body with the force of law to oversee a unified approach to managing a river system without regard to political boundaries. The members of this regional body - the Delaware River Basin Commission (DRBC) - include the four basin state governors and the Division Engineer, North Atlantic Division, U.S. Army Corps of Engineers, who serves as the federal representative. Commission programs include water quality protection, water supply allocation, regulatory review (permitting), water conservation initiatives, watershed planning, drought management, flood loss reduction, and recreation. Much of the new drilling interest taking place in northeastern Pennsylvania and southern New York is targeted at reaching the natural gas found in the Marcellus Shale formation, which underlies about 36 percent of the Delaware River Basin. Because the Marcellus Shale is considered a tight geologic formation, natural gas deposits were not previously thought to be practically and economically mineable using traditional techniques. New horizontal drilling and extraction methods, coupled with higher energy costs, have given energy companies reason to take a new interest in mining the natural gas deposits within the Marcellus Shale. In connection with natural gas drilling, the commission has identified three major areas of concern: 1.Gas drilling projects in the Marcellus Shale or other formations may have a substantial effect on the water resources of the basin by reducing the flow in streams and/or aquifers used to supply the significant amounts of fresh water needed in the natural gas mining process. 2.On-site drilling operations may potentially add, discharge or cause the release of pollutants into the ground water or surface water. 3.The recovered "frac water" must be treated and disposed of properly. DRBC is identifying methods, geospatial data, and other information to support decision making on how best to oversee the Marcellus Shale drilling in the Delaware River Basin (DRB).
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| U S Geological Survey |
| 2017 |
A breakthrough in water resources management occurred in 1961 when President Kennedy and the governors of Delaware, New Jersey, Pennsylvania, and New York for the first time signed concurrent compact legislation into law creating a regional body with the force of law to oversee a unified approach to managing a river system without regard to political boundaries. The members of this regional body - the Delaware River Basin Commission (DRBC) - include the four basin state governors and the Division Engineer, North Atlantic Division, U.S. Army Corps of Engineers, who serves as the federal representative. Commission programs include water quality protection, water supply allocation, regulatory review (permitting), water conservation initiatives, watershed planning, drought management, flood loss reduction, and recreation. Much of the new drilling interest taking place in northeastern Pennsylvania and southern New York is targeted at reaching the natural gas found in the Marcellus Shale formation, which underlies about 36 percent of the Delaware River Basin. Because the Marcellus Shale is considered a tight geologic formation, natural gas deposits were not previously thought to be practically and economically mineable using traditional techniques. New horizontal drilling and extraction methods, coupled with higher energy costs, have given energy companies reason to take a new interest in mining the natural gas deposits within the Marcellus Shale. In connection with natural gas drilling, the commission has identified three major areas of concern: 1.Gas drilling projects in the Marcellus Shale or other formations may have a substantial effect on the water resources of the basin by reducing the flow in streams and/or aquifers used to supply the significant amounts of fresh water needed in the natural gas mining process. 2.On-site drilling operations may potentially add, discharge or cause the release of pollutants into the ground water or surface water. 3.The recovered "frac water" must be treated and disposed of properly. DRBC is identifying methods, geospatial data, and other information to support decision making on how best to oversee the Marcellus Shale drilling in the Delaware River Basin (DRB).
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| U S Geological Survey |
| 2017 |
A breakthrough in water resources management occurred in 1961 when President Kennedy and the governors of Delaware, New Jersey, Pennsylvania, and New York for the first time signed concurrent compact legislation into law creating a regional body with the force of law to oversee a unified approach to managing a river system without regard to political boundaries. The members of this regional body - the Delaware River Basin Commission (DRBC) - include the four basin state governors and the Division Engineer, North Atlantic Division, U.S. Army Corps of Engineers, who serves as the federal representative. Commission programs include water quality protection, water supply allocation, regulatory review (permitting), water conservation initiatives, watershed planning, drought management, flood loss reduction, and recreation. Much of the new drilling interest taking place in northeastern Pennsylvania and southern New York is targeted at reaching the natural gas found in the Marcellus Shale formation, which underlies about 36 percent of the Delaware River Basin. Because the Marcellus Shale is considered a tight geologic formation, natural gas deposits were not previously thought to be practically and economically mineable using traditional techniques. New horizontal drilling and extraction methods, coupled with higher energy costs, have given energy companies reason to take a new interest in mining the natural gas deposits within the Marcellus Shale. In connection with natural gas drilling, the commission has identified three major areas of concern: 1.Gas drilling projects in the Marcellus Shale or other formations may have a substantial effect on the water resources of the basin by reducing the flow in streams and/or aquifers used to supply the significant amounts of fresh water needed in the natural gas mining process. 2.On-site drilling operations may potentially add, discharge or cause the release of pollutants into the ground water or surface water. 3.The recovered "frac water" must be treated and disposed of properly. DRBC is identifying methods, geospatial data, and other information to support decision making on how best to oversee the Marcellus Shale drilling in the Delaware River Basin (DRB).
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| U S Geological Survey |
| 2017 |
A breakthrough in water resources management occurred in 1961 when President Kennedy and the governors of Delaware, New Jersey, Pennsylvania, and New York for the first time signed concurrent compact legislation into law creating a regional body with the force of law to oversee a unified approach to managing a river system without regard to political boundaries. The members of this regional body - the Delaware River Basin Commission (DRBC) - include the four basin state governors and the Division Engineer, North Atlantic Division, U.S. Army Corps of Engineers, who serves as the federal representative. Commission programs include water quality protection, water supply allocation, regulatory review (permitting), water conservation initiatives, watershed planning, drought management, flood loss reduction, and recreation. Much of the new drilling interest taking place in northeastern Pennsylvania and southern New York is targeted at reaching the natural gas found in the Marcellus Shale formation, which underlies about 36 percent of the Delaware River Basin. Because the Marcellus Shale is considered a tight geologic formation, natural gas deposits were not previously thought to be practically and economically mineable using traditional techniques. New horizontal drilling and extraction methods, coupled with higher energy costs, have given energy companies reason to take a new interest in mining the natural gas deposits within the Marcellus Shale. In connection with natural gas drilling, the commission has identified three major areas of concern: 1.Gas drilling projects in the Marcellus Shale or other formations may have a substantial effect on the water resources of the basin by reducing the flow in streams and/or aquifers used to supply the significant amounts of fresh water needed in the natural gas mining process. 2.On-site drilling operations may potentially add, discharge or cause the release of pollutants into the ground water or surface water. 3.The recovered "frac water" must be treated and disposed of properly. DRBC is identifying methods, geospatial data, and other information to support decision making on how best to oversee the Marcellus Shale drilling in the Delaware River Basin (DRB).
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| U S Geological Survey |
| 2017 |
A breakthrough in water resources management occurred in 1961 when President Kennedy and the governors of Delaware, New Jersey, Pennsylvania, and New York for the first time signed concurrent compact legislation into law creating a regional body with the force of law to oversee a unified approach to managing a river system without regard to political boundaries. The members of this regional body - the Delaware River Basin Commission (DRBC) - include the four basin state governors and the Division Engineer, North Atlantic Division, U.S. Army Corps of Engineers, who serves as the federal representative. Commission programs include water quality protection, water supply allocation, regulatory review (permitting), water conservation initiatives, watershed planning, drought management, flood loss reduction, and recreation. Much of the new drilling interest taking place in northeastern Pennsylvania and southern New York is targeted at reaching the natural gas found in the Marcellus Shale formation, which underlies about 36 percent of the Delaware River Basin. Because the Marcellus Shale is considered a tight geologic formation, natural gas deposits were not previously thought to be practically and economically mineable using traditional techniques. New horizontal drilling and extraction methods, coupled with higher energy costs, have given energy companies reason to take a new interest in mining the natural gas deposits within the Marcellus Shale. In connection with natural gas drilling, the commission has identified three major areas of concern: 1.Gas drilling projects in the Marcellus Shale or other formations may have a substantial effect on the water resources of the basin by reducing the flow in streams and/or aquifers used to supply the significant amounts of fresh water needed in the natural gas mining process. 2.On-site drilling operations may potentially add, discharge or cause the release of pollutants into the ground water or surface water. 3.The recovered "frac water" must be treated and disposed of properly. DRBC is identifying methods, geospatial data, and other information to support decision making on how best to oversee the Marcellus Shale drilling in the Delaware River Basin (DRB).
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| U S Geological Survey |
| 2017 |
A breakthrough in water resources management occurred in 1961 when President Kennedy and the governors of Delaware, New Jersey, Pennsylvania, and New York for the first time signed concurrent compact legislation into law creating a regional body with the force of law to oversee a unified approach to managing a river system without regard to political boundaries. The members of this regional body - the Delaware River Basin Commission (DRBC) - include the four basin state governors and the Division Engineer, North Atlantic Division, U.S. Army Corps of Engineers, who serves as the federal representative. Commission programs include water quality protection, water supply allocation, regulatory review (permitting), water conservation initiatives, watershed planning, drought management, flood loss reduction, and recreation. Much of the new drilling interest taking place in northeastern Pennsylvania and southern New York is targeted at reaching the natural gas found in the Marcellus Shale formation, which underlies about 36 percent of the Delaware River Basin. Because the Marcellus Shale is considered a tight geologic formation, natural gas deposits were not previously thought to be practically and economically mineable using traditional techniques. New horizontal drilling and extraction methods, coupled with higher energy costs, have given energy companies reason to take a new interest in mining the natural gas deposits within the Marcellus Shale. In connection with natural gas drilling, the commission has identified three major areas of concern: 1.Gas drilling projects in the Marcellus Shale or other formations may have a substantial effect on the water resources of the basin by reducing the flow in streams and/or aquifers used to supply the significant amounts of fresh water needed in the natural gas mining process. 2.On-site drilling operations may potentially add, discharge or cause the release of pollutants into the ground water or surface water. 3.The recovered "frac water" must be treated and disposed of properly. DRBC is identifying methods, geospatial data, and other information to support decision making on how best to oversee the Marcellus Shale drilling in the Delaware River Basin (DRB).
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| U S Geological Survey |
| 1992 |
Orthophotos combine the image characteristics of a
photograph with the geometric qualities of a map. The
primary digital orthophotoquad (DOQ) is a 1-meter ground
resolution, quarter-quadrangle (3.75-minutes of latitude
by 3.75-minutes of longitude) image cast on the Universal
Transverse Mercator Projection (UTM) on the North
American Datum of 1983 (NAD83).The geographic extent of
the DOQ is equivalent to a quarter-quad plus The overedge
ranges a minimum of 50 meters to a maximum of 300 meters
beyond the extremes of the primary and secondary corner
points. The overedge is included to facilitate tonal
matching for mosaicking and for the placement of the NAD83
and secondary datum corner ticks. The normal orientation
of data is by lines (rows) and samples (columns). Each
line contains a series of pixels ordered from west to
east with the order of the lines from north to south.
The standard, archived digital orthophoto is formatted as
four ASCII header records, followed by a series of 8-bit
binary image data records. The radiometric image
brightness values are stored as 256 gray levels ranging
from 0 to 255. The metadata embedded in the digital
orthophoto contain a wide range of descriptive
information including format source information,
production instrumentation and dates, and data to assist
with displaying and georeferencing the image.
DOQ images are acquired as a part of the USGS' National Aerial Photography Program (NAPP).
Through NAPP imagery for each state is produced on a 7 year cycle.
These images are the NAPP III cycle which will run from 1997-2001
These DOQQ's are distributed through PASDA as GeoTIFF images as received from USGS.
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| U S Geological Survey |
| 1997 |
Orthophotos combine the image characteristics of a
photograph with the geometric qualities of a map. The
primary digital orthophotoquad (DOQ) is a 1-meter ground
resolution, quarter-quadrangle (3.75-minutes of latitude
by 3.75-minutes of longitude) image cast on the Universal
Transverse Mercator Projection (UTM) on the North
American Datum of 1983 (NAD83).The geographic extent of
the DOQ is equivalent to a quarter-quad plus The overedge
ranges a minimum of 50 meters to a maximum of 300 meters
beyond the extremes of the primary and secondary corner
points. The overedge is included to facilitate tonal
matching for mosaicking and for the placement of the NAD83
and secondary datum corner ticks. The normal orientation
of data is by lines (rows) and samples (columns). Each
line contains a series of pixels ordered from west to
east with the order of the lines from north to south.
The standard, archived digital orthophoto is formatted as
four ASCII header records, followed by a series of 8-bit
binary image data records. The radiometric image
brightness values are stored as 256 gray levels ranging
from 0 to 255. The metadata embedded in the digital
orthophoto contain a wide range of descriptive
information including format source information,
production instrumentation and dates, and data to assist
with displaying and georeferencing the image.
DOQ images are acquired as a part of the USGS' National Aerial Photography Program (NAPP).
Through NAPP imagery for each state is produced on a 7 year cycle.
These images are the NAPP III cycle which will run from 1997-2001
These DOQQ's are distributed through PASDA as GeoTIFF images as received from USGS.
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| U S Geological Survey |
| 2000 |
Orthophotos combine the image characteristics of a
photograph with the geometric qualities of a map. The
primary digital orthophotoquad (DOQ) is a 1-meter ground
resolution, quarter-quadrangle (3.75-minutes of latitude
by 3.75-minutes of longitude) image cast on the Universal
Transverse Mercator Projection (UTM) on the North
American Datum of 1983 (NAD83).The geographic extent of
the DOQ is equivalent to a quarter-quad plus The overedge
ranges a minimum of 50 meters to a maximum of 300 meters
beyond the extremes of the primary and secondary corner
points. The overedge is included to facilitate tonal
matching for mosaicking and for the placement of the NAD83
and secondary datum corner ticks. The normal orientation
of data is by lines (rows) and samples (columns). Each
line contains a series of pixels ordered from west to
east with the order of the lines from north to south.
The standard, archived digital orthophoto is formatted as
four ASCII header records, followed by a series of 8-bit
binary image data records. The radiometric image
brightness values are stored as 256 gray levels ranging
from 0 to 255. The metadata embedded in the digital
orthophoto contain a wide range of descriptive
information including format source information,
production instrumentation and dates, and data to assist
with displaying and georeferencing the image.
DOQ images are acquired as a part of the USGS' National Aerial Photography Program (NAPP).
Through NAPP imagery for each state is produced on a 7 year cycle.
These images are the NAPP III cycle which will run from 1997-2001
These DOQQ's are distributed through PASDA as GeoTIFF images as received from USGS.
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| U S Geological Survey |
| 1997 |
Orthophotos combine the image characteristics of a
photograph with the geometric qualities of a map. The
primary digital orthophotoquad (DOQ) is a 1-meter ground
resolution, quarter-quadrangle (3.75-minutes of latitude
by 3.75-minutes of longitude) image cast on the Universal
Transverse Mercator Projection (UTM) on the North
American Datum of 1983 (NAD83).The geographic extent of
the DOQ is equivalent to a quarter-quad plus The overedge
ranges a minimum of 50 meters to a maximum of 300 meters
beyond the extremes of the primary and secondary corner
points. The overedge is included to facilitate tonal
matching for mosaicking and for the placement of the NAD83
and secondary datum corner ticks. The normal orientation
of data is by lines (rows) and samples (columns). Each
line contains a series of pixels ordered from west to
east with the order of the lines from north to south.
The standard, archived digital orthophoto is formatted as
four ASCII header records, followed by a series of 8-bit
binary image data records. The radiometric image
brightness values are stored as 256 gray levels ranging
from 0 to 255. The metadata embedded in the digital
orthophoto contain a wide range of descriptive
information including format source information,
production instrumentation and dates, and data to assist
with displaying and georeferencing the image.
DOQ images are acquired as a part of the USGS' National Aerial Photography Program (NAPP).
Through NAPP imagery for each state is produced on a 7 year cycle.
These images are the NAPP III cycle which will run from 1997-2001
These DOQQ's are distributed through PASDA as GeoTIFF images as received from USGS.
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| U S Geological Survey |
| 1993 |
Orthophotos combine the image characteristics of a photograph with the geometric qualities of a map. The primary digital orthophotoquad (DOQ) is a 1-meter ground resolution, quarter-quadrangle (3.75-minutes of latitude by 3.75-minutes of longitude) image cast on the Universal Transverse Mercator Projection (UTM) on the North American Datum of 1983 (NAD83).The geographic extent of the DOQ is equivalent to a quarter-quad plus The overedge ranges a minimum of 50 meters to a maximum of 300 meters beyond the extremes of the primary and secondary corner points. The overedge is included to facilitate tonal matching for mosaicking and for the placement of the NAD83 and secondary datum corner ticks. The normal orientation of data is by lines (rows) and samples (columns). Each line contains a series of pixels ordered from west to east with the order of the lines from north to south. The standard, archived digital orthophoto is formatted as four ASCII header records, followed by a series of 8-bit binary image data records. The radiometric image brightness values are stored as 256 gray levels ranging from 0 to 255. The metadata embedded in the digital orthophoto contain a wide range of descriptive information including format source information, production instrumentation and dates, and data to assist with displaying and georeferencing the image. DOQ images are acquired as a part of the USGS' National Aerial Photography Program (NAPP). Through NAPP imagery for each state is produced on a 7 year cycle. These images are the NAPP III cycle which will run from 1997-2001 These DOQQ's are distributed through PASDA as GeoTIFF images as received from USGS.
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| U S Geological Survey |
| 1999 |
Orthophotos combine the image characteristics of a photograph with the geometric qualities of a map. The primary digital orthophotoquad (DOQ) is a 1-meter ground resolution, quarter-quadrangle (3.75-minutes of latitude by 3.75-minutes of longitude) image cast on the Universal Transverse Mercator Projection (UTM) on the North American Datum of 1983 (NAD83).The geographic extent of the DOQ is equivalent to a quarter-quad plus The overedge ranges a minimum of 50 meters to a maximum of 300 meters beyond the extremes of the primary and secondary corner points. The overedge is included to facilitate tonal matching for mosaicking and for the placement of the NAD83 and secondary datum corner ticks. The normal orientation of data is by lines (rows) and samples (columns). Each line contains a series of pixels ordered from west to east with the order of the lines from north to south. The standard, archived digital orthophoto is formatted as four ASCII header records, followed by a series of 8-bit binary image data records. The radiometric image brightness values are stored as 256 gray levels ranging from 0 to 255. The metadata embedded in the digital orthophoto contain a wide range of descriptive information including format source information, production instrumentation and dates, and data to assist with displaying and georeferencing the image. DOQ images are acquired as a part of the USGS' National Aerial Photography Program (NAPP). Through NAPP imagery for each state is produced on a 7 year cycle. These images are the NAPP III cycle which will run from 1997-2001 These DOQQ's are distributed through PASDA as GeoTIFF images as received from USGS.
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| U S Geological Survey |
| 2000 |
A scope of work was developed in response to a request by the U. S. Army Corps
of Engineers, Philadelphia District. The request was to perform a topographic
change grid analysis for the Frankford 7.5-minute quadrangle, 1:24,000-scale
topographic map, which includes the Wissinoming neighborhood, and the Germantown 7.5-minute quadrangle, which includes the Logan and Feltonville neighborhoods of the City of Philadelphia. The following tasks were performed under this scope of work: A GPS-corrected GIS grid analysis for each quadrangle was completed and is accompanied by documentation that describes procedures and provides metadata of the informational content of the GIS. A high-resolution global positioning system (GPS) survey was conducted for each topographic quadrangle in order to evaluate and correct systematic discrepancies in elevation between the modern and historic surveys. Prior to release, the fully documented GPS-corrected GIS grid analysis for each quadrangle was reviewed for (1) com-pleteness of documentation and for (2) appropriate analysis and discussion of uncertainties.
The following report is in fulfillment of the tasks outlined in this scope of work and was performed by the U. S. Geological Survey for the U. S. Army Corps of Engineers, Philadelphia District under MIPR agreement number: W25PHS93358288.
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| U S Geological Survey |
| 2023 |
This dataset consists of Pennsylvania bridge over water locations that are being considered for flood data collection. The purpose of this effort is to identify potential locations in Pennsylvania where additional or updated water level data may be needed during or after major storm events. Criteria involved in the identification of potential locations for flood data collection includes locations of bridges over water, scour-critical bridges, densely populated areas, historical hurricane tracks, historical flood event data collection sites, counties with historical Federal Emergency Management Agency (FEMA) disaster declarations, Social Vulnerability Index data, and flood-related disaster data provided by FEMA (insurance claims, individual assistance applications, and repetitive loss records). Pre-identification of these locations in anticipation of a flood event ensures that areas of interest are being targeted and allows for expedited decision-making related to site selection, resulting in safer and more timely installation of equipment.
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| U S Geological Survey |
| 2018 |
The Geographic Names Information System contains information about physical and cultural geographic features of all types in the United States, associated areas, and Antarctica, current and historical, but not including roads and highways. The database holds the Federally recognized name of each feature and defines the feature location by state, county, USGS topographic map, and geographic coordinates. Other attributes include names or spellings other than the official name, feature designations, feature classification, historical and descriptive information, and for some categories the geometric boundaries. The database assigns a unique, permanent feature identifier, the Feature ID, as a standard Federal key for accessing, integrating, or reconciling feature data from multiple data sets. The GNIS collects data from a broad program of partnerships with Federal, State, and local government agencies and other authorized contributors. The GNIS provides data to all levels of government and to the public, as well as to numerous applications through a web query site, web map and feature services, file download services, and customized files
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| U S Geological Survey |
| 2008 |
The Geographic Names Information System (GNIS), developed by the U.S. Geological Survey in cooperation with the U.S. Board on Geographic Names (BGN), contains information about physical and cultural geographic features in the United States and associated areas, both current and historical, but not including roads and highways. The database also contains geographic names in Antarctica. The database holds the Federally recognized name of each feature and defines the location of the feature by state, county, USGS topographic map, and geographic coordinates. Other feature attributes include names or spellings other than the official name, feature designations, feature class, historical and descriptive information, and for some categories of features the geometric boundaries. The database assigns a unique feature identifier, a random number, that is a key for accessing, integrating, or reconciling GNIS data with other data sets. The GNIS is our Nation's official repository of domestic geographic feature names information.
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Spreadsheet
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GeoJSON
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| U S Geological Survey |
| 1981 |
The Geographic Names Information System (GNIS), developed by the U.S. Geological Survey in cooperation with the U.S. Board on Geographic Names (BGN), contains information about physical and cultural geographic features in the United States and associated areas, both current and historical, but not including roads and highways. The database also contains geographic names in Antarctica. The database holds the Federally recognized name of each feature and defines the location of the feature by state, county, USGS topographic map, and geographic coordinates. Other feature attributes include names or spellings other than the official name, feature designations, feature class, historical and descriptive information, and for some categories of features the geometric boundaries. The database assigns a unique feature identifier, a random number, that is a key for accessing, integrating, or reconciling GNIS data with other data sets. The GNIS is our Nation's official repository of domestic geographic feature names information.
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KMZ
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Spreadsheet
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GeoJSON
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| U S Geological Survey |
| 2007 |
The Geographic Names Information System (GNIS), developed by the U.S. Geological Survey in cooperation with the U.S. Board on Geographic Names (BGN), contains information about physical and cultural geographic features in the United States and associated areas, both current and historical, but not including roads and highways. The database also contains geographic names in Antarctica. The database holds the Federally recognized name of each feature and defines the location of the feature by state, county, USGS topographic map, and geographic coordinates. Other feature attributes include names or spellings other than the official name, feature designations, feature class, historical and descriptive information, and for some categories of features the geometric boundaries. The database assigns a unique feature identifier, a random number, that is a key for accessing, integrating, or reconciling GNIS data with other data sets. The GNIS is our Nation's official repository of domestic geographic feature names information.
Metadata
|
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KMZ
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Spreadsheet
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GeoJSON
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| U S Geological Survey |
| 2017 |
The Geographic Names Information System (GNIS), developed by the U.S. Geological Survey in cooperation with the U.S. Board on Geographic Names (BGN), contains information about physical and cultural geographic features in the United States and associated areas, both current and historical, but not including roads and highways. The database also contains geographic names in Antarctica. The database holds the Federally recognized name of each feature and defines the location of the feature by state, county, USGS topographic map, and geographic coordinates. Other feature attributes include names or spellings other than the official name, feature designations, feature class, historical and descriptive information, and for some categories of features the geometric boundaries. The database assigns a unique feature identifier, a random number, that is a key for accessing, integrating, or reconciling GNIS data with other data sets. The GNIS is our Nation's official repository of domestic geographic feature names information.
Metadata
|
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|
Preview
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KMZ
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Spreadsheet
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GeoJSON
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or
Feature
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| U S Geological Survey |
| 2000 |
A scope of work was developed in response to a request by the U. S. Army Corps
of Engineers, Philadelphia District. The request was to perform a topographic
change grid analysis for the Frankford 7.5-minute quadrangle, 1:24,000-scale
topographic map, which includes the Wissinoming neighborhood, and the Germantown 7.5-minute quadrangle, which includes the Logan and Feltonville neighborhoods of the City of Philadelphia. The following tasks were performed under this scope of work: A GPS-corrected GIS grid analysis for each quadrangle was completed and is accompanied by documentation that describes procedures and provides metadata of the informational content of the GIS. A high-resolution global positioning system (GPS) survey was conducted for each topographic quadrangle in order to evaluate and correct systematic discrepancies in elevation between the modern and historic surveys. Prior to release, the fully documented GPS-corrected GIS grid analysis for each quadrangle was reviewed for (1) com-pleteness of documentation and for (2) appropriate analysis and discussion of uncertainties.
The following report is in fulfillment of the tasks outlined in this scope of work and was performed by the U. S. Geological Survey for the U. S. Army Corps of Engineers, Philadelphia District under MIPR agreement number: W25PHS93358288.
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| U S Geological Survey |
| 2002 |
Cell maps for each oil and gas assessment unit were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in an assessment unit or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, dry, or the type of production of the wells located within the cell is unknown. The well information was initially retrieved from the IHS Energy Group, PI/Dwights PLUS Well Data on CD-ROM, which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary PI/Dwights PLUS Well Data. No proprietary data are displayed or included in the cell maps. The data from PI/Dwights PLUS Well Data were current as of October 2001 when the cell maps were created in 2002.
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| U S Geological Survey |
| 2002 |
The Assessment Unit is the fundamental unit used in the National Assessment Project for the assessment of undiscovered oil and gas resources. The Assessment Unit is defined within the context of the higher-level Total Petroleum System. The Assessment Unit is shown here as a geographic boundary interpreted, defined, and mapped by the geologist responsible for the province and incorporates a set of known or postulated oil and (or) gas accumulations sharing similar geologic, geographic, and temporal properties within the Total Petroleum System, such as source rock, timing, migration pathways, trapping mechanism, and hydrocarbon type. The Assessment Unit boundary is defined geologically as the limits of the geologic elements that define the Assessment Unit, such as limits of reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are Assessment Units that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the Assessment Unit boundary.
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| U S Geological Survey |
| 2002 |
The Assessment Unit is the fundamental unit used in the National Assessment Project for the assessment of undiscovered oil and gas resources. The Assessment Unit is defined within the context of the higher-level Total Petroleum System. The Assessment Unit is shown here as a geographic boundary interpreted, defined, and mapped by the geologist responsible for the province and incorporates a set of known or postulated oil and (or) gas accumulations sharing similar geologic, geographic, and temporal properties within the Total Petroleum System, such as source rock, timing, migration pathways, trapping mechanism, and hydrocarbon type. The Assessment Unit boundary is defined geologically as the limits of the geologic elements that define the Assessment Unit, such as limits of reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are Assessment Units that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the Assessment Unit
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| U S Geological Survey |
| 2002 |
Cell maps for each oil and gas assessment unit were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in an assessment unit or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, dry, or the type of production of the wells located within the cell is unknown. The well information was initially retrieved from the IHS Energy Group, PI/Dwights PLUS Well Data on CD-ROM, which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary PI/Dwights PLUS Well Data. No proprietary data are displayed or included in the cell maps. The data from PI/Dwights PLUS Well Data were current as of October 2001 when the cell maps were created in 2002.
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| U S Geological Survey |
| 2005 |
Historic USGS 15 minute topographic maps for Pennsylvania as collected from the MapTech Historical Map Collection at '. Scanned map images from MapTech were downloaded, assembled, and registered and rectified via Arc/Info to the UTM Zone 17/18 NAD83 projection.
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| U S Geological Survey |
| 2006 |
A newly revised version of the historic USGS 15 minute topographic maps for Pennsylvania as collected from the MapTech Historical Map Collection at 'http://historical.maptech.com'. As an improvement to the initial version, the original scanned images from MapTech were downloaded, assembled with mosaicing software, and georeferenced to the statewide Albers NAD83 projection.
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| U S Geological Survey |
| 2002 |
The Assessment Unit is the fundamental unit used in the National Assessment Project for the assessment of undiscovered oil and gas resources. The Assessment Unit is defined within the context of the higher-level Total Petroleum System. The Assessment Unit is shown here as a geographic boundary interpreted, defined, and mapped by the geologist responsible for the province and incorporates a set of known or postulated oil and (or) gas accumulations sharing similar geologic, geographic, and temporal properties within the Total Petroleum System, such as source rock, timing, migration pathways, trapping mechanism, and hydrocarbon type. The Assessment Unit boundary is defined geologically as the limits of the geologic elements that define the Assessment Unit, such as limits of reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are Assessment Units that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the Assessment Unit boundary.
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KMZ
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| U S Geological Survey |
| 2002 |
Cell maps for each oil and gas assessment unit were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in an assessment unit or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, dry, or the type of production of the wells located within the cell is unknown. The well information was initially retrieved from the IHS Energy Group, PI/Dwights PLUS Well Data on CD-ROM, which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary PI/Dwights PLUS Well Data. No proprietary data are displayed or included in the cell maps. The data from PI/Dwights PLUS Well Data were current as of October 2001 when the cell maps were created in 2002.
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| U S Geological Survey |
| 2015 |
This data will assist in the evaluation of coastal storm damage impacts; aid in post-event reconstruction and mitigation planning for future events and collect LiDAR for counties heavily impacted by storm and flooding for which data is incomplete or inadequate to conduct proper analysis, as part of USGS Hurricane Sandy response.
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| U S Geological Survey |
| 2015 |
This data will assist in the evaluation of coastal storm damage impacts; aid in post-event reconstruction and mitigation planning for future events and collect LiDAR for counties heavily impacted by storm and flooding for which data is incomplete or inadequate to conduct proper analysis, as part of USGS Hurricane Sandy response.
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| U S Geological Survey |
| 2015 |
This data will assist in the evaluation of coastal storm damage impacts; aid in post-event reconstruction and mitigation planning for future events and collect LiDAR for counties heavily impacted by storm and flooding for which data is incomplete or inadequate to conduct proper analysis, as part of USGS Hurricane Sandy response.
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| U S Geological Survey |
| 2002 |
The Assessment Unit is the fundamental unit used in the National Assessment Project for the assessment of undiscovered oil and gas resources. The Assessment Unit is defined within the context of the higher-level Total Petroleum System. The Assessment Unit is shown here as a geographic boundary interpreted, defined, and mapped by the geologist responsible for the province and incorporates a set of known or postulated oil and (or) gas accumulations sharing similar geologic, geographic, and temporal properties within the Total Petroleum System, such as source rock, timing, migration pathways, trapping mechanism, and hydrocarbon type. The Assessment Unit boundary is defined geologically as the limits of the geologic elements that define the Assessment Unit, such as limits of reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are Assessment Units that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the Assessment Unit boundary.
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KMZ
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| U S Geological Survey |
| 2002 |
Cell maps for each oil and gas assessment unit were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in an assessment unit or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, dry, or the type of production of the wells located within the cell is unknown. The well information was initially retrieved from the IHS Energy Group, PI/Dwights PLUS Well Data on CD-ROM, which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary PI/Dwights PLUS Well Data. No proprietary data are displayed or included in the cell maps. The data from PI/Dwights PLUS Well Data were current as of October 2001 when the cell maps were created in 2002.
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| U S Geological Survey |
| 2002 |
The USGS Central Region Energy Team assesses oil and gas resources of the United States. The onshore and State water areas of the United States comprise 71 provinces. Within these provinces, Total Petroleum Systems are defined and Assessment Units are defined and assessed. Each of these provinces is defined geologically, and most province boundaries are defined by major geologic changes.
The Appalachian Basin Province is located in the eastern United States, encompassing all or parts of the counties in Alabama, Georgia, Kentucky, Maryland, New Jersey, New York, North Carolina, Ohio, Pennsylvania, Tennessee, Virginia, and West Virginia. The main population centers within the study area are Birmingham, Alabama; Buffalo, New York; Cleveland, Ohio; Pittsburgh, Pennsylvania; Chattanooga, Tennessee; and Roanoke, Virginia. The main Interstates are I-20, I-24, I-40, I-59, I-64, I-65, I-66, I-70, I-71, I-75, I-76, I-77, I-78, I-79, I-80, I-81, I-83, I-84, I-87, I-88, and I-90. The Ohio, Susquehanna, Allegheny, Tennessee, Coosa, Delaware, New, Potomac, and Scioto Rivers and their tributaries drain the area. The province boundary was drawn to include the geologic structures generally considered to be in or bounding the Appalachian Basin.
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| U S Geological Survey |
| 2004 |
The National Atmospheric Deposition Program/National Trends Network (NADP/NTN) is a nationwide network of precipitation monitoring sites. The network is a cooperative effort between many different groups, including the State Agricultural Experiment Stations, U.S. Geological Survey, U.S. Department of Agriculture, and numerous other governmental and private entities. The NADP/NTN has grown from 22 stations at the end of 1978, our first year, to over 250 sites spanning the continental United States, Alaska, and Puerto Rico, and the Virgin Islands.
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| U S Geological Survey |
| 2005 |
The National Atmospheric Deposition Program/National Trends Network (NADP/NTN) is a nationwide network of precipitation monitoring sites. The network is a cooperative effort between many different groups, including the State Agricultural Experiment Stations, U.S. Geological Survey, U.S. Department of Agriculture, and numerous other governmental and private entities. The NADP/NTN has grown from 22 stations at the end of 1978, our first year, to over 250 sites spanning the continental United States, Alaska, and Puerto Rico, and the Virgin Islands.
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| U S Geological Survey |
| 1999 |
The U.S. Geological Survey has developed a National Elevation Database (NED).The NED is a seamless mosaic of best-available elevation data. The 7.5-minute elevation data for the conterminous United States are the primary initial source data. In addition to the availability of complete 7.5-minute data, efficient processing methods were developed to filter production artifacts in the existing data, convert to a consistent datum, edge-match, fill slivers of missing data at quadrangle seams, recast the data to a consistent geographic projection and convert all elevation values to decimal meters as a consistent unit of measure.
NED has a resolution of one-third arc-second (approximately 10 meters) for much of the conterminous United States, Hawaii and Puerto Rico in a NAD83 datum. There is a resolution of two arc-seconds for Alaska and the datum is NAD27.
NED at 10 meters is created using the same methods outlined above with the source data being mostly the 10m DEMs. DEMs at 5 meters, 1/3 arc-second, and 1/9 arc-second maps are also used where available. In some cases, the 10m NED is resampled from LIDAR or created using aerial photography.
One of the effects of the NED processing steps is a much-improved base of elevation data for calculating slope and hydrologic derivatives. Artifact removal greatly improves the quality of the slope, shaded-relief, and synthetic drainage information that can be derived from the elevation data. Geospatial elevation data are used by the scientific and resource management communities for global change research, hydrologic modeling, resource monitoring, mapping, and visualization applications.
NRCS has elected to ONLY serve NED 10 which is 10 meter or better and not NED 10 which was resampled from 30 meter. NRCS also serves the maps in a UTM projection. These two facts differentiate the maps from those served at http://seamless.usgs.gov/.
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| U S Geological Survey |
| 1999 |
The U.S. Geological Survey has developed a National Elevation Dataset (NED). The NED is a seamless mosaic of best-available elevation data. The 7.5-minute elevation data for the conterminous United States are the primary initial source data. In addition to the availability of complete 7.5-minute data, efficient processing methods were developed to filter production artifacts in the existing data, convert to the NAD83 datum, edge-match, and fill slivers of missing data at quadrangle seams. One of the effects of the NED processing steps is a much-improved base of elevation data for calculating slope and hydrologic derivatives. NED files are available on CD from the EROS data center as 1x1 degree tiles. For online distribution the files on PASDA have been aggregated by county and projected into the Albers Equal Area projection.
Data incomplete, areas not mapped when screened at small scales during low
level radioactive waste siting analysis.
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| U S Geological Survey |
| 2004 |
The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water bodies. Reaches are also defined on waterbodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Geographic Data Committee.
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| U S Geological Survey |
| 2021 |
The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released five National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, 2011, and 2016. The 2016 release saw landcover created for additional years of 2003, 2008, and 2013. These products provide spatially explicit and reliable information on the Nation’s land cover and land cover change. To continue the legacy of NLCD and further establish a long-term monitoring capability for the Nation’s land resources, the USGS has designed a new generation of NLCD products named NLCD 2019. The NLCD 2019 design aims to provide innovative, consistent, and robust methodologies for production of a multi-temporal land cover and land cover change database from 2001 to 2019 at 2–3-year intervals. Comprehensive research was conducted and resulted in developed strategies for NLCD 2019: continued integration between impervious surface and all landcover products with impervious surface being directly mapped as developed classes in the landcover, a streamlined compositing process for assembling and preprocessing based on Landsat imagery and geospatial ancillary datasets; a multi-source integrated training data development and decision-tree based land cover classifications; a temporally, spectrally, and spatially integrated land cover change analysis strategy; a hierarchical theme-based post-classification and integration protocol for generating land cover and change products; a continuous fields biophysical parameters modeling method; and an automated scripted operational system for the NLCD 2019 production. The performance of the developed strategies and methods were tested in twenty composite referenced areas throughout the conterminous U.S. An overall accuracy assessment from the 2016 publication give a 91% overall landcover accuracy, with the developed classes also showing a 91% accuracy in overall developed. Results from this study confirm the robustness of this comprehensive and highly automated procedure for NLCD 2019 operational mapping. Questions about the NLCD 2019 land cover product can be directed to the NLCD 2019 land cover mapping team at USGS EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov. See included spatial metadata for more details.
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| U S Geological Survey |
| 2021 |
The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released five National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, 2011, and 2016. The 2016 release saw landcover created for additional years of 2003, 2008, and 2013. These products provide spatially explicit and reliable information on the Nation’s land cover and land cover change. To continue the legacy of NLCD and further establish a long-term monitoring capability for the Nation’s land resources, the USGS has designed a new generation of NLCD products named NLCD 2019. The NLCD 2019 design aims to provide innovative, consistent, and robust methodologies for production of a multi-temporal land cover and land cover change database from 2001 to 2019 at 2–3-year intervals. Comprehensive research was conducted and resulted in developed strategies for NLCD 2019: continued integration between impervious surface and all landcover products with impervious surface being directly mapped as developed classes in the landcover, a streamlined compositing process for assembling and preprocessing based on Landsat imagery and geospatial ancillary datasets; a multi-source integrated training data development and decision-tree based land cover classifications; a temporally, spectrally, and spatially integrated land cover change analysis strategy; a hierarchical theme-based post-classification and integration protocol for generating land cover and change products; a continuous fields biophysical parameters modeling method; and an automated scripted operational system for the NLCD 2019 production. The performance of the developed strategies and methods were tested in twenty composite referenced areas throughout the conterminous U.S. An overall accuracy assessment from the 2016 publication give a 91% overall landcover accuracy, with the developed classes also showing a 91% accuracy in overall developed. Results from this study confirm the robustness of this comprehensive and highly automated procedure for NLCD 2019 operational mapping. Questions about the NLCD 2019 land cover product can be directed to the NLCD 2019 land cover mapping team at USGS EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov. See included spatial metadata for more details.
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| U S Geological Survey |
| 2021 |
The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released five National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, 2011, and 2016. The 2016 release saw landcover created for additional years of 2003, 2008, and 2013. These products provide spatially explicit and reliable information on the Nation’s land cover and land cover change. To continue the legacy of NLCD and further establish a long-term monitoring capability for the Nation’s land resources, the USGS has designed a new generation of NLCD products named NLCD 2019. The NLCD 2019 design aims to provide innovative, consistent, and robust methodologies for production of a multi-temporal land cover and land cover change database from 2001 to 2019 at 2–3-year intervals. Comprehensive research was conducted and resulted in developed strategies for NLCD 2019: continued integration between impervious surface and all landcover products with impervious surface being directly mapped as developed classes in the landcover, a streamlined compositing process for assembling and preprocessing based on Landsat imagery and geospatial ancillary datasets; a multi-source integrated training data development and decision-tree based land cover classifications; a temporally, spectrally, and spatially integrated land cover change analysis strategy; a hierarchical theme-based post-classification and integration protocol for generating land cover and change products; a continuous fields biophysical parameters modeling method; and an automated scripted operational system for the NLCD 2019 production. The performance of the developed strategies and methods were tested in twenty composite referenced areas throughout the conterminous U.S. An overall accuracy assessment from the 2016 publication give a 91% overall landcover accuracy, with the developed classes also showing a 91% accuracy in overall developed. Results from this study confirm the robustness of this comprehensive and highly automated procedure for NLCD 2019 operational mapping. Questions about the NLCD 2019 land cover product can be directed to the NLCD 2019 land cover mapping team at USGS EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov. See included spatial metadata for more details.
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| U S Geological Survey |
| 2021 |
The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released five National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, 2011, and 2016. The 2016 release saw landcover created for additional years of 2003, 2008, and 2013. These products provide spatially explicit and reliable information on the Nation’s land cover and land cover change. To continue the legacy of NLCD and further establish a long-term monitoring capability for the Nation’s land resources, the USGS has designed a new generation of NLCD products named NLCD 2019. The NLCD 2019 design aims to provide innovative, consistent, and robust methodologies for production of a multi-temporal land cover and land cover change database from 2001 to 2019 at 2–3-year intervals. Comprehensive research was conducted and resulted in developed strategies for NLCD 2019: continued integration between impervious surface and all landcover products with impervious surface being directly mapped as developed classes in the landcover, a streamlined compositing process for assembling and preprocessing based on Landsat imagery and geospatial ancillary datasets; a multi-source integrated training data development and decision-tree based land cover classifications; a temporally, spectrally, and spatially integrated land cover change analysis strategy; a hierarchical theme-based post-classification and integration protocol for generating land cover and change products; a continuous fields biophysical parameters modeling method; and an automated scripted operational system for the NLCD 2019 production. The performance of the developed strategies and methods were tested in twenty composite referenced areas throughout the conterminous U.S. An overall accuracy assessment from the 2016 publication give a 91% overall landcover accuracy, with the developed classes also showing a 91% accuracy in overall developed. Results from this study confirm the robustness of this comprehensive and highly automated procedure for NLCD 2019 operational mapping. Questions about the NLCD 2019 land cover product can be directed to the NLCD 2019 land cover mapping team at USGS EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov. See included spatial metadata for more details.
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| U S Geological Survey |
| 2021 |
The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released five National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, 2011, and 2016. The 2016 release saw landcover created for additional years of 2003, 2008, and 2013. These products provide spatially explicit and reliable information on the Nation’s land cover and land cover change. To continue the legacy of NLCD and further establish a long-term monitoring capability for the Nation’s land resources, the USGS has designed a new generation of NLCD products named NLCD 2019. The NLCD 2019 design aims to provide innovative, consistent, and robust methodologies for production of a multi-temporal land cover and land cover change database from 2001 to 2019 at 2–3-year intervals. Comprehensive research was conducted and resulted in developed strategies for NLCD 2019: continued integration between impervious surface and all landcover products with impervious surface being directly mapped as developed classes in the landcover, a streamlined compositing process for assembling and preprocessing based on Landsat imagery and geospatial ancillary datasets; a multi-source integrated training data development and decision-tree based land cover classifications; a temporally, spectrally, and spatially integrated land cover change analysis strategy; a hierarchical theme-based post-classification and integration protocol for generating land cover and change products; a continuous fields biophysical parameters modeling method; and an automated scripted operational system for the NLCD 2019 production. The performance of the developed strategies and methods were tested in twenty composite referenced areas throughout the conterminous U.S. An overall accuracy assessment from the 2016 publication give a 91% overall landcover accuracy, with the developed classes also showing a 91% accuracy in overall developed. Results from this study confirm the robustness of this comprehensive and highly automated procedure for NLCD 2019 operational mapping. Questions about the NLCD 2019 land cover product can be directed to the NLCD 2019 land cover mapping team at USGS EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov. See included spatial metadata for more details.
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| U S Geological Survey |
| 2021 |
The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released five National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, 2011, and 2016. The 2016 release saw landcover created for additional years of 2003, 2008, and 2013. These products provide spatially explicit and reliable information on the Nation’s land cover and land cover change. To continue the legacy of NLCD and further establish a long-term monitoring capability for the Nation’s land resources, the USGS has designed a new generation of NLCD products named NLCD 2019. The NLCD 2019 design aims to provide innovative, consistent, and robust methodologies for production of a multi-temporal land cover and land cover change database from 2001 to 2019 at 2–3-year intervals. Comprehensive research was conducted and resulted in developed strategies for NLCD 2019: continued integration between impervious surface and all landcover products with impervious surface being directly mapped as developed classes in the landcover, a streamlined compositing process for assembling and preprocessing based on Landsat imagery and geospatial ancillary datasets; a multi-source integrated training data development and decision-tree based land cover classifications; a temporally, spectrally, and spatially integrated land cover change analysis strategy; a hierarchical theme-based post-classification and integration protocol for generating land cover and change products; a continuous fields biophysical parameters modeling method; and an automated scripted operational system for the NLCD 2019 production. The performance of the developed strategies and methods were tested in twenty composite referenced areas throughout the conterminous U.S. An overall accuracy assessment from the 2016 publication give a 91% overall landcover accuracy, with the developed classes also showing a 91% accuracy in overall developed. Results from this study confirm the robustness of this comprehensive and highly automated procedure for NLCD 2019 operational mapping. Questions about the NLCD 2019 land cover product can be directed to the NLCD 2019 land cover mapping team at USGS EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov. See included spatial metadata for more details.
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| U S Geological Survey |
| 2021 |
The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released five National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, 2011, and 2016. The 2016 release saw landcover created for additional years of 2003, 2008, and 2013. These products provide spatially explicit and reliable information on the Nation’s land cover and land cover change. To continue the legacy of NLCD and further establish a long-term monitoring capability for the Nation’s land resources, the USGS has designed a new generation of NLCD products named NLCD 2019. The NLCD 2019 design aims to provide innovative, consistent, and robust methodologies for production of a multi-temporal land cover and land cover change database from 2001 to 2019 at 2–3-year intervals. Comprehensive research was conducted and resulted in developed strategies for NLCD 2019: continued integration between impervious surface and all landcover products with impervious surface being directly mapped as developed classes in the landcover, a streamlined compositing process for assembling and preprocessing based on Landsat imagery and geospatial ancillary datasets; a multi-source integrated training data development and decision-tree based land cover classifications; a temporally, spectrally, and spatially integrated land cover change analysis strategy; a hierarchical theme-based post-classification and integration protocol for generating land cover and change products; a continuous fields biophysical parameters modeling method; and an automated scripted operational system for the NLCD 2019 production. The performance of the developed strategies and methods were tested in twenty composite referenced areas throughout the conterminous U.S. An overall accuracy assessment from the 2016 publication give a 91% overall landcover accuracy, with the developed classes also showing a 91% accuracy in overall developed. Results from this study confirm the robustness of this comprehensive and highly automated procedure for NLCD 2019 operational mapping. Questions about the NLCD 2019 land cover product can be directed to the NLCD 2019 land cover mapping team at USGS EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov. See included spatial metadata for more details.
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| U S Geological Survey |
| 2021 |
The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released five National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, 2011, and 2016. The 2016 release saw landcover created for additional years of 2003, 2008, and 2013. These products provide spatially explicit and reliable information on the Nation’s land cover and land cover change. To continue the legacy of NLCD and further establish a long-term monitoring capability for the Nation’s land resources, the USGS has designed a new generation of NLCD products named NLCD 2019. The NLCD 2019 design aims to provide innovative, consistent, and robust methodologies for production of a multi-temporal land cover and land cover change database from 2001 to 2019 at 2–3-year intervals. Comprehensive research was conducted and resulted in developed strategies for NLCD 2019: continued integration between impervious surface and all landcover products with impervious surface being directly mapped as developed classes in the landcover, a streamlined compositing process for assembling and preprocessing based on Landsat imagery and geospatial ancillary datasets; a multi-source integrated training data development and decision-tree based land cover classifications; a temporally, spectrally, and spatially integrated land cover change analysis strategy; a hierarchical theme-based post-classification and integration protocol for generating land cover and change products; a continuous fields biophysical parameters modeling method; and an automated scripted operational system for the NLCD 2019 production. The performance of the developed strategies and methods were tested in twenty composite referenced areas throughout the conterminous U.S. An overall accuracy assessment from the 2016 publication give a 91% overall landcover accuracy, with the developed classes also showing a 91% accuracy in overall developed. Results from this study confirm the robustness of this comprehensive and highly automated procedure for NLCD 2019 operational mapping. Questions about the NLCD 2019 land cover product can be directed to the NLCD 2019 land cover mapping team at USGS EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov. See included spatial metadata for more details.
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| U S Geological Survey |
| 2021 |
The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released five National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, 2011, and 2016. The 2016 release saw landcover created for additional years of 2003, 2008, and 2013. These products provide spatially explicit and reliable information on the Nation’s land cover and land cover change. To continue the legacy of NLCD and further establish a long-term monitoring capability for the Nation’s land resources, the USGS has designed a new generation of NLCD products named NLCD 2019. The NLCD 2019 design aims to provide innovative, consistent, and robust methodologies for production of a multi-temporal land cover and land cover change database from 2001 to 2019 at 2–3-year intervals. Comprehensive research was conducted and resulted in developed strategies for NLCD 2019: continued integration between impervious surface and all landcover products with impervious surface being directly mapped as developed classes in the landcover, a streamlined compositing process for assembling and preprocessing based on Landsat imagery and geospatial ancillary datasets; a multi-source integrated training data development and decision-tree based land cover classifications; a temporally, spectrally, and spatially integrated land cover change analysis strategy; a hierarchical theme-based post-classification and integration protocol for generating land cover and change products; a continuous fields biophysical parameters modeling method; and an automated scripted operational system for the NLCD 2019 production. The performance of the developed strategies and methods were tested in twenty composite referenced areas throughout the conterminous U.S. An overall accuracy assessment from the 2016 publication give a 91% overall landcover accuracy, with the developed classes also showing a 91% accuracy in overall developed. Results from this study confirm the robustness of this comprehensive and highly automated procedure for NLCD 2019 operational mapping. Questions about the NLCD 2019 land cover product can be directed to the NLCD 2019 land cover mapping team at USGS EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov. See included spatial metadata for more details.
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| U S Geological Survey |
| 2021 |
The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released five National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, 2011, and 2016. The 2016 release saw landcover created for additional years of 2003, 2008, and 2013. These products provide spatially explicit and reliable information on the Nation’s land cover and land cover change. To continue the legacy of NLCD and further establish a long-term monitoring capability for the Nation’s land resources, the USGS has designed a new generation of NLCD products named NLCD 2019. The NLCD 2019 design aims to provide innovative, consistent, and robust methodologies for production of a multi-temporal land cover and land cover change database from 2001 to 2019 at 2–3-year intervals. Comprehensive research was conducted and resulted in developed strategies for NLCD 2019: continued integration between impervious surface and all landcover products with impervious surface being directly mapped as developed classes in the landcover, a streamlined compositing process for assembling and preprocessing based on Landsat imagery and geospatial ancillary datasets; a multi-source integrated training data development and decision-tree based land cover classifications; a temporally, spectrally, and spatially integrated land cover change analysis strategy; a hierarchical theme-based post-classification and integration protocol for generating land cover and change products; a continuous fields biophysical parameters modeling method; and an automated scripted operational system for the NLCD 2019 production. The performance of the developed strategies and methods were tested in twenty composite referenced areas throughout the conterminous U.S. An overall accuracy assessment from the 2016 publication give a 91% overall landcover accuracy, with the developed classes also showing a 91% accuracy in overall developed. Results from this study confirm the robustness of this comprehensive and highly automated procedure for NLCD 2019 operational mapping. Questions about the NLCD 2019 land cover product can be directed to the NLCD 2019 land cover mapping team at USGS EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov. See included spatial metadata for more details.
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| U S Geological Survey |
| 2021 |
The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released five National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, 2011, and 2016. The 2016 release saw landcover created for additional years of 2003, 2008, and 2013. These products provide spatially explicit and reliable information on the Nation’s land cover and land cover change. To continue the legacy of NLCD and further establish a long-term monitoring capability for the Nation’s land resources, the USGS has designed a new generation of NLCD products named NLCD 2019. The NLCD 2019 design aims to provide innovative, consistent, and robust methodologies for production of a multi-temporal land cover and land cover change database from 2001 to 2019 at 2–3-year intervals. Comprehensive research was conducted and resulted in developed strategies for NLCD 2019: continued integration between impervious surface and all landcover products with impervious surface being directly mapped as developed classes in the landcover, a streamlined compositing process for assembling and preprocessing based on Landsat imagery and geospatial ancillary datasets; a multi-source integrated training data development and decision-tree based land cover classifications; a temporally, spectrally, and spatially integrated land cover change analysis strategy; a hierarchical theme-based post-classification and integration protocol for generating land cover and change products; a continuous fields biophysical parameters modeling method; and an automated scripted operational system for the NLCD 2019 production. The performance of the developed strategies and methods were tested in twenty composite referenced areas throughout the conterminous U.S. An overall accuracy assessment from the 2016 publication give a 91% overall landcover accuracy, with the developed classes also showing a 91% accuracy in overall developed. Results from this study confirm the robustness of this comprehensive and highly automated procedure for NLCD 2019 operational mapping. Questions about the NLCD 2019 land cover product can be directed to the NLCD 2019 land cover mapping team at USGS EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov. See included spatial metadata for more details.
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| U S Geological Survey |
| 2021 |
The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released five National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, 2011, and 2016. The 2016 release saw landcover created for additional years of 2003, 2008, and 2013. These products provide spatially explicit and reliable information on the Nation’s land cover and land cover change. To continue the legacy of NLCD and further establish a long-term monitoring capability for the Nation’s land resources, the USGS has designed a new generation of NLCD products named NLCD 2019. The NLCD 2019 design aims to provide innovative, consistent, and robust methodologies for production of a multi-temporal land cover and land cover change database from 2001 to 2019 at 2–3-year intervals. Comprehensive research was conducted and resulted in developed strategies for NLCD 2019: continued integration between impervious surface and all landcover products with impervious surface being directly mapped as developed classes in the landcover, a streamlined compositing process for assembling and preprocessing based on Landsat imagery and geospatial ancillary datasets; a multi-source integrated training data development and decision-tree based land cover classifications; a temporally, spectrally, and spatially integrated land cover change analysis strategy; a hierarchical theme-based post-classification and integration protocol for generating land cover and change products; a continuous fields biophysical parameters modeling method; and an automated scripted operational system for the NLCD 2019 production. The performance of the developed strategies and methods were tested in twenty composite referenced areas throughout the conterminous U.S. An overall accuracy assessment from the 2016 publication give a 91% overall landcover accuracy, with the developed classes also showing a 91% accuracy in overall developed. Results from this study confirm the robustness of this comprehensive and highly automated procedure for NLCD 2019 operational mapping. Questions about the NLCD 2019 land cover product can be directed to the NLCD 2019 land cover mapping team at USGS EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov. See included spatial metadata for more details.
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| U S Geological Survey |
| 2021 |
The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released five National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, 2011, and 2016. The 2016 release saw landcover created for additional years of 2003, 2008, and 2013. These products provide spatially explicit and reliable information on the Nation’s land cover and land cover change. To continue the legacy of NLCD and further establish a long-term monitoring capability for the Nation’s land resources, the USGS has designed a new generation of NLCD products named NLCD 2019. The NLCD 2019 design aims to provide innovative, consistent, and robust methodologies for production of a multi-temporal land cover and land cover change database from 2001 to 2019 at 2–3-year intervals. Comprehensive research was conducted and resulted in developed strategies for NLCD 2019: continued integration between impervious surface and all landcover products with impervious surface being directly mapped as developed classes in the landcover, a streamlined compositing process for assembling and preprocessing based on Landsat imagery and geospatial ancillary datasets; a multi-source integrated training data development and decision-tree based land cover classifications; a temporally, spectrally, and spatially integrated land cover change analysis strategy; a hierarchical theme-based post-classification and integration protocol for generating land cover and change products; a continuous fields biophysical parameters modeling method; and an automated scripted operational system for the NLCD 2019 production. The performance of the developed strategies and methods were tested in twenty composite referenced areas throughout the conterminous U.S. An overall accuracy assessment from the 2016 publication give a 91% overall landcover accuracy, with the developed classes also showing a 91% accuracy in overall developed. Results from this study confirm the robustness of this comprehensive and highly automated procedure for NLCD 2019 operational mapping. Questions about the NLCD 2019 land cover product can be directed to the NLCD 2019 land cover mapping team at USGS EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov. See included spatial metadata for more details.
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| U S Geological Survey |
| 2021 |
The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released five National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, 2011, and 2016. The 2016 release saw landcover created for additional years of 2003, 2008, and 2013. These products provide spatially explicit and reliable information on the Nation’s land cover and land cover change. To continue the legacy of NLCD and further establish a long-term monitoring capability for the Nation’s land resources, the USGS has designed a new generation of NLCD products named NLCD 2019. The NLCD 2019 design aims to provide innovative, consistent, and robust methodologies for production of a multi-temporal land cover and land cover change database from 2001 to 2019 at 2–3-year intervals. Comprehensive research was conducted and resulted in developed strategies for NLCD 2019: continued integration between impervious surface and all landcover products with impervious surface being directly mapped as developed classes in the landcover, a streamlined compositing process for assembling and preprocessing based on Landsat imagery and geospatial ancillary datasets; a multi-source integrated training data development and decision-tree based land cover classifications; a temporally, spectrally, and spatially integrated land cover change analysis strategy; a hierarchical theme-based post-classification and integration protocol for generating land cover and change products; a continuous fields biophysical parameters modeling method; and an automated scripted operational system for the NLCD 2019 production. The performance of the developed strategies and methods were tested in twenty composite referenced areas throughout the conterminous U.S. An overall accuracy assessment from the 2016 publication give a 91% overall landcover accuracy, with the developed classes also showing a 91% accuracy in overall developed. Results from this study confirm the robustness of this comprehensive and highly automated procedure for NLCD 2019 operational mapping. Questions about the NLCD 2019 land cover product can be directed to the NLCD 2019 land cover mapping team at USGS EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov. See included spatial metadata for more details.
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| U S Geological Survey |
| 2021 |
The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released five National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, 2011, and 2016. The 2016 release saw landcover created for additional years of 2003, 2008, and 2013. These products provide spatially explicit and reliable information on the Nation’s land cover and land cover change. To continue the legacy of NLCD and further establish a long-term monitoring capability for the Nation’s land resources, the USGS has designed a new generation of NLCD products named NLCD 2019. The NLCD 2019 design aims to provide innovative, consistent, and robust methodologies for production of a multi-temporal land cover and land cover change database from 2001 to 2019 at 2–3-year intervals. Comprehensive research was conducted and resulted in developed strategies for NLCD 2019: continued integration between impervious surface and all landcover products with impervious surface being directly mapped as developed classes in the landcover, a streamlined compositing process for assembling and preprocessing based on Landsat imagery and geospatial ancillary datasets; a multi-source integrated training data development and decision-tree based land cover classifications; a temporally, spectrally, and spatially integrated land cover change analysis strategy; a hierarchical theme-based post-classification and integration protocol for generating land cover and change products; a continuous fields biophysical parameters modeling method; and an automated scripted operational system for the NLCD 2019 production. The performance of the developed strategies and methods were tested in twenty composite referenced areas throughout the conterminous U.S. An overall accuracy assessment from the 2016 publication give a 91% overall landcover accuracy, with the developed classes also showing a 91% accuracy in overall developed. Results from this study confirm the robustness of this comprehensive and highly automated procedure for NLCD 2019 operational mapping. Questions about the NLCD 2019 land cover product can be directed to the NLCD 2019 land cover mapping team at USGS EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov. See included spatial metadata for more details.
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| U S Geological Survey |
| 2021 |
The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released five National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, 2011, and 2016. The 2016 release saw landcover created for additional years of 2003, 2008, and 2013. These products provide spatially explicit and reliable information on the Nation’s land cover and land cover change. To continue the legacy of NLCD and further establish a long-term monitoring capability for the Nation’s land resources, the USGS has designed a new generation of NLCD products named NLCD 2019. The NLCD 2019 design aims to provide innovative, consistent, and robust methodologies for production of a multi-temporal land cover and land cover change database from 2001 to 2019 at 2–3-year intervals. Comprehensive research was conducted and resulted in developed strategies for NLCD 2019: continued integration between impervious surface and all landcover products with impervious surface being directly mapped as developed classes in the landcover, a streamlined compositing process for assembling and preprocessing based on Landsat imagery and geospatial ancillary datasets; a multi-source integrated training data development and decision-tree based land cover classifications; a temporally, spectrally, and spatially integrated land cover change analysis strategy; a hierarchical theme-based post-classification and integration protocol for generating land cover and change products; a continuous fields biophysical parameters modeling method; and an automated scripted operational system for the NLCD 2019 production. The performance of the developed strategies and methods were tested in twenty composite referenced areas throughout the conterminous U.S. An overall accuracy assessment from the 2016 publication give a 91% overall landcover accuracy, with the developed classes also showing a 91% accuracy in overall developed. Results from this study confirm the robustness of this comprehensive and highly automated procedure for NLCD 2019 operational mapping. Questions about the NLCD 2019 land cover product can be directed to the NLCD 2019 land cover mapping team at USGS EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov. See included spatial metadata for more details.
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| U S Geological Survey |
| 2021 |
The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released five National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, 2011, and 2016. The 2016 release saw landcover created for additional years of 2003, 2008, and 2013. These products provide spatially explicit and reliable information on the Nation’s land cover and land cover change. To continue the legacy of NLCD and further establish a long-term monitoring capability for the Nation’s land resources, the USGS has designed a new generation of NLCD products named NLCD 2019. The NLCD 2019 design aims to provide innovative, consistent, and robust methodologies for production of a multi-temporal land cover and land cover change database from 2001 to 2019 at 2–3-year intervals. Comprehensive research was conducted and resulted in developed strategies for NLCD 2019: continued integration between impervious surface and all landcover products with impervious surface being directly mapped as developed classes in the landcover, a streamlined compositing process for assembling and preprocessing based on Landsat imagery and geospatial ancillary datasets; a multi-source integrated training data development and decision-tree based land cover classifications; a temporally, spectrally, and spatially integrated land cover change analysis strategy; a hierarchical theme-based post-classification and integration protocol for generating land cover and change products; a continuous fields biophysical parameters modeling method; and an automated scripted operational system for the NLCD 2019 production. The performance of the developed strategies and methods were tested in twenty composite referenced areas throughout the conterminous U.S. An overall accuracy assessment from the 2016 publication give a 91% overall landcover accuracy, with the developed classes also showing a 91% accuracy in overall developed. Results from this study confirm the robustness of this comprehensive and highly automated procedure for NLCD 2019 operational mapping. Questions about the NLCD 2019 land cover product can be directed to the NLCD 2019 land cover mapping team at USGS EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov. See included spatial metadata for more details.
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| U S Geological Survey |
| 2021 |
The USDA Forest Service (USFS) builds two versions of percent tree canopy cover data, in order to serve needs of multiple user communities. These datasets encompass conterminous United States (CONUS), Coastal Alaska, Hawaii, and Puerto Rico and U.S. Virgin Islands (PRUSVI). The two versions of data within the v2021-4 TCC product suite include: The initial model outputs referred to as the Science data; And a modified version built for the National Land Cover Database and referred to as NLCD data. The NLCD product suite includes data for years 2011, 2013, 2016, 2019 and 2021. The NCLD data are processed to remove small interannual changes from the annual TCC timeseries, and to mask TCC pixels that are known to be 0 percent TCC, non-tree agriculture, and water. A small interannual change is defined as a TCC change less than an increase or decrease of 10 percent compared to a TCC baseline value established in a prior year. The initial TCC baseline value is the mean of 2008-2010 TCC data. For each year following 2011, on a pixel-wise basis TCC values are updated to a new baseline value if an increase or decrease of 10 percent TCC occurs relative to the 2008-2010 TCC baseline value. If no increase or decrease greater than 10 percent TCC occurs relative to the 2008-2010 baseline, then the 2008-2010 TCC baseline value is caried through to the next year in the timeseries. Pixel values range from 0 to 100 percent. The non-processing area is represented by value 254, and the background is represented by the value 255. The Science and NLCD tree canopy cover data are accessible for multiple user communities, through multiple channels and platforms. For information on the Science data and processing steps see the Science metadata. Information on the NLCD data and processing steps are included here.
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| U S Geological Survey |
| 2021 |
The USDA Forest Service (USFS) builds two versions of percent tree canopy cover data, in order to serve needs of multiple user communities. These datasets encompass conterminous United States (CONUS), Coastal Alaska, Hawaii, and Puerto Rico and U.S. Virgin Islands (PRUSVI). The two versions of data within the v2021-4 TCC product suite include: The initial model outputs referred to as the Science data; And a modified version built for the National Land Cover Database and referred to as NLCD data. The NLCD product suite includes data for years 2011, 2013, 2016, 2019 and 2021. The NCLD data are processed to remove small interannual changes from the annual TCC timeseries, and to mask TCC pixels that are known to be 0 percent TCC, non-tree agriculture, and water. A small interannual change is defined as a TCC change less than an increase or decrease of 10 percent compared to a TCC baseline value established in a prior year. The initial TCC baseline value is the mean of 2008-2010 TCC data. For each year following 2011, on a pixel-wise basis TCC values are updated to a new baseline value if an increase or decrease of 10 percent TCC occurs relative to the 2008-2010 TCC baseline value. If no increase or decrease greater than 10 percent TCC occurs relative to the 2008-2010 baseline, then the 2008-2010 TCC baseline value is caried through to the next year in the timeseries. Pixel values range from 0 to 100 percent. The non-processing area is represented by value 254, and the background is represented by the value 255. The Science and NLCD tree canopy cover data are accessible for multiple user communities, through multiple channels and platforms. For information on the Science data and processing steps see the Science metadata. Information on the NLCD data and processing steps are included here.
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| U S Geological Survey |
| 2021 |
The USDA Forest Service (USFS) builds two versions of percent tree canopy cover data, in order to serve needs of multiple user communities. These datasets encompass conterminous United States (CONUS), Coastal Alaska, Hawaii, and Puerto Rico and U.S. Virgin Islands (PRUSVI). The two versions of data within the v2021-4 TCC product suite include: The initial model outputs referred to as the Science data; And a modified version built for the National Land Cover Database and referred to as NLCD data. The NLCD product suite includes data for years 2011, 2013, 2016, 2019 and 2021. The NCLD data are processed to remove small interannual changes from the annual TCC timeseries, and to mask TCC pixels that are known to be 0 percent TCC, non-tree agriculture, and water. A small interannual change is defined as a TCC change less than an increase or decrease of 10 percent compared to a TCC baseline value established in a prior year. The initial TCC baseline value is the mean of 2008-2010 TCC data. For each year following 2011, on a pixel-wise basis TCC values are updated to a new baseline value if an increase or decrease of 10 percent TCC occurs relative to the 2008-2010 TCC baseline value. If no increase or decrease greater than 10 percent TCC occurs relative to the 2008-2010 baseline, then the 2008-2010 TCC baseline value is caried through to the next year in the timeseries. Pixel values range from 0 to 100 percent. The non-processing area is represented by value 254, and the background is represented by the value 255. The Science and NLCD tree canopy cover data are accessible for multiple user communities, through multiple channels and platforms. For information on the Science data and processing steps see the Science metadata. Information on the NLCD data and processing steps are included here.
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| U S Geological Survey |
| 2021 |
The USDA Forest Service (USFS) builds two versions of percent tree canopy cover data, in order to serve needs of multiple user communities. These datasets encompass conterminous United States (CONUS), Coastal Alaska, Hawaii, and Puerto Rico and U.S. Virgin Islands (PRUSVI). The two versions of data within the v2021-4 TCC product suite include: The initial model outputs referred to as the Science data; And a modified version built for the National Land Cover Database and referred to as NLCD data. The NLCD product suite includes data for years 2011, 2013, 2016, 2019 and 2021. The NCLD data are processed to remove small interannual changes from the annual TCC timeseries, and to mask TCC pixels that are known to be 0 percent TCC, non-tree agriculture, and water. A small interannual change is defined as a TCC change less than an increase or decrease of 10 percent compared to a TCC baseline value established in a prior year. The initial TCC baseline value is the mean of 2008-2010 TCC data. For each year following 2011, on a pixel-wise basis TCC values are updated to a new baseline value if an increase or decrease of 10 percent TCC occurs relative to the 2008-2010 TCC baseline value. If no increase or decrease greater than 10 percent TCC occurs relative to the 2008-2010 baseline, then the 2008-2010 TCC baseline value is caried through to the next year in the timeseries. Pixel values range from 0 to 100 percent. The non-processing area is represented by value 254, and the background is represented by the value 255. The Science and NLCD tree canopy cover data are accessible for multiple user communities, through multiple channels and platforms. For information on the Science data and processing steps see the Science metadata. Information on the NLCD data and processing steps are included here.
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| U S Geological Survey |
| 2021 |
The USDA Forest Service (USFS) builds two versions of percent tree canopy cover data, in order to serve needs of multiple user communities. These datasets encompass conterminous United States (CONUS), Coastal Alaska, Hawaii, and Puerto Rico and U.S. Virgin Islands (PRUSVI). The two versions of data within the v2021-4 TCC product suite include: The initial model outputs referred to as the Science data; And a modified version built for the National Land Cover Database and referred to as NLCD data. The NLCD product suite includes data for years 2011, 2013, 2016, 2019 and 2021. The NCLD data are processed to remove small interannual changes from the annual TCC timeseries, and to mask TCC pixels that are known to be 0 percent TCC, non-tree agriculture, and water. A small interannual change is defined as a TCC change less than an increase or decrease of 10 percent compared to a TCC baseline value established in a prior year. The initial TCC baseline value is the mean of 2008-2010 TCC data. For each year following 2011, on a pixel-wise basis TCC values are updated to a new baseline value if an increase or decrease of 10 percent TCC occurs relative to the 2008-2010 TCC baseline value. If no increase or decrease greater than 10 percent TCC occurs relative to the 2008-2010 baseline, then the 2008-2010 TCC baseline value is caried through to the next year in the timeseries. Pixel values range from 0 to 100 percent. The non-processing area is represented by value 254, and the background is represented by the value 255. The Science and NLCD tree canopy cover data are accessible for multiple user communities, through multiple channels and platforms. For information on the Science data and processing steps see the Science metadata. Information on the NLCD data and processing steps are included here.
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| U S Geological Survey |
| 2021 |
The USDA Forest Service (USFS) builds two versions of percent tree canopy cover data, in order to serve needs of multiple user communities. These datasets encompass conterminous United States (CONUS), Coastal Alaska, Hawaii, and Puerto Rico and U.S. Virgin Islands (PRUSVI). The two versions of data within the v2021-4 TCC product suite include: The initial model outputs referred to as the Science data; And a modified version built for the National Land Cover Database and referred to as NLCD data. The NLCD product suite includes data for years 2011, 2013, 2016, 2019 and 2021. The NCLD data are processed to remove small interannual changes from the annual TCC timeseries, and to mask TCC pixels that are known to be 0 percent TCC, non-tree agriculture, and water. A small interannual change is defined as a TCC change less than an increase or decrease of 10 percent compared to a TCC baseline value established in a prior year. The initial TCC baseline value is the mean of 2008-2010 TCC data. For each year following 2011, on a pixel-wise basis TCC values are updated to a new baseline value if an increase or decrease of 10 percent TCC occurs relative to the 2008-2010 TCC baseline value. If no increase or decrease greater than 10 percent TCC occurs relative to the 2008-2010 baseline, then the 2008-2010 TCC baseline value is caried through to the next year in the timeseries. Pixel values range from 0 to 100 percent. The non-processing area is represented by value 254, and the background is represented by the value 255. The Science and NLCD tree canopy cover data are accessible for multiple user communities, through multiple channels and platforms. For information on the Science data and processing steps see the Science metadata. Information on the NLCD data and processing steps are included here.
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| U S Geological Survey |
| 2021 |
The USDA Forest Service (USFS) builds two versions of percent tree canopy cover data, in order to serve needs of multiple user communities. These datasets encompass conterminous United States (CONUS), Coastal Alaska, Hawaii, and Puerto Rico and U.S. Virgin Islands (PRUSVI). The two versions of data within the v2021-4 TCC product suite include: The initial model outputs referred to as the Science data; And a modified version built for the National Land Cover Database and referred to as NLCD data. The NLCD product suite includes data for years 2011, 2013, 2016, 2019 and 2021. The NCLD data are processed to remove small interannual changes from the annual TCC timeseries, and to mask TCC pixels that are known to be 0 percent TCC, non-tree agriculture, and water. A small interannual change is defined as a TCC change less than an increase or decrease of 10 percent compared to a TCC baseline value established in a prior year. The initial TCC baseline value is the mean of 2008-2010 TCC data. For each year following 2011, on a pixel-wise basis TCC values are updated to a new baseline value if an increase or decrease of 10 percent TCC occurs relative to the 2008-2010 TCC baseline value. If no increase or decrease greater than 10 percent TCC occurs relative to the 2008-2010 baseline, then the 2008-2010 TCC baseline value is caried through to the next year in the timeseries. Pixel values range from 0 to 100 percent. The non-processing area is represented by value 254, and the background is represented by the value 255. The Science and NLCD tree canopy cover data are accessible for multiple user communities, through multiple channels and platforms. For information on the Science data and processing steps see the Science metadata. Information on the NLCD data and processing steps are included here.
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| U S Geological Survey |
| 2021 |
The USDA Forest Service (USFS) builds two versions of percent tree canopy cover data, in order to serve needs of multiple user communities. These datasets encompass conterminous United States (CONUS), Coastal Alaska, Hawaii, and Puerto Rico and U.S. Virgin Islands (PRUSVI). The two versions of data within the v2021-4 TCC product suite include: The initial model outputs referred to as the Science data; And a modified version built for the National Land Cover Database and referred to as NLCD data. The NLCD product suite includes data for years 2011, 2013, 2016, 2019 and 2021. The NCLD data are processed to remove small interannual changes from the annual TCC timeseries, and to mask TCC pixels that are known to be 0 percent TCC, non-tree agriculture, and water. A small interannual change is defined as a TCC change less than an increase or decrease of 10 percent compared to a TCC baseline value established in a prior year. The initial TCC baseline value is the mean of 2008-2010 TCC data. For each year following 2011, on a pixel-wise basis TCC values are updated to a new baseline value if an increase or decrease of 10 percent TCC occurs relative to the 2008-2010 TCC baseline value. If no increase or decrease greater than 10 percent TCC occurs relative to the 2008-2010 baseline, then the 2008-2010 TCC baseline value is caried through to the next year in the timeseries. Pixel values range from 0 to 100 percent. The non-processing area is represented by value 254, and the background is represented by the value 255. The Science and NLCD tree canopy cover data are accessible for multiple user communities, through multiple channels and platforms. For information on the Science data and processing steps see the Science metadata. Information on the NLCD data and processing steps are included here.
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| U S Geological Survey |
| 2021 |
The USDA Forest Service (USFS) builds two versions of percent tree canopy cover data, in order to serve needs of multiple user communities. These datasets encompass conterminous United States (CONUS), Coastal Alaska, Hawaii, and Puerto Rico and U.S. Virgin Islands (PRUSVI). The two versions of data within the v2021-4 TCC product suite include: The initial model outputs referred to as the Science data; And a modified version built for the National Land Cover Database and referred to as NLCD data. The NLCD product suite includes data for years 2011, 2013, 2016, 2019 and 2021. The NCLD data are processed to remove small interannual changes from the annual TCC timeseries, and to mask TCC pixels that are known to be 0 percent TCC, non-tree agriculture, and water. A small interannual change is defined as a TCC change less than an increase or decrease of 10 percent compared to a TCC baseline value established in a prior year. The initial TCC baseline value is the mean of 2008-2010 TCC data. For each year following 2011, on a pixel-wise basis TCC values are updated to a new baseline value if an increase or decrease of 10 percent TCC occurs relative to the 2008-2010 TCC baseline value. If no increase or decrease greater than 10 percent TCC occurs relative to the 2008-2010 baseline, then the 2008-2010 TCC baseline value is caried through to the next year in the timeseries. Pixel values range from 0 to 100 percent. The non-processing area is represented by value 254, and the background is represented by the value 255. The Science and NLCD tree canopy cover data are accessible for multiple user communities, through multiple channels and platforms. For information on the Science data and processing steps see the Science metadata. Information on the NLCD data and processing steps are included here.
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| U S Geological Survey |
| 2021 |
The USDA Forest Service (USFS) builds two versions of percent tree canopy cover data, in order to serve needs of multiple user communities. These datasets encompass conterminous United States (CONUS), Coastal Alaska, Hawaii, and Puerto Rico and U.S. Virgin Islands (PRUSVI). The two versions of data within the v2021-4 TCC product suite include: The initial model outputs referred to as the Science data; And a modified version built for the National Land Cover Database and referred to as NLCD data. The NLCD product suite includes data for years 2011, 2013, 2016, 2019 and 2021. The NCLD data are processed to remove small interannual changes from the annual TCC timeseries, and to mask TCC pixels that are known to be 0 percent TCC, non-tree agriculture, and water. A small interannual change is defined as a TCC change less than an increase or decrease of 10 percent compared to a TCC baseline value established in a prior year. The initial TCC baseline value is the mean of 2008-2010 TCC data. For each year following 2011, on a pixel-wise basis TCC values are updated to a new baseline value if an increase or decrease of 10 percent TCC occurs relative to the 2008-2010 TCC baseline value. If no increase or decrease greater than 10 percent TCC occurs relative to the 2008-2010 baseline, then the 2008-2010 TCC baseline value is caried through to the next year in the timeseries. Pixel values range from 0 to 100 percent. The non-processing area is represented by value 254, and the background is represented by the value 255. The Science and NLCD tree canopy cover data are accessible for multiple user communities, through multiple channels and platforms. For information on the Science data and processing steps see the Science metadata. Information on the NLCD data and processing steps are included here.
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| U S Geological Survey |
| 2021 |
The USDA Forest Service (USFS) builds two versions of percent tree canopy cover data, in order to serve needs of multiple user communities. These datasets encompass conterminous United States (CONUS), Coastal Alaska, Hawaii, and Puerto Rico and U.S. Virgin Islands (PRUSVI). The two versions of data within the v2021-4 TCC product suite include: The initial model outputs referred to as the Science data; And a modified version built for the National Land Cover Database and referred to as NLCD data. The NLCD product suite includes data for years 2011, 2013, 2016, 2019 and 2021. The NCLD data are processed to remove small interannual changes from the annual TCC timeseries, and to mask TCC pixels that are known to be 0 percent TCC, non-tree agriculture, and water. A small interannual change is defined as a TCC change less than an increase or decrease of 10 percent compared to a TCC baseline value established in a prior year. The initial TCC baseline value is the mean of 2008-2010 TCC data. For each year following 2011, on a pixel-wise basis TCC values are updated to a new baseline value if an increase or decrease of 10 percent TCC occurs relative to the 2008-2010 TCC baseline value. If no increase or decrease greater than 10 percent TCC occurs relative to the 2008-2010 baseline, then the 2008-2010 TCC baseline value is caried through to the next year in the timeseries. Pixel values range from 0 to 100 percent. The non-processing area is represented by value 254, and the background is represented by the value 255. The Science and NLCD tree canopy cover data are accessible for multiple user communities, through multiple channels and platforms. For information on the Science data and processing steps see the Science metadata. Information on the NLCD data and processing steps are included here.
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| U S Geological Survey |
| 2003 |
The National Land Cover Database 2001 for mapping zone 47 was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of federal agencies (www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (EPA), the U.S. Department of Agriculture (USDA), the U.S. Forest Service (USFS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (FWS), the Bureau of Land Management (BLM) and the USDA Natural Resources Conservation Service (NRCS). One of the primary goals of the project is to generate a current, consistent, seamless, and accurate National Land Cover Database (NLCD) circa 2001 for the United States at medium spatial resolution. For a detailed definition and discussion on MRLC and the NLCD 2001 products, refer to Homer et al. (2003) and http://www.mrlc.gov/mrlc2k.asp.
The NLCD 2001 was created by partitioning the U.S. into mapping zones. A total of 66 mapping zones were delineated within the conterminous U.S. based on ecoregion and geographical characteristics, edge matching features and the size requirement of Landsat mosaics. Mapping zone 47 encompasses whole or portions of several states including the states of Kentucky, Indiana, Ohio, Tennessee, and Missouri. Questions about the NLCD mapping zone 47 can be directed to the NLCD 2001 land cover mapping team at the National Center, EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov.
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| U S Geological Survey |
| 2003 |
The National Land Cover Database 2001 tree canopy layer for mapping zone 47 was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of federal agencies (www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (EPA), the U.S. Department of Agriculture (USDA), the U.S. Forest Service (USFS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (FWS), the Bureau of Land Management (BLM) and the USDA Natural Resources Conservation Service (NRCS). One of the primary goals of the project is to generate a current, consistent, seamless, and accurate National Land cover Database (NLCD) circa 2001 for the United States at medium spatial resolution. For a detailed definition and discussion on MRLC and the NLCD 2001 products, refer to Homer et al. (2003) and http://www.mrlc.gov/mrlc2k.asp.
The NLCD 2001 was created by partitioning the U.S. into mapping zones. A total of 66 mapping zones were delineated within the conterminous U.S. based on ecoregion and geographical characteristics, edge matching features and the size requirement of Landsat mosaics. Mapping zone 47 encompasses whole or portions of several states including the states of Kentucky, Indiana, Ohio, Tennessee, and Missouri. Questions about the NLCD mapping zone 47 can be directed to the NLCD 2001 land cover mapping team at the National Center, EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov.
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| U S Geological Survey |
| 2003 |
The National Land Cover Database 2001 tree canopy layer for mapping zone 47 was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of federal agencies (www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (EPA), the U.S. Department of Agriculture (USDA), the U.S. Forest Service (USFS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (FWS), the Bureau of Land Management (BLM) and the USDA Natural Resources Conservation Service (NRCS). One of the primary goals of the project is to generate a current, consistent, seamless, and accurate National Land cover Database (NLCD) circa 2001 for the United States at medium spatial resolution. For a detailed definition and discussion on MRLC and the NLCD 2001 products, refer to Homer et al. (2003) and http://www.mrlc.gov/mrlc2k.asp.
The NLCD 2001 was created by partitioning the U.S. into mapping zones. A total of 66 mapping zones were delineated within the conterminous U.S. based on ecoregion and geographical characteristics, edge matching features and the size requirement of Landsat mosaics. Mapping zone 47 encompasses whole or portions of several states including the states of Kentucky, Indiana, Ohio, Tennessee, and Missouri. Questions about the NLCD mapping zone 47 can be directed to the NLCD 2001 land cover mapping team at the National Center, EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov.
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| U S Geological Survey |
| 2003 |
The National Land Cover Database 2001 for mapping zone 47 was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of federal agencies (www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (EPA), the U.S. Department of Agriculture (USDA), the U.S. Forest Service (USFS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (FWS), the Bureau of Land Management (BLM) and the USDA Natural Resources Conservation Service (NRCS). One of the primary goals of the project is to generate a current, consistent, seamless, and accurate National Land Cover Database (NLCD) circa 2001 for the United States at medium spatial resolution. For a detailed definition and discussion on MRLC and the NLCD 2001 products, refer to Homer et al. (2003) and http://www.mrlc.gov/mrlc2k.asp.
The NLCD 2001 was created by partitioning the U.S. into mapping zones. A total of 66 mapping zones were delineated within the conterminous U.S. based on ecoregion and geographical characteristics, edge matching features and the size requirement of Landsat mosaics. Mapping zone 47 encompasses whole or portions of several states including the states of Kentucky, Indiana, Ohio, Tennessee, and Missouri. Questions about the NLCD mapping zone 47 can be directed to the NLCD 2001 land cover mapping team at the National Center, EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov.
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| U S Geological Survey |
| 2003 |
The National Land Cover Database 2001 tree canopy layer for mapping zone 47 was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of federal agencies (www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (EPA), the U.S. Department of Agriculture (USDA), the U.S. Forest Service (USFS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (FWS), the Bureau of Land Management (BLM) and the USDA Natural Resources Conservation Service (NRCS). One of the primary goals of the project is to generate a current, consistent, seamless, and accurate National Land cover Database (NLCD) circa 2001 for the United States at medium spatial resolution. For a detailed definition and discussion on MRLC and the NLCD 2001 products, refer to Homer et al. (2003) and http://www.mrlc.gov/mrlc2k.asp.
The NLCD 2001 was created by partitioning the U.S. into mapping zones. A total of 66 mapping zones were delineated within the conterminous U.S. based on ecoregion and geographical characteristics, edge matching features and the size requirement of Landsat mosaics. Mapping zone 47 encompasses whole or portions of several states including the states of Kentucky, Indiana, Ohio, Tennessee, and Missouri. Questions about the NLCD mapping zone 47 can be directed to the NLCD 2001 land cover mapping team at the National Center, EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov.
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| U S Geological Survey |
| 2003 |
The National Land Cover Database 2001 was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of federal agencies (www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (EPA), the U.S. Department of Agriculture (USDA), the U.S. Forest Service (USFS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (FWS), the Bureau of Land Management (BLM) and the USDA Natural Resources Conservation Service (NRCS). One of the primary goals of the project is to generate a current, consistent, seamless, and accurate National Land cover Database (NLCD) circa 2001 for the United States at medium spatial resolution. This landcover map and all documents pertaining to it are considered "provisional" until a formal accuracy assessment can be conducted. For a detailed definition and discussion on MRLC and the NLCD 2001 products, refer to Homer et al. (2004) and http://www.mrlc.gov/mrlc2k.asp.
The NLCD 2001 is created by partitioning the U.S. into mapping zones. A total of 66 mapping zones were delineated within the conterminous U.S. based on ecoregion and geographical characteristics, edge matching features and the size requirement of Landsat mosaics. Mapping zone 60 encompasses whole or portions of several states, including the states of New Jersey, Delaware, Maryland, Pennsylvania, Virginia, and the District of Columbia. Questions about the NLCD mapping zone 60 can be directed to the NLCD 2001 land cover mapping team at the National Center, EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov.
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| U S Geological Survey |
| 2003 |
The National Land Cover Database 2001 was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of federal agencies (www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (EPA), the U.S. Department of Agriculture (USDA), the U.S. Forest Service (USFS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (FWS), the Bureau of Land Management (BLM) and the USDA Natural Resources Conservation Service (NRCS). One of the primary goals of the project is to generate a current, consistent, seamless, and accurate National Land cover Database (NLCD) circa 2001 for the United States at medium spatial resolution. This landcover map and all documents pertaining to it are considered "provisional" until a formal accuracy assessment can be conducted. For a detailed definition and discussion on MRLC and the NLCD 2001 products, refer to Homer et al. (2004) and http://www.mrlc.gov/mrlc2k.asp.
The NLCD 2001 is created by partitioning the U.S. into mapping zones. A total of 66 mapping zones were delineated within the conterminous U.S. based on ecoregion and geographical characteristics, edge matching features and the size requirement of Landsat mosaics. Mapping zone 60 encompasses whole or portions of several states, including the states of New Jersey, Delaware, Maryland, Pennsylvania, Virginia, and the District of Columbia. Questions about the NLCD mapping zone 60 can be directed to the NLCD 2001 land cover mapping team at the National Center, EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov.
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| U S Geological Survey |
| 2003 |
The National Land Cover Database 2001 was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of federal agencies (www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (EPA), the U.S. Department of Agriculture (USDA), the U.S. Forest Service (USFS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (FWS), the Bureau of Land Management (BLM) and the USDA Natural Resources Conservation Service (NRCS). One of the primary goals of the project is to generate a current, consistent, seamless, and accurate National Land cover Database (NLCD) circa 2001 for the United States at medium spatial resolution. This landcover map and all documents pertaining to it are considered "provisional" until a formal accuracy assessment can be conducted. For a detailed definition and discussion on MRLC and the NLCD 2001 products, refer to Homer et al. (2004) and http://www.mrlc.gov/mrlc2k.asp.
The NLCD 2001 is created by partitioning the U.S. into mapping zones. A total of 66 mapping zones were delineated within the conterminous U.S. based on ecoregion and geographical characteristics, edge matching features and the size requirement of Landsat mosaics. Mapping zone 60 encompasses whole or portions of several states, including the states of New Jersey, Delaware, Maryland, Pennsylvania, Virginia, and the District of Columbia. Questions about the NLCD mapping zone 60 can be directed to the NLCD 2001 land cover mapping team at the National Center, EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov.
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| U S Geological Survey |
| 2004 |
The National Land Cover Database 2001 tree canopy layer for mapping zone 47 was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of federal agencies (www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (EPA), the U.S. Department of Agriculture (USDA), the U.S. Forest Service (USFS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (FWS), the Bureau of Land Management (BLM) and the USDA Natural Resources Conservation Service (NRCS). One of the primary goals of the project is to generate a current, consistent, seamless, and accurate National Land cover Database (NLCD) circa 2001 for the United States at medium spatial resolution. For a detailed definition and discussion on MRLC and the NLCD 2001 products, refer to Homer et al. (2003) and http://www.mrlc.gov/mrlc2k.asp.
The NLCD 2001 was created by partitioning the U.S. into mapping zones. A total of 66 mapping zones were delineated within the conterminous U.S. based on ecoregion and geographical characteristics, edge matching features and the size requirement of Landsat mosaics. Mapping zone 47 encompasses whole or portions of several states including the states of Kentucky, Indiana, Ohio, Tennessee, and Missouri. Questions about the NLCD mapping zone 47 can be directed to the NLCD 2001 land cover mapping team at the National Center, EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov.
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| U S Geological Survey |
| 1999 |
These data can be used in a geographic information system (GIS) for any
number of purposes such as assessing wildlife habitat, water quality,
pesticide runoff, land use change, etc. The State data sets are provided
with a 300 meter buffer beyond the State border to facilitate combining
the State files into larger regions.
The user must have a firm understanding of how the datasets were compiled
and the resulting limitations of these data. The National Land Cover Dataset
was compiled from Landsat satellite TM imagery (circa 1992) with a spatial
resolution of 30 meters and supplemented by various ancillary data (where
available). The analysis and interpretation of the satellite imagery was
conducted using very large, sometimes multi-state image mosaics (i.e. up to 18
Landsat scenes). Using a relatively small number of aerial photographs for
'ground truth', the thematic interpretations were necessarily conducted from a
spatially-broad perspective. Furthermore, the accuracy assessments (see below)
correspond to 'federal regions' which are groupings of contiguous states. Thus,
the reliability of the data is greatest at the state or multi-state level. The
statistical accuracy of the data is known only for the region.
Important Caution Advisory
With this in mind, users are cautioned to carefully scrutinize the data to
see if they are of sufficient reliability before attempting to use the
dataset for larger-scale or local analyses. This evaluation must be made
remembering that the NLCD represents conditions in the early 1990s.
The Pennsylvania portion of the NLCD was created as part of land cover
mapping activities for Federal Region III that includes the States of
Maryland, Delaware, Pennsylvania, Virginia, West Virginia, and the
District of Columbia. The NLCD classification contains 21 different
land cover categories with a spatial resolution of 30 meters. The NLCD
was produced as a cooperative effort between the U.S. Geological Survey
(USGS) and the U.S. Environmental Protection Agency (US EPA) to produce
a consistent, land cover data layer for the conterminous U.S. using
early 1990s Landsat thematic mapper (TM) data purchased by the
Multi-resolution Land Characterization (MRLC) Consortium. The MRLC
Consortium is a partnership of federal agencies that produce or use land
cover data. Partners include the USGS (National Mapping, Biological
Resources, and Water Resources Divisions), US EPA, the U.S. Forest Service,
and the National Oceanic and Atmospheric Administration.
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| U S Geological Survey |
| 1999 |
These data can be used in a geographic information system (GIS) for any
number of purposes such as assessing wildlife habitat, water quality,
pesticide runoff, land use change, etc. The State data sets are provided
with a 300 meter buffer beyond the State border to facilitate combining
the State files into larger regions.
The user must have a firm understanding of how the datasets were compiled
and the resulting limitations of these data. The National Land Cover Dataset
was compiled from Landsat satellite TM imagery (circa 1992) with a spatial
resolution of 30 meters and supplemented by various ancillary data (where
available). The analysis and interpretation of the satellite imagery was
conducted using very large, sometimes multi-state image mosaics (i.e. up to 18
Landsat scenes). Using a relatively small number of aerial photographs for
'ground truth', the thematic interpretations were necessarily conducted from a
spatially-broad perspective. Furthermore, the accuracy assessments (see below)
correspond to 'federal regions' which are groupings of contiguous states. Thus,
the reliability of the data is greatest at the state or multi-state level. The
statistical accuracy of the data is known only for the region.
Important Caution Advisory
With this in mind, users are cautioned to carefully scrutinize the data to
see if they are of sufficient reliability before attempting to use the
dataset for larger-scale or local analyses. This evaluation must be made
remembering that the NLCD represents conditions in the early 1990s.
The Pennsylvania portion of the NLCD was created as part of land cover
mapping activities for Federal Region III that includes the States of
Maryland, Delaware, Pennsylvania, Virginia, West Virginia, and the
District of Columbia. The NLCD classification contains 21 different
land cover categories with a spatial resolution of 30 meters. The NLCD
was produced as a cooperative effort between the U.S. Geological Survey
(USGS) and the U.S. Environmental Protection Agency (US EPA) to produce
a consistent, land cover data layer for the conterminous U.S. using
early 1990s Landsat thematic mapper (TM) data purchased by the
Multi-resolution Land Characterization (MRLC) Consortium. The MRLC
Consortium is a partnership of federal agencies that produce or use land
cover data. Partners include the USGS (National Mapping, Biological
Resources, and Water Resources Divisions), US EPA, the U.S. Forest Service,
and the National Oceanic and Atmospheric Administration.
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| U S Geological Survey |
| 1999 |
These data can be used in a geographic
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| U S Geological Survey |
| 2005 |
New York state boundary includes offshore boundaries (oceans, bays, and great lakes). This map layer portrays the State boundaries of the United States, and the boundaries of Puerto Rico and the U.S. Virgin Islands. The map layer was created by extracting the State boundary polygons from the individual
1:2,000,000-scale State boundary Digital Line Graph (DLG) files produced
by the U.S.
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| U S Geological Survey |
| 2004 |
The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water bodies. Reaches are also defined on waterbodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Geographic Data Committee.
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| U S Geological Survey |
| 2004 |
The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water bodies. Reaches are also defined on waterbodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Geographic Data Committee.
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| U S Geological Survey |
| 2004 |
The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water bodies. Reaches are also defined on waterbodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Geographic Data Committee.
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| U S Geological Survey |
| 2004 |
The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water bodies. Reaches are also defined on waterbodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Geographic Data Committee.
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| U S Geological Survey |
| 2004 |
The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water bodies. Reaches are also defined on waterbodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Geographic Data Committee.
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| U S Geological Survey |
| 2004 |
The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water bodies. Reaches are also defined on waterbodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Geographic Data Committee.
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| U S Geological Survey |
| 1999 |
The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that comprise the nation's surface water drainage system. Medium resolution NHD is based on the content of the U.S. Geological Survey 1:100,000-scale Digital Line Graph (DLG) hydrography data, integrated with reach-related information from the U.S. Environmental Protection Agency Reach File Version 3.0 (RF3). More specifically, it contains reach codes for networked features and isolated lakes, flow direction, names, stream level, and centerline representations for areal water bodies. Reaches are also defined to represent water bodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Geographic Data Committee.
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| U S Geological Survey |
| 2004 |
The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water bodies. Reaches are also defined on waterbodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Geographic Data Committee.
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| U S Geological Survey |
| 2004 |
The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water bodies. Reaches are also defined on waterbodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Geographic Data Committee.
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KMZ
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| U S Geological Survey |
| 2004 |
The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water bodies. Reaches are also defined on waterbodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Geographic Data Committee.
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| U S Geological Survey |
| 2004 |
The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water bodies. Reaches are also defined on waterbodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Geographic Data Committee.
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KMZ
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| U S Geological Survey |
| 2004 |
The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water bodies. Reaches are also defined on waterbodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Geographic Data Committee.
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KMZ
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| U S Geological Survey |
| 2004 |
The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water bodies. Reaches are also defined on waterbodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Geographic Data Committee.
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KMZ
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| U S Geological Survey |
| 2004 |
The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water bodies. Reaches are also defined on waterbodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Geographic Data Committee.
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KMZ
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| U S Geological Survey |
| 2004 |
The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water bodies. Reaches are also defined on waterbodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Geographic Data Committee.
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KMZ
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| U S Geological Survey |
| 2004 |
The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water bodies. Reaches are also defined on waterbodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Geographic Data Committee.
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KMZ
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| U S Geological Survey |
| 2004 |
The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water bodies. Reaches are also defined on waterbodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Geographic Data Committee.
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KMZ
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| U S Geological Survey |
| 1999 |
The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that comprise the nation's surface water drainage system. Medium resolution NHD is based on the content of the U.S. Geological Survey 1:100,000-scale Digital Line Graph (DLG) hydrography data, integrated with reach-related information from the U.S. Environmental Protection Agency Reach File Version 3.0 (RF3). More specifically, it contains reach codes for networked features and isolated lakes, flow direction, names, stream level, and centerline representations for areal water bodies. Reaches are also defined to represent water bodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Geographic Data Committee.
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KMZ
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| U S Geological Survey |
| 2004 |
The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water bodies. Reaches are also defined on waterbodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Geographic Data Committee.
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KMZ
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| U S Geological Survey |
| 2004 |
The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water bodies. Reaches are also defined on waterbodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Geographic Data Committee.
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KMZ
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| U S Geological Survey |
| 2004 |
The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water bodies. Reaches are also defined on waterbodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Geographic Data Committee.
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KMZ
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| U S Geological Survey |
| 2004 |
The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water bodies. Reaches are also defined on waterbodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Geographic Data Committee.
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KMZ
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| U S Geological Survey |
| 2004 |
The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water bodies. Reaches are also defined on waterbodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Geographic Data Committee.
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| U S Geological Survey |
| 1999 |
The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that comprise the nation's surface water drainage system. Medium resolution NHD is based on the content of the U.S. Geological Survey 1:100,000-scale Digital Line Graph (DLG) hydrography data, integrated with reach-related information from the U.S. Environmental Protection Agency Reach File Version 3.0 (RF3). More specifically, it contains reach codes for networked features and isolated lakes, flow direction, names, stream level, and centerline representations for areal water bodies. Reaches are also defined to represent water bodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Geographic Data Committee.
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| U S Geological Survey |
| 2015 |
This data will assist in the evaluation of coastal storm damage impacts; aid in post-event reconstruction and mitigation planning for future events and collect LiDAR for counties heavily impacted by storm and flooding for which data is incomplete or inadequate to conduct proper analysis, as part of USGS Hurricane Sandy response.
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| U S Geological Survey |
| 2015 |
This data will assist in the evaluation of coastal storm damage impacts; aid in post-event reconstruction and mitigation planning for future events and collect LiDAR for counties heavily impacted by storm and flooding for which data is incomplete or inadequate to conduct proper analysis, as part of USGS Hurricane Sandy response.
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| U S Geological Survey |
| 2015 |
This data will assist in the evaluation of coastal storm damage impacts; aid in post-event reconstruction and mitigation planning for future events and collect LiDAR for counties heavily impacted by storm and flooding for which data is incomplete or inadequate to conduct proper analysis, as part of USGS Hurricane Sandy response.
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| U S Geological Survey |
| 2014 |
The National Land Cover Database products are created through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of Federal agencies (www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (EPA), the U.S. Department of Agriculture - Forest Service (USDA-FS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (USFWS), the Bureau of Land Management (BLM) and the USDA Natural Resources Conservation Service (NRCS). The success of NLCD over nearly two decades is credited to the continuing collaborative spirit of the agencies that make up the MRLC. NLCD 2011 is the most up-to-date iteration of the National Land Cover Database, the definitive Landsat-based, 30-meter resolution land cover database for the Nation. The data in NLCD 2011 are completely integrated with NLCD 2001 (2011 Edition, amended 2014) and NLCD 2006 (2011 Edition, amended 2014).
For NLCD 2011, there are 5 primary data products:
1) NLCD 2011 Land Cover
2) NLCD 2006/2011 Land Cover Change Pixels labeled with the 2011 land cover class
3) NLCD 2011 Percent Developed Imperviousness
4) NLCD 2006/2011 Percent Developed Imperviousness Change Pixels
5) NLCD 2011 Tree Canopy Cover provided by an MRLC partner - the USDA Forest Service Remote Sensing Applications Center.
In addition, ancillary metadata includes the NLCD 2011 Path/Row Index shapefile showing the footprint of Landsat scenes and change analysis pairs used to derive 2006/2011 spectral change. All Landsat scene acquisition dates are included in the shapefile's attribute table. As part of the NLCD 2011 project, NLCD 2001 and 2006 land cover and impervious data products were revised and reissued (2011 Edition, amended 2014) to provide full compatibility with the new NLCD 2011 products. The 2014 amended version corrects for the over-elimination of small areas of the four developed classes.
NLCD Tree Canopy Cover was created using MRLC mapping zones from NLCD 2001 (see Tree Canopy Cover metadata for additional detail). All other NLCD 2011 products were created on a path/row basis and mosaicked to create a seamless national product. Questions about the NLCD 2011 land cover product can be directed to the NLCD 2011 land cover mapping team at the USGS/EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov.
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| U S Geological Survey |
| 2014 |
The National Land Cover Database products are created through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of federal agencies (www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (EPA), the U.S. Department of Agriculture -Forest Service (USDA-FS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (FWS), the Bureau of Land Management (BLM) and the USDA Natural Resources Conservation Service (NRCS). The success of NLCD over nearly two decades is credited to the continuing collaborative spirit of the agencies that make up the MRLC. NLCD 2011 is the definitive Landsat-based, 30-meter resolution land cover database for the Nation. The data in NLCD 2011 are completely integrated with NLCD 2001 (2011 Edition, amended 2014) and NLCD 2006 (2011 Edition, amended 2014).
For NLCD 2011, there are 5 primary data products:
1) NLCD 2011 Land Cover;
2) NLCD 2006/2011 Land Cover Change Pixels labeled with the 2011 land cover class;
3) NLCD 2011 Percent Developed Imperviousness;
4) NLCD 2006/2011 Percent Developed Imperviousness Change Pixels; and
5) NLCD 2011 Tree Canopy Cover provided by an MRLC partner - the USDA Forest Service Remote Sensing Applications Center.
In addition, ancillary metadata includes the NLCD 2011 Path/Row Index shapefile showing the footprint of Landsat scenes and change analysis pairs used to derive 2006/2011 spectral change. All Landsat scene acquisition dates are included in the shapefile's attribute table. As part of the NLCD 2011 project, NLCD 2001 and 2006 land cover and impervious data products have been revised and reissued (2011 Edition, amended 2014) to provide full compatibility with the new NLCD 2011 products. The 2014 amended version corrects for the over-elimination of small areas of the four developed classes.
NLCD Tree Canopy Cover was created using MRLC mapping zones from NLCD 2001 (see Tree Canopy Cover metadata for additional detail). All other NLCD 2011 products were created on a path/row basis and mosaicked to create a seamless national product. Questions about the NLCD 2011 products can be directed to the NLCD 2011 land cover mapping team at the USGS/EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov.
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| U S Geological Survey |
| 2019 |
The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released four
National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, and 2011.
These products provide spatially explicit and reliable information on the Nation’s land cover and land cover
change. To continue the legacy of NLCD and further establish a long-term monitoring capability for the Nation’s
land resources, the USGS has designed a new generation of NLCD products named NLCD 2016. The NLCD 2016
design aims to provide innovative, consistent, and robust methodologies for production of a multi-temporal land
cover and land cover change database from 2001 to 2016 at 2–3-year intervals. Comprehensive research was
conducted and resulted in developed strategies for NLCD 2016: a streamlined process for assembling and preprocessing
Landsat imagery and geospatial ancillary datasets; a multi-source integrated training data development
and decision-tree based land cover classifications; a temporally, spectrally, and spatially integrated land
cover change analysis strategy; a hierarchical theme-based post-classification and integration protocol for
generating land cover and change products; a continuous fields biophysical parameters modeling method; and
an automated scripted operational system for the NLCD 2016 production. The performance of the developed
strategies and methods were tested in twenty World Reference System-2 path/row throughout the conterminous
U.S. An overall agreement ranging from 71% to 97% between land cover classification and reference data was
achieved for all tested area and all years. Results from this study confirm the robustness of this comprehensive
and highly automated procedure for NLCD 2016 operational mapping.
Questions about the NLCD 2016 land cover product can be directed to the NLCD 2016 land cover mapping team at USGS EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov. See included spatial metadata for more details.
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| U S Geological Survey |
| 2019 |
The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released four National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, and 2011. These products provide spatially explicit and reliable information on the Nation’s land cover and land cover change. To continue the legacy of NLCD and further establish a long-term monitoring capability for the Nation’s land resources, the USGS has designed a new generation of NLCD products named NLCD 2016. The NLCD 2016 design aims to provide innovative, consistent, and robust methodologies for production of a multi-temporal land cover and land cover change database from 2001 to 2016 at 2–3-year intervals. Comprehensive research was conducted and resulted in developed strategies for NLCD 2016: a streamlined process for assembling and preprocessing Landsat imagery and geospatial ancillary datasets; a multi-source integrated training data development and decision-tree based land cover classifications; a temporally, spectrally, and spatially integrated land cover change analysis strategy; a hierarchical theme-based post-classification and integration protocol for generating land cover and change products; a continuous fields biophysical parameters modeling method; and an automated scripted operational system for the NLCD 2016 production. The performance of the developed strategies and methods were tested in twenty World Reference System-2 path/rows throughout the conterminous U.S. An overall agreement ranging from 71% to 97% between land cover classification and reference data was achieved for all tested areas and all years. Results from this study confirm the robustness of this comprehensive and highly automated procedure for NLCD 2016 operational mapping. Questions about the NLCD 2016 land cover product can be directed to the NLCD 2016 land cover mapping team at USGS EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov. See included spatial metadata for more details.
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| U S Geological Survey |
| 2014 |
The National Land Cover Database products are created through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of federal agencies (www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (EPA), the U.S. Department of Agriculture -Forest Service (USDA-FS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (FWS), the Bureau of Land Management (BLM) and the USDA Natural Resources Conservation Service (NRCS). The success of NLCD over nearly two decades is credited to the continuing collaborative spirit of the agencies that make up the MRLC. NLCD 2011 is the definitive Landsat-based, 30-meter resolution land cover database for the Nation. The data in NLCD 2011 are completely integrated with NLCD 2001 (2011 Edition, amended 2014) and NLCD 2006 (2011 Edition, amended 2014). For NLCD 2011, there are 5 primary data products: 1) NLCD 2011 Land Cover; 2) NLCD 2006/2011 Land Cover Change Pixels labeled with the 2011 land cover class; 3) NLCD 2011 Percent Developed Imperviousness; 4) NLCD 2006/2011 Percent Developed Imperviousness Change Pixels; and 5) NLCD 2011 Tree Canopy Cover provided by an MRLC partner - the USDA Forest Service Remote Sensing Applications Center. In addition, ancillary metadata includes the NLCD 2011 Path/Row Index shapefile showing the footprint of Landsat scenes and change analysis pairs used to derive 2006/2011 spectral change. All Landsat scene acquisition dates are included in the shapefile's attribute table. As part of the NLCD 2011 project, NLCD 2001 and 2006 land cover and impervious data products have been revised and reissued (2011 Edition, amended 2014) to provide full compatibility with the new NLCD 2011 products. The 2014 amended version corrects for the over-elimination of small areas of the four developed classes. NLCD Tree Canopy Cover was created using MRLC mapping zones from NLCD 2001 (see Tree Canopy Cover metadata for additional detail). All other NLCD 2011 products were created on a path/row basis and mosaicked to create a seamless national product. Questions about the NLCD 2011 products can be directed to the NLCD 2011 land cover mapping team at the USGS/EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov.
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| U S Geological Survey |
| 2021 |
The 2020 North American Land Cover 30-meter dataset was produced as part of the North American Land Change Monitoring System (NALCMS), a trilateral effort between Natural Resources Canada, the United States Geological Survey, and three Mexican organizations including the National Institute of Statistics and Geography (Instituto Nacional de EstadÃstica y GeografÃa), National Commission for the Knowledge and Use of the Biodiversity (Comisión Nacional Para el Conocimiento y Uso de la Biodiversidad), and the National Forestry Commission of Mexico (Comisión Nacional Forestal). The collaboration is facilitated by the Commission for Environmental Cooperation, an international organization created by the Canada, Mexico, and United States governments under the North American Agreement on Environmental Cooperation to promote environmental collaboration between the three countries.The general objective of NALCMS is to devise, through collective effort, a harmonized multi-scale land cover monitoring approach which ensures high accuracy and consistency in monitoring land cover changes at the North American scale and which meets each country’s specific requirements.This 30-meter dataset of North American Land Cover reflects land cover information for 2020 from Mexico and Canada, 2019 over the conterminous United States and 2021 over Alaska. Each country developed its own classification method to identify Land Cover classes and then provided an input layer to produce a continental Land Cover map across North America. Canada, Mexico, and the United States developed their own 30-meter land cover products.The main inputs for image classification were 30-meter Landsat 8 Collection 2 Level 1 data in the three countries (Canada, the United States and Mexico). Image selection processes and reduction to specific spectral bands varied among the countries due to study-site-specific requirements. While Canada selected most images from the year 2020 with a few from 2019 and 2021, the Conterminous United States employed mainly images from 2019, while Alaska land cover maps are mainly based on the use of images from 2021. The land cover map for Mexico was based on land cover change detection between 2015 and 2020 Mexico Landsat 8 mosaics.In order to generate a seamless and consistent land cover map of North America, national maps were generated for Canada by the CCRS; for Mexico by CONABIO, INEGI, and CONAFOR; and for the United States by the USGS. Each country chose their own approaches, ancillary data, and land cover mapping methodologies to create national datasets. This North America dataset was produced by combining the national land cover datasets. The integration of the three national products merged four Land Cover map sections, Alaska, Canada, the conterminous United States and Mexico.
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| U S Geological Survey |
| 2002 |
The Assessment Unit is the fundamental unit used in the National Assessment Project for the assessment of undiscovered oil and gas resources. The Assessment Unit is defined within the context of the higher-level Total Petroleum System. The Assessment Unit is shown here as a geographic boundary interpreted, defined, and mapped by the geologist responsible for the province and incorporates a set of known or postulated oil and (or) gas accumulations sharing similar geologic, geographic, and temporal properties within the Total Petroleum System, such as source rock, timing, migration pathways, trapping mechanism, and hydrocarbon type. The Assessment Unit boundary is defined geologically as the limits of the geologic elements that define the Assessment Unit, such as limits of reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are Assessment Units that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the Assessment Unit boundary.
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| U S Geological Survey |
| 2002 |
Cell maps for each oil and gas assessment unit were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in an assessment unit or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, dry, or the type of production of the wells located within the cell is unknown. The well information was initially retrieved from the IHS Energy Group, PI/Dwights PLUS Well Data on CD-ROM, which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary PI/Dwights PLUS Well Data. No proprietary data are displayed or included in the cell maps. The data from PI/Dwights PLUS Well Data were current as of October 2001 when the cell maps were created in 2002.
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| U S Geological Survey |
| 2002 |
The Assessment Unit is the fundamental unit used in the National Assessment Project for the assessment of undiscovered oil and gas resources. The Assessment Unit is defined within the context of the higher-level Total Petroleum System. The Assessment Unit is shown here as a geographic boundary interpreted, defined, and mapped by the geologist responsible for the province and incorporates a set of known or postulated oil and (or) gas accumulations sharing similar geologic, geographic, and temporal properties within the Total Petroleum System, such as source rock, timing, migration pathways, trapping mechanism, and hydrocarbon type. The Assessment Unit boundary is defined geologically as the limits of the geologic elements that define the Assessment Unit, such as limits of reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are Assessment Units that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the Assessment Unit boundary.
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| U S Geological Survey |
| 2002 |
Cell maps for each oil and gas assessment unit were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in an assessment unit or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, dry, or the type of production of the wells located within the cell is unknown. The well information was initially retrieved from the IHS Energy Group, PI/Dwights PLUS Well Data on CD-ROM, which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary PI/Dwights PLUS Well Data. No proprietary data are displayed or included in the cell maps. The data from PI/Dwights PLUS Well Data were current as of October 2001 when the cell maps were created in 2002.
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| U S Geological Survey |
| 2002 |
The Assessment Unit is the fundamental unit used in the National Assessment Project for the assessment of undiscovered oil and gas resources. The Assessment Unit is defined within the context of the higher-level Total Petroleum System. The Assessment Unit is shown here as a geographic boundary interpreted, defined, and mapped by the geologist responsible for the province and incorporates a set of known or postulated oil and (or) gas accumulations sharing similar geologic, geographic, and temporal properties within the Total Petroleum System, such as source rock, timing, migration pathways, trapping mechanism, and hydrocarbon type. The Assessment Unit boundary is defined geologically as the limits of the geologic elements that define the Assessment Unit, such as limits of reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are Assessment Units that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the Assessment Unit boundary.
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| U S Geological Survey |
| 2002 |
Cell maps for each oil and gas assessment unit were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in an assessment unit or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, dry, or the type of production of the wells located within the cell is unknown. The well information was initially retrieved from the IHS Energy Group, PI/Dwights PLUS Well Data on CD-ROM, which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary PI/Dwights PLUS Well Data. No proprietary data are displayed or included in the cell maps. The data from PI/Dwights PLUS Well Data were current as of October 2001 when the cell maps were created in 2002.
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| U S Geological Survey |
| 1996 |
Digital Elevation Model (DEM) is the terminology adopted by the USGS to describe terrain elevation data sets in a digital raster form. The standard DEM consists of a regular array of elevations cast on a designated coordinate projection system. The DEM data are stored as a series of profiles in which the spacing of the elevations along and between each profile is in regular whole number intervals. The normal orientation of data is by columns and rows. Each column contains a series of elevations ordered from south to north with the order of the columns from west to east. The DEM is formatted as one ASCII header record (A-record), followed by a series of profile records (B-records) each of which include a short B-record header followed by a series of ASCII integer elevations per each profile. The last physical record of the DEM is an accuracy record (C-record). 7.5-minute DEM (30- by 30-meter data spacing, cast on Universal Transverse Mercator (UTM) projection). Provides coverage in 7.5- by 7.5-minute blocks. Each product provides the same coverage as a standard USGS 7.5-minute quadrangle without over edge. Coverage is for the Contiguous United States, Hawaii, and Puerto Rico.
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| U S Geological Survey |
| 1996 |
Digital Elevation Model (DEM) is the terminology adopted by the USGS to describe terrain elevation data sets in a digital raster form. The standard DEM consists of a regular array of elevations cast on a designated coordinate projection system. The DEM data are stored as a series of profiles in which the spacing of the elevations along and between each profile is in regular whole number intervals. The normal orientation of data is by columns and rows. Each column contains a series of elevations ordered from south to north with the order of the columns from west to east. The DEM is formatted as one ASCII header record (A-record), followed by a series of profile records (B-records) each of which include a short B-record header followed by a series of ASCII integer elevations per each profile. The last physical record of the DEM is an accuracy record (C-record). 7.5-minute DEM (30- by 30-meter data spacing, cast on Universal Transverse Mercator (UTM) projection). Provides coverage in 7.5- by 7.5-minute blocks. Each product provides the same coverage as a standard USGS 7.5-minute quadrangle without over edge. Coverage is for the Contiguous United States, Hawaii, and Puerto Rico.
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| U S Geological Survey |
| 2019 |
Breakline data is used to hydroflatten the DEMs created for the Pennsylvania North Central Lidar QL1 project. Breaklines are reviewed against LiDAR intensity imagery to verify completeness of capture.
Geographic Extent: 4 counties in Pennsylvania, covering approximately 85 total square miles.
Dataset Description: The Pennsylvania North Central Lidar QL1 project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.35 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 1.3. The data were developed based on a horizontal projection/datum of NAD 1983 StatePlane Pennsylvania North FIPS 3701 Feet, Foot US and vertical datum of NAVD88 GEOID12b, Foot US. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 95 individual 5,000 ft x 5,000 ft tiles; and as 31 10,000 ft x 10,000 ft tiled intensity imagery, and as tiled bare earth DEMs; Continuous breaklines were produced in Esri file geodatabase format.
Ground Conditions: LiDAR was collected in spring 2019, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Quantum Spatial, Inc. utilized a total of 326 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 546 independent accuracy checkpoints, 322 in Bare Earth and Urban landcovers (322 NVA points), 224 in Tall Weeds categories (224 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2019 |
These lidar data are processed Classified LAS 1.4 files, formatted to 95 individual 5,000 ft x 5,000 ft tiles; used to create intensity images, 3D breaklines, and hydro-flattened DEMs as necessary.
Geographic Extent: 4 counties in Pennsylvania, covering approximately 85 total square miles.
Dataset Description: The Pennsylvania North Central Lidar QL1 project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.35 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 1.3. The data were developed based on a horizontal projection/datum of NAD 1983 StatePlane Pennsylvania North FIPS 3701 Feet, Foot US and vertical datum of NAVD88 GEOID12b, Foot US. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 95 individual 5,000 ft x 5,000 ft tiles; and as 31 10,000 ft x 10,000 ft tiled intensity imagery, and as tiled bare earth DEMs; Continuous breaklines were produced in Esri file geodatabase format.
Ground Conditions: LiDAR was collected in spring 2019, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Quantum Spatial, Inc. utilized a total of 326 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 546 independent accuracy checkpoints, 322 in Bare Earth and Urban landcovers (322 NVA points), 224 in Tall Weeds categories (224 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2019 |
Contours with a 1 foot interval in Esri file geodatabase format.
Geographic Extent: 4 counties in Pennsylvania, covering approximately 85 total square miles.
Dataset Description: The Pennsylvania North Central Lidar QL1 project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.35 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 1.3. The data were developed based on a horizontal projection/datum of NAD 1983 StatePlane Pennsylvania North FIPS 3701 Feet, Foot US and vertical datum of NAVD88 GEOID12b, Foot US. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 31 individual 10,000 ft x 10,000 ft tiles, as tiled intensity imagery, and as tiled bare earth DEMs; all tiled to the same 10,000 ft x 10,000 ft schema. Continuous breaklines were produced in Esri file geodatabase format.
Ground Conditions: LiDAR was collected in spring 2019, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Quantum Spatial, Inc. utilized a total of 326 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 546 independent accuracy checkpoints, 322 in Bare Earth and Urban landcovers (322 NVA points), 224 in Tall Weeds categories (224 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2019 |
These are Digital Elevation Model (DEM) data for Pennsylvania as part of the required deliverables for the Pennsylvania North Central Lidar QL1 project. Class 2 (ground) LiDAR points in conjunction with the hydro breaklines were used to create a 1.25 foot hydro-flattened Raster DEM.
Geographic Extent: 4 counties in Pennsylvania, covering approximately 85 total square miles.
Dataset Description: The Pennsylvania North Central Lidar QL1 project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.35 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 1.3. The data were developed based on a horizontal projection/datum of NAD 1983 StatePlane Pennsylvania North FIPS 3701 Feet, Foot US and vertical datum of NAVD88 GEOID12b, Foot US. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 95 individual 5,000 ft x 5,000 ft tiles; and as 31 10,000 ft x 10,000 ft tiled intensity imagery, and as tiled bare earth DEMs; Continuous breaklines were produced in Esri file geodatabase format.
Ground Conditions: LiDAR was collected in spring 2019, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Quantum Spatial, Inc. utilized a total of 326 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 546 independent accuracy checkpoints, 322 in Bare Earth and Urban landcovers (322 NVA points), 224 in Tall Weeds categories (224 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2019 |
Pennsylvania North Central Lidar QL1 Intensity Imagery.
Geographic Extent: 4 counties in Pennsylvania, covering approximately 85 total square miles.
Dataset Description: The Pennsylvania North Central Lidar QL1 project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.35 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 1.3. The data were developed based on a horizontal projection/datum of NAD 1983 StatePlane Pennsylvania North FIPS 3701 Feet, Foot US and vertical datum of NAVD88 GEOID12b, Foot US. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 95 individual 5,000 ft x 5,000 ft tiles; and as 31 10,000 ft x 10,000 ft tiled intensity imagery, and as tiled bare earth DEMs; Continuous breaklines were produced in Esri file geodatabase format.
Ground Conditions: LiDAR was collected in spring 2019, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Quantum Spatial, Inc. utilized a total of 326 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 546 independent accuracy checkpoints, 322 in Bare Earth and Urban landcovers (322 NVA points), 224 in Tall Weeds categories (224 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2019 |
Breakline data is used to hydroflatten the DEMs created for the Pennsylvania North Central Lidar QL2 project. Breaklines are reviewed against LiDAR intensity imagery to verify completeness of capture.
Geographic Extent: 42 counties in Pennsylvania, covering approximately 14244 total square miles.
Dataset Description: The Pennsylvania North Central Lidar QL2 project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.71 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 1.3. The data were developed based on a horizontal projection/datum of NAD 1983 StatePlane Pennsylvania North FIPS 3701 Feet, Foot US and vertical datum of NAVD88 GEOID12B, Foot US. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 15,404 individual 5,000 ft x 5,000 ft tiles; and 3971 individual 10,000 ft x 10,000 ft tiles, as tiled intensity imagery, and as tiled bare earth DEMs. Continuous breaklines were produced in Esri file geodatabase format.
Ground Conditions: LiDAR was collected in spring and fall 2019, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Quantum Spatial, Inc. utilized a total of 326 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 546 independent accuracy checkpoints, 322 in Bare Earth and Urban landcovers (322 NVA points), 224 in Tall Weeds categories (224 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2019 |
Breakline data is used to hydroflatten the DEMs created for the Pennsylvania North Central Lidar QL2 project. Breaklines are reviewed against LiDAR intensity imagery to verify completeness of capture.
Geographic Extent: 35 counties in Pennsylvania, covering approximately 5922 total square miles.
Dataset Description: The Pennsylvania North Central Lidar QL2 project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.71 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 1.3. The data were developed based on a horizontal projection/datum of NAD 1983 StatePlane Pennsylvania South FIPS 3702 Feet, Foot US and vertical datum of NAVD88 GEOID12B, Foot US. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 6,269 individual 5,000 ft x 5,000 ft tiles; 1651 individual 10,000 ft x 10,000 ft tiles, as tiled intensity imagery, and as tiled bare earth DEMs.Continuous breaklines were produced in Esri file geodatabase format.
Ground Conditions: LiDAR was collected in spring and fall 2019, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Quantum Spatial, Inc. utilized a total of 326 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 546 independent accuracy checkpoints, 322 in Bare Earth and Urban landcovers (322 NVA points), 224 in Tall Weeds categories (224 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2019 |
These lidar data are processed Classified LAS 1.4 files, formatted to 15,404 individual 5,000 ft x 5,000 ft tiles; used to create intensity images, 3D breaklines, and hydro-flattened DEMs as necessary.
Geographic Extent: 42 counties in Pennsylvania, covering approximately 14244 total square miles.
Dataset Description: The Pennsylvania North Central Lidar QL2 project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.71 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 1.3. The data were developed based on a horizontal projection/datum of NAD 1983 StatePlane Pennsylvania North FIPS 3701 Feet, Foot US and vertical datum of NAVD88 GEOID12B, Foot US. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 15,404 individual 5,000 ft x 5,000 ft tiles; and 3971 individual 10,000 ft x 10,000 ft tiles, as tiled intensity imagery, and as tiled bare earth DEMs. Continuous breaklines were produced in Esri file geodatabase format.
Ground Conditions: LiDAR was collected in spring and fall 2019, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Quantum Spatial, Inc. utilized a total of 326 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 546 independent accuracy checkpoints, 322 in Bare Earth and Urban landcovers (322 NVA points), 224 in Tall Weeds categories (224 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2019 |
These lidar data are processed Classified LAS 1.4 files, formatted to 6,269 individual 5,000 ft x 5,000 ft tiles; used to create intensity images, 3D breaklines, and hydro-flattened DEMs as necessary.
Geographic Extent: 35 counties in Pennsylvania, covering approximately 5922 total square miles.
Dataset Description: The Pennsylvania North Central Lidar QL2 project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.71 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 1.3. The data were developed based on a horizontal projection/datum of NAD 1983 StatePlane Pennsylvania South FIPS 3702 Feet, Foot US and vertical datum of NAVD88 GEOID12B, Foot US. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 6,269 individual 5,000 ft x 5,000 ft tiles; 1651 individual 10,000 ft x 10,000 ft tiles, as tiled intensity imagery, and as tiled bare earth DEMs.Continuous breaklines were produced in Esri file geodatabase format.
Ground Conditions: LiDAR was collected in spring and fall 2019, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Quantum Spatial, Inc. utilized a total of 326 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 546 independent accuracy checkpoints, 322 in Bare Earth and Urban landcovers (322 NVA points), 224 in Tall Weeds categories (224 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2019 |
Contours with a 1 foot interval in Esri file geodatabase format.
Geographic Extent: 42 counties in Pennsylvania, covering approximately 13813 total square miles.
Dataset Description: The Pennsylvania North Central Lidar QL2 project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.71 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 1.3. The data were developed based on a horizontal projection/datum of NAD 1983 StatePlane Pennsylvania North FIPS 3701 Feet, Foot US and vertical datum of NAVD88 GEOID12B, Foot US. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 3971 individual 10,000 ft x 10,000 ft tiles, as tiled intensity imagery, and as tiled bare earth DEMs; all tiled to the same 10,000 ft x 10,000 ft schema. Continuous breaklines were produced in Esri file geodatabase format.
Ground Conditions: LiDAR was collected in spring and fall 2019, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Quantum Spatial, Inc. utilized a total of 326 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 546 independent accuracy checkpoints, 322 in Bare Earth and Urban landcovers (322 NVA points), 224 in Tall Weeds categories (224 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2019 |
Contours with a 1 foot interval in Esri file geodatabase format.
Geographic Extent: 34 counties in Pennsylvania, covering approximately 5621 total square miles.
Dataset Description: The Pennsylvania North Central Lidar QL2 project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.71 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 1.3. The data were developed based on a horizontal projection/datum of NAD 1983 StatePlane Pennsylvania South FIPS 3702 Feet, Foot US and vertical datum of NAVD88 GEOID12B, Foot US. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 1651 individual 10,000 ft x 10,000 ft tiles, as tiled intensity imagery, and as tiled bare earth DEMs; all tiled to the same 10,000 ft x 10,000 ft schema. Continuous breaklines were produced in Esri file geodatabase format.
Ground Conditions: LiDAR was collected in spring and fall 2019, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Quantum Spatial, Inc. utilized a total of 326 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 546 independent accuracy checkpoints, 322 in Bare Earth and Urban landcovers (322 NVA points), 224 in Tall Weeds categories (224 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2019 |
County Mosaics - These are Digital Elevation Model (DEM) data for Pennsylvania as part of the required deliverables for the Pennsylvania North Central Lidar QL1 project. Class 2 (ground) LiDAR points in conjunction with the hydro breaklines were used to create a 1.25 foot hydro-flattened Raster DEM.
Geographic Extent: 4 counties in Pennsylvania, covering approximately 85 total square miles.
Dataset Description: The Pennsylvania North Central Lidar QL1 project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.35 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 1.3. The data were developed based on a horizontal projection/datum of NAD 1983 StatePlane Pennsylvania North FIPS 3701 Feet, Foot US and vertical datum of NAVD88 GEOID12b, Foot US. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 95 individual 5,000 ft x 5,000 ft tiles; and as 31 10,000 ft x 10,000 ft tiled intensity imagery, and as tiled bare earth DEMs; Continuous breaklines were produced in Esri file geodatabase format.
Ground Conditions: LiDAR was collected in spring 2019, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Quantum Spatial, Inc. utilized a total of 326 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 546 independent accuracy checkpoints, 322 in Bare Earth and Urban landcovers (322 NVA points), 224 in Tall Weeds categories (224 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2019 |
These are Digital Elevation Model (DEM) data for Pennsylvania as part of the required deliverables for the Pennsylvania North Central Lidar QL2 project. Class 2 (ground) LiDAR points in conjunction with the hydro breaklines were used to create a 2.5 foot hydro-flattened Raster DEM.
Geographic Extent: 42 counties in Pennsylvania, covering approximately 14244 total square miles.
Dataset Description: The Pennsylvania North Central Lidar QL2 project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.71 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 1.3. The data were developed based on a horizontal projection/datum of NAD 1983 StatePlane Pennsylvania North FIPS 3701 Feet, Foot US and vertical datum of NAVD88 GEOID12B, Foot US. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 15,404 individual 5,000 ft x 5,000 ft tiles; and 3971 individual 10,000 ft x 10,000 ft tiles, as tiled intensity imagery, and as tiled bare earth DEMs. Continuous breaklines were produced in Esri file geodatabase format.
Ground Conditions: LiDAR was collected in spring and fall 2019, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Quantum Spatial, Inc. utilized a total of 326 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 546 independent accuracy checkpoints, 322 in Bare Earth and Urban landcovers (322 NVA points), 224 in Tall Weeds categories (224 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2019 |
Pennsylvania North Central Lidar QL2 Intensity Imagery.
Geographic Extent: 35 counties in Pennsylvania, covering approximately 5922 total square miles.
Dataset Description: The Pennsylvania North Central Lidar QL2 project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.71 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 1.3. The data were developed based on a horizontal projection/datum of NAD 1983 StatePlane Pennsylvania South FIPS 3702 Feet, Foot US and vertical datum of NAVD88 GEOID12B, Foot US. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 6,269 individual 5,000 ft x 5,000 ft tiles; 1651 individual 10,000 ft x 10,000 ft tiles, as tiled intensity imagery, and as tiled bare earth DEMs.Continuous breaklines were produced in Esri file geodatabase format.
Ground Conditions: LiDAR was collected in spring and fall 2019, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Quantum Spatial, Inc. utilized a total of 326 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 546 independent accuracy checkpoints, 322 in Bare Earth and Urban landcovers (322 NVA points), 224 in Tall Weeds categories (224 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2019 |
Pennsylvania North Central Lidar QL2 Intensity Imagery.
Geographic Extent: 42 counties in Pennsylvania, covering approximately 14244 total square miles.
Dataset Description: The Pennsylvania North Central Lidar QL2 project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.71 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 1.3. The data were developed based on a horizontal projection/datum of NAD 1983 StatePlane Pennsylvania North FIPS 3701 Feet, Foot US and vertical datum of NAVD88 GEOID12B, Foot US. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 15,404 individual 5,000 ft x 5,000 ft tiles; and 3971 individual 10,000 ft x 10,000 ft tiles, as tiled intensity imagery, and as tiled bare earth DEMs. Continuous breaklines were produced in Esri file geodatabase format.
Ground Conditions: LiDAR was collected in spring and fall 2019, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Quantum Spatial, Inc. utilized a total of 326 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 546 independent accuracy checkpoints, 322 in Bare Earth and Urban landcovers (322 NVA points), 224 in Tall Weeds categories (224 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2019 |
Pennsylvania North Central Lidar QL2 Intensity Imagery.
Geographic Extent: 35 counties in Pennsylvania, covering approximately 5922 total square miles.
Dataset Description: The Pennsylvania North Central Lidar QL2 project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.71 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 1.3. The data were developed based on a horizontal projection/datum of NAD 1983 StatePlane Pennsylvania South FIPS 3702 Feet, Foot US and vertical datum of NAVD88 GEOID12B, Foot US. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 6,269 individual 5,000 ft x 5,000 ft tiles; 1651 individual 10,000 ft x 10,000 ft tiles, as tiled intensity imagery, and as tiled bare earth DEMs.Continuous breaklines were produced in Esri file geodatabase format.
Ground Conditions: LiDAR was collected in spring and fall 2019, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Quantum Spatial, Inc. utilized a total of 326 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 546 independent accuracy checkpoints, 322 in Bare Earth and Urban landcovers (322 NVA points), 224 in Tall Weeds categories (224 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2002 |
Quadrangle Boundaries of Pennsylvania
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| U S Geological Survey |
| 2020 |
Breakline data is used to hydroflatten the DEMs created for the PA_WesternPA_2019_D20 Lidar QL1 project. Breaklines are reviewed against LiDAR intensity imagery to verify completeness of capture.
Geographic Extent: 2 counties in Pennsylvania, covering approximately 62 total square miles.
Dataset Description: The PA_WesternPA_2019_D20 Lidar QL1 project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.35 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 2.1. The data were developed based on a horizontal projection/datum of NAD 1983 2011 StatePlane Pennsylvania North FIPS 3701 Ft US, Foot US and vertical datum of NAVD88 Geoid 12b, Foot US. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 114 individual 5,000 ft x 5,000 ft tiles and as tiled intensity imagery, and tiled bare earth DEMs formatted to 40 10,000 ft x 10,000 ft tiles. Continuous breaklines were produced in Esri file geodatabase format.
Ground Conditions: LiDAR was collected in spring 2020, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, NV5 Geospatial, powered by Quantum Spatial utilized a total of 274 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 485 independent accuracy checkpoints, 291 in Bare Earth and Urban landcovers (291 NVA points), 194 in Tall Weeds categories (194 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2020 |
Pennsylvania Western Lidar 2020 QL1; Classified Point Cloud
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| U S Geological Survey |
| 2020 |
Contours with a 1 foot interval in Esri file geodatabase format.
Geographic Extent: 2 counties in Pennsylvania, covering approximately 62 total square miles.
Dataset Description: The PA_WesternPA_2019_D20 Lidar QL1 project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.35 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 2.1. The data were developed based on a horizontal projection/datum of NAD 1983 2011 StatePlane Pennsylvania North FIPS 3701 Ft US, Foot US and vertical datum of NAVD88 Geoid 12b, Foot US. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 114 individual 5,000 ft x 5,000 ft tiles and as tiled intensity imagery, and tiled bare earth DEMs formatted to 40 10,000 ft x 10,000 ft tiles. Continuous breaklines were produced in Esri file geodatabase format.
Ground Conditions: LiDAR was collected in spring 2020, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, NV5 Geospatial, powered by Quantum Spatial utilized a total of 274 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 485 independent accuracy checkpoints, 291 in Bare Earth and Urban landcovers (291 NVA points), 194 in Tall Weeds categories (194 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2020 |
These are Digital Elevation Model (DEM) data for Pennsylvania as part of the required deliverables for the PA_WesternPA_2019_D20 Lidar QL1 project. Class 2 (ground) LiDAR points in conjunction with the hydro breaklines were used to create a 1.25 foot hydro-flattened Raster DEM.
Geographic Extent: 2 counties in Pennsylvania, covering approximately 62 total square miles.
Dataset Description: The PA_WesternPA_2019_D20 Lidar QL1 project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.35 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 2.1. The data were developed based on a horizontal projection/datum of NAD 1983 2011 StatePlane Pennsylvania North FIPS 3701 Ft US, Foot US and vertical datum of NAVD88 Geoid 12b, Foot US. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 114 individual 5,000 ft x 5,000 ft tiles and as tiled intensity imagery, and tiled bare earth DEMs formatted to 40 10,000 ft x 10,000 ft tiles. Continuous breaklines were produced in Esri file geodatabase format.
Ground Conditions: LiDAR was collected in spring 2020, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, NV5 Geospatial, powered by Quantum Spatial utilized a total of 274 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 485 independent accuracy checkpoints, 291 in Bare Earth and Urban landcovers (291 NVA points), 194 in Tall Weeds categories (194 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2020 |
PA_WesternPA_2019_D20 Lidar QL1 Intensity Imagery.
Geographic Extent: 2 counties in Pennsylvania, covering approximately 62 total square miles.
Dataset Description: The PA_WesternPA_2019_D20 Lidar QL1 project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.35 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 2.1. The data were developed based on a horizontal projection/datum of NAD 1983 2011 StatePlane Pennsylvania North FIPS 3701 Ft US, Foot US and vertical datum of NAVD88 Geoid 12b, Foot US. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 114 individual 5,000 ft x 5,000 ft tiles and as tiled intensity imagery, and tiled bare earth DEMs formatted to 40 10,000 ft x 10,000 ft tiles. Continuous breaklines were produced in Esri file geodatabase format.
Ground Conditions: LiDAR was collected in spring 2020, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, NV5 Geospatial, powered by Quantum Spatial utilized a total of 274 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 485 independent accuracy checkpoints, 291 in Bare Earth and Urban landcovers (291 NVA points), 194 in Tall Weeds categories (194 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2020 |
Breakline data is used to hydroflatten the DEMs created for the PA_WesternPA_2019_D20 Lidar QL2 project. Breaklines are reviewed against LiDAR intensity imagery to verify completeness of capture.
Geographic Extent: 22 counties in Pennsylvania, covering approximately 6282 total square miles.
Dataset Description: The PA_WesternPA_2019_D20 Lidar QL2 project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.71 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 2.1. The data were developed based on a horizontal projection/datum of NAD 1983 2011 StatePlane Pennsylvania North FIPS 3701 Ft US, Foot US and vertical datum of NAVD88 Geoid 12b, Foot US. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 7229 individual 5,000 ft x 5,000 ft tiles, and as tiled intensity imagery and tiled bare earth DEMs formatted to 1848 individual 10,000 ft x 10,000 ft tiles. Continuous breaklines were produced in Esri file geodatabase format.
Ground Conditions: LiDAR was collected in fall 2019 and spring 2020, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, NV5 Geospatial, powered by Quantum Spatial utilized a total of 274 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 485 independent accuracy checkpoints, 291 in Bare Earth and Urban landcovers (291 NVA points), 194 in Tall Weeds categories (194 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2020 |
Breakline data is used to hydroflatten the DEMs created for the PA_WesternPA_2019_D20 Lidar QL2 project. Breaklines are reviewed against LiDAR intensity imagery to verify completeness of capture.
Geographic Extent: 31 counties in Pennsylvania, covering approximately 9299 total square miles.
Dataset Description: The PA_WesternPA_2019_D20 Lidar QL2 project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.71 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 2.1. The data were developed based on a horizontal projection/datum of NAD 1983 2011 StatePlane Pennsylvania South FIPS 3702 Ft US, Foot US and vertical datum of NAVD88 Geoid 12b, Foot US. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 10576 individual 5,000 ft x 5,000 ft tiles, and as tiled intensity imagery and tiled bare earth DEMs 2684 individual 10,000 ft x 10,000 ft tiles. Continuous breaklines were produced in Esri file geodatabase format.
Ground Conditions: LiDAR was collected in fall 2019 and spring 2020, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, NV5 Geospatial, powered by Quantum Spatial utilized a total of 274 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 485 independent accuracy checkpoints, 291 in Bare Earth and Urban landcovers (291 NVA points), 194 in Tall Weeds categories (194 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2020 |
Pennsylvania Western Lidar 2020 QL2; Classified Point Cloud
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| U S Geological Survey |
| 2020 |
These lidar data are processed Classified LAS 1.4 files, formatted to 2684 individual 10,000 ft x 10,000 ft tiles; used to create intensity images, 3D breaklines, and hydro-flattened DEMs as necessary.
Geographic Extent: 31 counties in Pennsylvania, covering approximately 9299 total square miles.
Dataset Description: The PA_WesternPA_2019_D20 Lidar QL2 project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.71 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 2.1. The data were developed based on a horizontal projection/datum of NAD 1983 2011 StatePlane Pennsylvania South FIPS 3702 Ft US, Foot US and vertical datum of NAVD88 Geoid 12b, Foot US. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 10576 individual 5,000 ft x 5,000 ft tiles, and as tiled intensity imagery and tiled bare earth DEMs 2684 individual 10,000 ft x 10,000 ft tiles. Continuous breaklines were produced in Esri file geodatabase format.
Ground Conditions: LiDAR was collected in fall 2019 and spring 2020, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, NV5 Geospatial, powered by Quantum Spatial utilized a total of 274 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 485 independent accuracy checkpoints, 291 in Bare Earth and Urban landcovers (291 NVA points), 194 in Tall Weeds categories (194 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2020 |
Contours with a 1 foot interval in Esri file geodatabase format.
Geographic Extent: 22 counties in Pennsylvania, covering approximately 6282 total square miles.
Dataset Description: The PA_WesternPA_2019_D20 Lidar QL2 project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.71 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 2.1. The data were developed based on a horizontal projection/datum of NAD 1983 2011 StatePlane Pennsylvania North FIPS 3701 Ft US, Foot US and vertical datum of NAVD88 Geoid 12b, Foot US. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 7229 individual 5,000 ft x 5,000 ft tiles, and as tiled intensity imagery and tiled bare earth DEMs formatted to 1848 individual 10,000 ft x 10,000 ft tiles. Continuous breaklines were produced in Esri file geodatabase format.
Ground Conditions: LiDAR was collected in fall 2019 and spring 2020, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, NV5 Geospatial, powered by Quantum Spatial utilized a total of 274 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 485 independent accuracy checkpoints, 291 in Bare Earth and Urban landcovers (291 NVA points), 194 in Tall Weeds categories (194 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2020 |
Contours with a 1 foot interval in Esri file geodatabase format.
Geographic Extent: 31 counties in Pennsylvania, covering approximately 9299 total square miles.
Dataset Description: The PA_WesternPA_2019_D20 Lidar QL2 project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.71 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 2.1. The data were developed based on a horizontal projection/datum of NAD 1983 2011 StatePlane Pennsylvania South FIPS 3702 Ft US, Foot US and vertical datum of NAVD88 Geoid 12b, Foot US. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 2684 individual 10,000 ft x 10,000 ft tiles, as tiled intensity imagery, and as tiled bare earth DEMs; all tiled to the same 10,000 ft x 10,000 ft schema. Continuous breaklines were produced in Esri file geodatabase format.
Ground Conditions: LiDAR was collected in fall 2019 and spring 2020, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, NV5 Geospatial, powered by Quantum Spatial utilized a total of 274 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 485 independent accuracy checkpoints, 291 in Bare Earth and Urban landcovers (291 NVA points), 194 in Tall Weeds categories (194 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2020 |
These are Digital Elevation Model (DEM) data for Pennsylvania as part of the required deliverables for the PA_WesternPA_2019_D20 Lidar QL2 project. Class 2 (ground) LiDAR points in conjunction with the hydro breaklines were used to create a 2.5 foot hydro-flattened Raster DEM.
Geographic Extent: 22 counties in Pennsylvania, covering approximately 6282 total square miles.
Dataset Description: The PA_WesternPA_2019_D20 Lidar QL2 project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.71 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 2.1. The data were developed based on a horizontal projection/datum of NAD 1983 2011 StatePlane Pennsylvania North FIPS 3701 Ft US, Foot US and vertical datum of NAVD88 Geoid 12b, Foot US. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 7229 individual 5,000 ft x 5,000 ft tiles, and as tiled intensity imagery and tiled bare earth DEMs formatted to 1848 individual 10,000 ft x 10,000 ft tiles. Continuous breaklines were produced in Esri file geodatabase format.
Ground Conditions: LiDAR was collected in fall 2019 and spring 2020, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, NV5 Geospatial, powered by Quantum Spatial utilized a total of 274 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 485 independent accuracy checkpoints, 291 in Bare Earth and Urban landcovers (291 NVA points), 194 in Tall Weeds categories (194 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2020 |
These are Digital Elevation Model (DEM) data for Pennsylvania as part of the required deliverables for the PA_WesternPA_2019_D20 Lidar QL2 project. Class 2 (ground) LiDAR points in conjunction with the hydro breaklines were used to create a 2.5 foot hydro-flattened Raster DEM.
Geographic Extent: 31 counties in Pennsylvania, covering approximately 9299 total square miles.
Dataset Description: The PA_WesternPA_2019_D20 Lidar QL2 project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.71 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 2.1. The data were developed based on a horizontal projection/datum of NAD 1983 2011 StatePlane Pennsylvania South FIPS 3702 Ft US, Foot US and vertical datum of NAVD88 Geoid 12b, Foot US. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 10576 individual 5,000 ft x 5,000 ft tiles, and as tiled intensity imagery and tiled bare earth DEMs 2684 individual 10,000 ft x 10,000 ft tiles. Continuous breaklines were produced in Esri file geodatabase format.
Ground Conditions: LiDAR was collected in fall 2019 and spring 2020, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, NV5 Geospatial, powered by Quantum Spatial utilized a total of 274 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 485 independent accuracy checkpoints, 291 in Bare Earth and Urban landcovers (291 NVA points), 194 in Tall Weeds categories (194 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2020 |
Pennsylvania Western Lidar 2020 QL2; Intensity Imagery
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| U S Geological Survey |
| 2020 |
PA_WesternPA_2019_D20 Lidar QL2 Intensity Imagery.
Geographic Extent: 31 counties in Pennsylvania, covering approximately 9299 total square miles.
Dataset Description: The PA_WesternPA_2019_D20 Lidar QL2 project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.71 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 2.1. The data were developed based on a horizontal projection/datum of NAD 1983 2011 StatePlane Pennsylvania South FIPS 3702 Ft US, Foot US and vertical datum of NAVD88 Geoid 12b, Foot US. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 10576 individual 5,000 ft x 5,000 ft tiles, and as tiled intensity imagery and tiled bare earth DEMs 2684 individual 10,000 ft x 10,000 ft tiles. Continuous breaklines were produced in Esri file geodatabase format.
Ground Conditions: LiDAR was collected in fall 2019 and spring 2020, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, NV5 Geospatial, powered by Quantum Spatial utilized a total of 274 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 485 independent accuracy checkpoints, 291 in Bare Earth and Urban landcovers (291 NVA points), 194 in Tall Weeds categories (194 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2003 |
This map layer contains the shallowest principal aquifers of the
conterminous United States, Hawaii, Puerto Rico, and the U.S. Virgin
Islands, portrayed as polygons. The map layer was developed as part of
the effort to produce the maps published at 1:2,500,000 in the printed
series "Ground Water Atlas of the United States". The published maps
contain base and cultural features not included in these data. This is a
replacement for the July 1998 map layer called Principal Aquifers of the
48 Conterminous United States.
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| U S Geological Survey |
| 2002 |
Quadrangle Boundaries for the continental United States and Hawaii
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| U S Geological Survey |
| 2017 |
Contours with a 2-foot interval in Esri file shapefile format.
Geographic Extent: 13 counties in Pennsylvania, covering approximately 6,602 total
square miles. Dataset Description: The South Central Pennsylvania 2017 QL2 LiDAR
project called for the planning, acquisition, processing, and derivative products of
lidar data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. Project
specifications are based on the U.S. Geological Survey National Geospatial Program
Base LiDAR Specification, Version 1.2. The data were developed based on a horizontal
projection/datum of NAD 1983 (2011), UTM Zone 18, meters and vertical datum of NAVD
1988 (GEOID 12B), meters. LiDAR data were delivered as processed Classified LAS 1.4
files formatted to 7,975 individual 1,500-meter x 1,500-meter tiles, as tiled
intensity imagery, and as tiled bare earth DEMs; all tiled to the same 1,500-meter x
1,500-meter schema. Continuous breaklines were produced in Esri file geodatabase
format. Ground Conditions: LiDAR was collected in fall 2017, while no snow was on
the ground and rivers were at or below normal levels. In order to post process the
LiDAR data to meet task order specifications and meet ASPRS vertical accuracy
guidelines, Quantum Spatial, Inc. utilized a total of 150 ground control points that
were used to calibrate the LiDAR to known ground locations established throughout
the project area. An additional 245 independent accuracy checkpoints, 142 in Bare
Earth and Urban landcovers (142 NVA points), 103 in Tall Weeds categories (103 VVA
points), were used to assess the vertical accuracy of the data. These checkpoints
were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2000 |
A scope of work was developed in response to a request by the U. S. Army Corps
of Engineers, Philadelphia District. The request was to perform a topographic
change grid analysis for the Frankford 7.5-minute quadrangle, 1:24,000-scale
topographic map, which includes the Wissinoming neighborhood, and the Germantown 7.5-minute quadrangle, which includes the Logan and Feltonville neighborhoods of the City of Philadelphia. The following tasks were performed under this scope of work: A GPS-corrected GIS grid analysis for each quadrangle was completed and is accompanied by documentation that describes procedures and provides metadata of the informational content of the GIS. A high-resolution global positioning system (GPS) survey was conducted for each topographic quadrangle in order to evaluate and correct systematic discrepancies in elevation between the modern and historic surveys. Prior to release, the fully documented GPS-corrected GIS grid analysis for each quadrangle was reviewed for (1) com-pleteness of documentation and for (2) appropriate analysis and discussion of uncertainties.
The following report is in fulfillment of the tasks outlined in this scope of work and was performed by the U. S. Geological Survey for the U. S. Army Corps of Engineers, Philadelphia District under MIPR agreement number: W25PHS93358288.
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| U S Geological Survey |
| 1996 |
A Digital Raster Graphic (DRG) is a raster image of a scanned USGS
topographic or planimetric map including the collar information, georeferenced to
the UTM grid.
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| U S Geological Survey |
| 1996 |
A Digital Raster Graphic (DRG) is a raster image of a scanned USGS
topographic or planimetric map including the collar information, georeferenced to
the UTM grid.
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| U S Geological Survey |
| 1996 |
A Digital Raster Graphic (DRG) is a raster image of a scanned USGS
topographic or planimetric map including the collar information, georeferenced to
the UTM grid.
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| U S Geological Survey |
| 1996 |
A Digital Raster Graphic (DRG) is a raster image of a scanned USGS
topographic or planimetric map including the collar information, georeferenced to
the UTM grid.
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| U S Geological Survey |
| 1996 |
A Digital Raster Graphic (DRG) is a raster image of a scanned USGS
topographic or planimetric map including the collar information, georeferenced to
the UTM grid.
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| U S Geological Survey |
| 1996 |
A Digital Raster Graphic (DRG) is a raster image of a scanned USGS
topographic or planimetric map including the collar information, georeferenced to
the UTM grid.
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| U S Geological Survey |
| 1996 |
A Digital Raster Graphic (DRG) is a raster image of a scanned USGS
topographic or planimetric map including the collar information, georeferenced to
the UTM grid.
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| U S Geological Survey |
| 2002 |
The Total Petroleum System is used in the National Assessment Project and incorporates the Assessment Unit, which is the fundamental geologic unit used for the assessment of undiscovered oil and gas resources. The Total Petroleum System is shown here as a geographic boundary defined and mapped by the geologist responsible for the province and incorporates not only the set of known or postulated oil and (or) gas accumulations, but also the geologic interpretation of the essential elements and processes within the petroleum system that relate to source, generation, migration, accumulation, and trapping of the discovered and undiscovered petroleum resource(s).
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| U S Geological Survey |
| 2009 |
One foot GSD, natural color (RGB), 8-bit digital orthophotography for the City of Erie, Pennsylvania. The imagery was collected using the Leica Geosystems ADS40 sensor between April 27th and June 6th, 2009 at an average altitude of 9,600 feet above ground level. The National Elevation Dataset (NED) was used as vertical control. Airborne GPS/IMU data was used as horizontal control. The orthophotography is georeferenced to UTM Zone 17 North, meter units, NAD83, NAVD88. The imagery was produced by Pixxures, Inc. under contract for DigitalGlobe, Inc." Data received at EROS were reprojected from 1-foot Pennsylvania 3-band, State Plane to 3-band, 0.30 meter UTM Zone 17 and resampled to align to the USNG using the USGS Seamless system. The naming convention is based on the U.S. National Grid (USNG), taking the coordinates of the SW corner of the orthoimage. The metadata were imported and updated for display through The National Map Seamless Server at Chip-level metadata are provided in XML format.
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| U S Geological Survey |
| 2009 |
TILE INDEX - One foot GSD, natural color (RGB), 8-bit digital orthophotography for the City of Erie, Pennsylvania. The imagery was collected using the Leica Geosystems ADS40 sensor between April 27th and June 6th, 2009 at an average altitude of 9,600 feet above ground level. The National Elevation Dataset (NED) was used as vertical control. Airborne GPS/IMU data was used as horizontal control. The orthophotography is georeferenced to UTM Zone 17 North, meter units, NAD83, NAVD88. The imagery was produced by Pixxures, Inc. under contract for DigitalGlobe, Inc." Data received at EROS were reprojected from 1-foot Pennsylvania 3-band, State Plane to 3-band, 0.30 meter UTM Zone 17 and resampled to align to the USNG using the USGS Seamless system. The naming convention is based on the U.S. National Grid (USNG), taking the coordinates of the SW corner of the orthoimage. The metadata were imported and updated for display through The National Map Seamless Server at Chip-level metadata are provided in XML format.
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| U S Geological Survey |
| 2009 |
One foot GSD, natural color (RGB), 8-bit digital orthophotography for the City of PIttsburgh, Pennsylvania. The imagery was collected using the Leica Geosystems ADS40 sensor between April 26th and July 8th, 2009 at an average altitude of 9,600 feet above ground level. The National Elevation Dataset (NED) was used as vertical control. Airborne GPS/IMU data was used as horizontal control. The orthophotography is georeferenced to UTM Zone 17 North, meter units, NAD83, NAVD88. The imagery was produced by Pixxures, Inc. under contract for DigitalGlobe, Inc." Data received at EROS were reprojected from 1-foot Pennsylvania 3-band, State Plane to 3-band, 0.30 meter UTM Zone 17 and resampled to align to the USNG using the USGS Seamless system. The naming convention is based on the U.S. National Grid (USNG), taking the coordinates of the SW corner of the orthoimage. The metadata were imported and updated for display through The National Map Seamless Server at Chip-level metadata are provided in XML format.
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| U S Geological Survey |
| 2012 |
"This task order consists of digital orthophoto production covering the Pittsburgh Area, Pennsylvania." An orthoimage is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation have been mathematically removed. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. There is no image overlap between adjacent files.
Data received at Earth Resources Observation and Science Center (EROS) were verified as:
Projection: NAD_1983_UTM_Zone_17N
Resolution: 0.3000 m
Type: Natural Color
and resampled to align to the U.S. National Grid (USNG) using The National Map. The naming convention is based on the U.S. National Grid (USNG), taking the coordinates of the SW corner of the orthoimage. The metadata were imported and updated for display through The National Map at http://nationalmap.gov/viewer.html Chip-level metadata are provided in HTML and XML format. Data were compressed utilizing IAS software. The compression was JPEG2000 Lossy Compressed. The file format created was .jp2.
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| U S Geological Survey |
| 2009 |
TILE INDEX - One foot GSD, natural color (RGB), 8-bit digital orthophotography for the City of PIttsburgh, Pennsylvania. The imagery was collected using the Leica Geosystems ADS40 sensor between April 26th and July 8th, 2009 at an average altitude of 9,600 feet above ground level. The National Elevation Dataset (NED) was used as vertical control. Airborne GPS/IMU data was used as horizontal control. The orthophotography is georeferenced to UTM Zone 17 North, meter units, NAD83, NAVD88. The imagery was produced by Pixxures, Inc. under contract for DigitalGlobe, Inc." Data received at EROS were reprojected from 1-foot Pennsylvania 3-band, State Plane to 3-band, 0.30 meter UTM Zone 17 and resampled to align to the USNG using the USGS Seamless system. The naming convention is based on the U.S. National Grid (USNG), taking the coordinates of the SW corner of the orthoimage. The metadata were imported and updated for display through The National Map Seamless Server at Chip-level metadata are provided in XML format.
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| U S Geological Survey |
| 2012 |
TILE INDEX -"This task order consists of digital orthophoto production covering the Pittsburgh Area, Pennsylvania." An orthoimage is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation have been mathematically removed. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. There is no image overlap between adjacent files.
Data received at Earth Resources Observation and Science Center (EROS) were verified as:
Projection: NAD_1983_UTM_Zone_17N
Resolution: 0.3000 m
Type: Natural Color
and resampled to align to the U.S. National Grid (USNG) using The National Map. The naming convention is based on the U.S. National Grid (USNG), taking the coordinates of the SW corner of the orthoimage. The metadata were imported and updated for display through The National Map at http://nationalmap.gov/viewer.html Chip-level metadata are provided in HTML and XML format. Data were compressed utilizing IAS software. The compression was JPEG2000 Lossy Compressed. The file format created was .jp2.
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| U S Geological Survey |
| 2009 |
The Geographic Names Information System (GNIS), developed by the U.S. Geological Survey in cooperation with the U.S. Board on Geographic Names (BGN), contains information about physical and cultural geographic features in the United States and associated areas, both current and historical, but not including roads and highways. The database also contains geographic names in Antarctica. The database holds the Federally recognized name of each feature and defines the location of the feature by state, county, USGS topographic map, and geographic coordinates. Other feature attributes include names or spellings other than the official name, feature designations, feature class, historical and descriptive information, and for some categories of features the geometric boundaries. The database assigns a unique feature identifier, a random number, that is a key for accessing, integrating, or reconciling GNIS data with other data sets. The GNIS is our Nation's official repository of domestic geographic feature names information.
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| U S Geological Survey |
| 2009 |
The Geographic Names Information System (GNIS), developed by the U.S. Geological Survey in cooperation with the U.S. Board on Geographic Names (BGN), contains information about physical and cultural geographic features in the United States and associated areas, both current and historical, but not including roads and highways. The database also contains geographic names in Antarctica. The database holds the Federally recognized name of each feature and defines the location of the feature by state, county, USGS topographic map, and geographic coordinates. Other feature attributes include names or spellings other than the official name, feature designations, feature class, historical and descriptive information, and for some categories of features the geometric boundaries. The database assigns a unique feature identifier, a random number, that is a key for accessing, integrating, or reconciling GNIS data with other data sets. The GNIS is our Nation's official repository of domestic geographic feature names information.
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| U S Geological Survey |
| 2009 |
The Geographic Names Information System (GNIS), developed by the U.S. Geological Survey in cooperation with the U.S. Board on Geographic Names (BGN), contains information about physical and cultural geographic features in the United States and associated areas, both current and historical, but not including roads and highways. The database also contains geographic names in Antarctica. The database holds the Federally recognized name of each feature and defines the location of the feature by state, county, USGS topographic map, and geographic coordinates. Other feature attributes include names or spellings other than the official name, feature designations, feature class, historical and descriptive information, and for some categories of features the geometric boundaries. The database assigns a unique feature identifier, a random number, that is a key for accessing, integrating, or reconciling GNIS data with other data sets. The GNIS is our Nation's official repository of domestic geographic feature names information.
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| U S Geological Survey |
| 2023 |
This dataset is Elevation-derived hydrography (EDH) for the 140G00221F0093-PA_EDHL_Raystown_2021_D21 project covering HU 02050302 - Upper Juniata Watershed. The hydrography layer contains line features representing stream rivers and polygons representing waterbody. The EDH was derived from light detection and ranging (lidar) derived Digital Elevation Model of 1m, flown as part of 3 different projects between November 2017 and March 2020. This dataset was created to meet the requirements of the USGS Elevation-derived hydrography specification, https://www.usgs.gov/core-science-systems/ngp/ss/elevation-derived-hydrography-specifications. The line features contain Elevation class (EClass) codes useful for hydro-enforcement, including culvert identification. Feature Class (FCLASS) and Feature codes (FCodes) are hydrography codes compatible with the National Hydrography Dataset (NHD). The EDH product should be suitable for pre-conflation to the NHD.
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| U S Geological Survey |
| 2023 |
This dataset is Elevation-derived hydrography (EDH) for the 140G00221F0093-PA_EDHL_Raystown_2021_D21 project covering HU 02050303 - Raystown Watershed. The hydrography layer contains line features representing stream rivers and polygons representing waterbody. The EDH was derived from light detection and ranging (lidar) derived Digital Elevation Model of 1m, flown as part of 3 different projects between November 2017 and March 2020. This dataset was created to meet the requirements of the USGS Elevation-derived hydrography specification, https://www.usgs.gov/core-science-systems/ngp/ss/elevation-derived-hydrography-specifications. The line features contain Elevation class (EClass) codes useful for hydro-enforcement, including culvert identification. Feature Class (FCLASS) and Feature codes (FCodes) are hydrography codes compatible with the National Hydrography Dataset (NHD). The EDH product should be suitable for pre-conflation to the NHD.
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| U S Geological Survey |
| 2023 |
This dataset is Elevation-derived hydrography (EDH) for the 140G00221F0093-PA_EDHL_Raystown_2021_D21 project covering HU 02050304 - Lower Juniata Watershed. The hydrography layer contains line features representing stream rivers and polygons representing waterbody. The EDH was derived from light detection and ranging (lidar) derived Digital Elevation Model of 1m, flown as part of 3 different projects between November 2017 and March 2020. This dataset was created to meet the requirements of the USGS Elevation-derived hydrography specification, https://www.usgs.gov/core-science-systems/ngp/ss/elevation-derived-hydrography-specifications. The line features contain Elevation class (EClass) codes useful for hydro-enforcement, including culvert identification. Feature Class (FCLASS) and Feature codes (FCodes) are hydrography codes compatible with the National Hydrography Dataset (NHD). The EDH product should be suitable for pre-conflation to the NHD.
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| U S Geological Survey |
| 2011 |
About GeoPDF data files
PDF (Portable Document Format) digital files are now available for US Geological Survey topographic quadrangle maps. Each file is essentially a scan of a topographic map with the added feature of being georegistered. The files can be used as a PDF file, enabling users to view topo maps onscreen.
The GeoPDF format is an extension to Adobe's PDF 1.3 and higher versions enabling GIS functionality within standard PDF files. This format is designed for the efficient distribution and communication of rich spatial data to anyone who needs to view, review, verify, update, or print it. Because GeoPDF files are highly compressed and encapsulated, they are smaller, faster, and easier to transmit than GIS data sets, without the overhead associated with typical GIS spatial data sets (or the management of database tables, external links, and dependencies). Using the GeoPDF format, publishers of spatial data can select the specific spatial data they want recipients to see and can publish GIS source files into a single GeoPDF file.
GeoPDF files are not a replacement for native GIS formats. GIS professionals still need the original files for editing or updating spatial data. GeoPDF files enable non-GIS professionals, field technicians, business executives, and their colleagues to utilize rich spatial information. Users can view and print GeoPDF files with the free and ubiquitous Adobe Reader ,and they can do more with the data using a free plug-in called TerraGo Toolbar. Users do not have to install this plug-in to view GeoPDF files.
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| U S Geological Survey |
| 2014 |
About GeoPDF data files
PDF (Portable Document Format) digital files are now available for US Geological Survey topographic quadrangle maps. Each file is essentially a scan of a topographic map with the added feature of being georegistered. The files can be used as a PDF file, enabling users to view topo maps onscreen.
The GeoPDF format is an extension to Adobe's PDF 1.3 and higher versions enabling GIS functionality within standard PDF files. This format is designed for the efficient distribution and communication of rich spatial data to anyone who needs to view, review, verify, update, or print it. Because GeoPDF files are highly compressed and encapsulated, they are smaller, faster, and easier to transmit than GIS data sets, without the overhead associated with typical GIS spatial data sets (or the management of database tables, external links, and dependencies). Using the GeoPDF format, publishers of spatial data can select the specific spatial data they want recipients to see and can publish GIS source files into a single GeoPDF file.
GeoPDF files are not a replacement for native GIS formats. GIS professionals still need the original files for editing or updating spatial data. GeoPDF files enable non-GIS professionals, field technicians, business executives, and their colleagues to utilize rich spatial information. Users can view and print GeoPDF files with the free and ubiquitous Adobe Reader ,and they can do more with the data using a free plug-in called TerraGo Toolbar. Users do not have to install this plug-in to view GeoPDF files.
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| U S Geological Survey |
| 2011 |
The USGS Historical Quadrangle Scanning Project (HQSP) is scanning all scales and all editions of topographic maps published by the U.S. Geological Survey (USGS) since the inception of the topographic mapping program in 1884. This map is provided as a general purpose map in GeoPDF for users who are not GIS experts.
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| U S Geological Survey |
| 2011 |
About GeoPDF data files
PDF (Portable Document Format) digital files are now available for US Geological Survey topographic quadrangle maps. Each file is essentially a scan of a topographic map with the added feature of being georegistered. The files can be used as a PDF file, enabling users to view topo maps onscreen.
The GeoPDF format is an extension to Adobe's PDF 1.3 and higher versions enabling GIS functionality within standard PDF files. This format is designed for the efficient distribution and communication of rich spatial data to anyone who needs to view, review, verify, update, or print it. Because GeoPDF files are highly compressed and encapsulated, they are smaller, faster, and easier to transmit than GIS data sets, without the overhead associated with typical GIS spatial data sets (or the management of database tables, external links, and dependencies). Using the GeoPDF format, publishers of spatial data can select the specific spatial data they want recipients to see and can publish GIS source files into a single GeoPDF file.
GeoPDF files are not a replacement for native GIS formats. GIS professionals still need the original files for editing or updating spatial data. GeoPDF files enable non-GIS professionals, field technicians, business executives, and their colleagues to utilize rich spatial information. Users can view and print GeoPDF files with the free and ubiquitous Adobe Reader ,and they can do more with the data using a free plug-in called TerraGo Toolbar. Users do not have to install this plug-in to view GeoPDF files.
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| U S Geological Survey |
| 2014 |
About GeoPDF data files
PDF (Portable Document Format) digital files are now available for US Geological Survey topographic quadrangle maps. Each file is essentially a scan of a topographic map with the added feature of being georegistered. The files can be used as a PDF file, enabling users to view topo maps onscreen.
The GeoPDF format is an extension to Adobe's PDF 1.3 and higher versions enabling GIS functionality within standard PDF files. This format is designed for the efficient distribution and communication of rich spatial data to anyone who needs to view, review, verify, update, or print it. Because GeoPDF files are highly compressed and encapsulated, they are smaller, faster, and easier to transmit than GIS data sets, without the overhead associated with typical GIS spatial data sets (or the management of database tables, external links, and dependencies). Using the GeoPDF format, publishers of spatial data can select the specific spatial data they want recipients to see and can publish GIS source files into a single GeoPDF file.
GeoPDF files are not a replacement for native GIS formats. GIS professionals still need the original files for editing or updating spatial data. GeoPDF files enable non-GIS professionals, field technicians, business executives, and their colleagues to utilize rich spatial information. Users can view and print GeoPDF files with the free and ubiquitous Adobe Reader ,and they can do more with the data using a free plug-in called TerraGo Toolbar. Users do not have to install this plug-in to view GeoPDF files.
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| U S Geological Survey |
| 2011 |
The USGS Historical Quadrangle Scanning Project (HQSP) is scanning all scales and all editions of topographic maps published by the U.S. Geological Survey (USGS) since the inception of the topographic mapping program in 1884. This map is provided as a general purpose map in GeoPDF for users who are not GIS experts.
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| U S Geological Survey |
| 2011 |
About GeoPDF data files
PDF (Portable Document Format) digital files are now available for US Geological Survey topographic quadrangle maps. Each file is essentially a scan of a topographic map with the added feature of being georegistered. The files can be used as a PDF file, enabling users to view topo maps onscreen.
The GeoPDF format is an extension to Adobe's PDF 1.3 and higher versions enabling GIS functionality within standard PDF files. This format is designed for the efficient distribution and communication of rich spatial data to anyone who needs to view, review, verify, update, or print it. Because GeoPDF files are highly compressed and encapsulated, they are smaller, faster, and easier to transmit than GIS data sets, without the overhead associated with typical GIS spatial data sets (or the management of database tables, external links, and dependencies). Using the GeoPDF format, publishers of spatial data can select the specific spatial data they want recipients to see and can publish GIS source files into a single GeoPDF file.
GeoPDF files are not a replacement for native GIS formats. GIS professionals still need the original files for editing or updating spatial data. GeoPDF files enable non-GIS professionals, field technicians, business executives, and their colleagues to utilize rich spatial information. Users can view and print GeoPDF files with the free and ubiquitous Adobe Reader ,and they can do more with the data using a free plug-in called TerraGo Toolbar. Users do not have to install this plug-in to view GeoPDF files.
Metadata
|
Download
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| U S Geological Survey |
| 2014 |
About GeoPDF data files
PDF (Portable Document Format) digital files are now available for US Geological Survey topographic quadrangle maps. Each file is essentially a scan of a topographic map with the added feature of being georegistered. The files can be used as a PDF file, enabling users to view topo maps onscreen.
The GeoPDF format is an extension to Adobe's PDF 1.3 and higher versions enabling GIS functionality within standard PDF files. This format is designed for the efficient distribution and communication of rich spatial data to anyone who needs to view, review, verify, update, or print it. Because GeoPDF files are highly compressed and encapsulated, they are smaller, faster, and easier to transmit than GIS data sets, without the overhead associated with typical GIS spatial data sets (or the management of database tables, external links, and dependencies). Using the GeoPDF format, publishers of spatial data can select the specific spatial data they want recipients to see and can publish GIS source files into a single GeoPDF file.
GeoPDF files are not a replacement for native GIS formats. GIS professionals still need the original files for editing or updating spatial data. GeoPDF files enable non-GIS professionals, field technicians, business executives, and their colleagues to utilize rich spatial information. Users can view and print GeoPDF files with the free and ubiquitous Adobe Reader ,and they can do more with the data using a free plug-in called TerraGo Toolbar. Users do not have to install this plug-in to view GeoPDF files.
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| U S Geological Survey |
| 2011 |
The USGS Historical Quadrangle Scanning Project (HQSP) is scanning all scales and all editions of topographic maps published by the U.S. Geological Survey (USGS) since the inception of the topographic mapping program in 1884. This map is provided as a general purpose map in GeoPDF for users who are not GIS experts.
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| U S Geological Survey |
| 2011 |
About GeoPDF data files
PDF (Portable Document Format) digital files are now available for US Geological Survey topographic quadrangle maps. Each file is essentially a scan of a topographic map with the added feature of being georegistered. The files can be used as a PDF file, enabling users to view topo maps onscreen.
The GeoPDF format is an extension to Adobe's PDF 1.3 and higher versions enabling GIS functionality within standard PDF files. This format is designed for the efficient distribution and communication of rich spatial data to anyone who needs to view, review, verify, update, or print it. Because GeoPDF files are highly compressed and encapsulated, they are smaller, faster, and easier to transmit than GIS data sets, without the overhead associated with typical GIS spatial data sets (or the management of database tables, external links, and dependencies). Using the GeoPDF format, publishers of spatial data can select the specific spatial data they want recipients to see and can publish GIS source files into a single GeoPDF file.
GeoPDF files are not a replacement for native GIS formats. GIS professionals still need the original files for editing or updating spatial data. GeoPDF files enable non-GIS professionals, field technicians, business executives, and their colleagues to utilize rich spatial information. Users can view and print GeoPDF files with the free and ubiquitous Adobe Reader ,and they can do more with the data using a free plug-in called TerraGo Toolbar. Users do not have to install this plug-in to view GeoPDF files.
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| U S Geological Survey |
| 2014 |
About GeoPDF data files
PDF (Portable Document Format) digital files are now available for US Geological Survey topographic quadrangle maps. Each file is essentially a scan of a topographic map with the added feature of being georegistered. The files can be used as a PDF file, enabling users to view topo maps onscreen.
The GeoPDF format is an extension to Adobe's PDF 1.3 and higher versions enabling GIS functionality within standard PDF files. This format is designed for the efficient distribution and communication of rich spatial data to anyone who needs to view, review, verify, update, or print it. Because GeoPDF files are highly compressed and encapsulated, they are smaller, faster, and easier to transmit than GIS data sets, without the overhead associated with typical GIS spatial data sets (or the management of database tables, external links, and dependencies). Using the GeoPDF format, publishers of spatial data can select the specific spatial data they want recipients to see and can publish GIS source files into a single GeoPDF file.
GeoPDF files are not a replacement for native GIS formats. GIS professionals still need the original files for editing or updating spatial data. GeoPDF files enable non-GIS professionals, field technicians, business executives, and their colleagues to utilize rich spatial information. Users can view and print GeoPDF files with the free and ubiquitous Adobe Reader ,and they can do more with the data using a free plug-in called TerraGo Toolbar. Users do not have to install this plug-in to view GeoPDF files.
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| U S Geological Survey |
| 2011 |
The USGS Historical Quadrangle Scanning Project (HQSP) is scanning all scales and all editions of topographic maps published by the U.S. Geological Survey (USGS) since the inception of the topographic mapping program in 1884. This map is provided as a general purpose map in GeoPDF for users who are not GIS experts.
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| U S Geological Survey |
| 2011 |
About GeoPDF data files
PDF (Portable Document Format) digital files are now available for US Geological Survey topographic quadrangle maps. Each file is essentially a scan of a topographic map with the added feature of being georegistered. The files can be used as a PDF file, enabling users to view topo maps onscreen.
The GeoPDF format is an extension to Adobe's PDF 1.3 and higher versions enabling GIS functionality within standard PDF files. This format is designed for the efficient distribution and communication of rich spatial data to anyone who needs to view, review, verify, update, or print it. Because GeoPDF files are highly compressed and encapsulated, they are smaller, faster, and easier to transmit than GIS data sets, without the overhead associated with typical GIS spatial data sets (or the management of database tables, external links, and dependencies). Using the GeoPDF format, publishers of spatial data can select the specific spatial data they want recipients to see and can publish GIS source files into a single GeoPDF file.
GeoPDF files are not a replacement for native GIS formats. GIS professionals still need the original files for editing or updating spatial data. GeoPDF files enable non-GIS professionals, field technicians, business executives, and their colleagues to utilize rich spatial information. Users can view and print GeoPDF files with the free and ubiquitous Adobe Reader ,and they can do more with the data using a free plug-in called TerraGo Toolbar. Users do not have to install this plug-in to view GeoPDF files.
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| U S Geological Survey |
| 2011 |
The USGS Historical Quadrangle Scanning Project (HQSP) is scanning all scales and all editions of topographic maps published by the U.S. Geological Survey (USGS) since the inception of the topographic mapping program in 1884. This map is provided as a general purpose map in GeoPDF for users who are not GIS experts.
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| U S Geological Survey |
| 2011 |
About GeoPDF data files
PDF (Portable Document Format) digital files are now available for US Geological Survey topographic quadrangle maps. Each file is essentially a scan of a topographic map with the added feature of being georegistered. The files can be used as a PDF file, enabling users to view topo maps onscreen.
The GeoPDF format is an extension to Adobe's PDF 1.3 and higher versions enabling GIS functionality within standard PDF files. This format is designed for the efficient distribution and communication of rich spatial data to anyone who needs to view, review, verify, update, or print it. Because GeoPDF files are highly compressed and encapsulated, they are smaller, faster, and easier to transmit than GIS data sets, without the overhead associated with typical GIS spatial data sets (or the management of database tables, external links, and dependencies). Using the GeoPDF format, publishers of spatial data can select the specific spatial data they want recipients to see and can publish GIS source files into a single GeoPDF file.
GeoPDF files are not a replacement for native GIS formats. GIS professionals still need the original files for editing or updating spatial data. GeoPDF files enable non-GIS professionals, field technicians, business executives, and their colleagues to utilize rich spatial information. Users can view and print GeoPDF files with the free and ubiquitous Adobe Reader ,and they can do more with the data using a free plug-in called TerraGo Toolbar. Users do not have to install this plug-in to view GeoPDF files.
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| U S Geological Survey |
| 2011 |
The USGS Historical Quadrangle Scanning Project (HQSP) is scanning all scales and all editions of topographic maps published by the U.S. Geological Survey (USGS) since the inception of the topographic mapping program in 1884. This map is provided as a general purpose map in GeoPDF for users who are not GIS experts.
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| U S Geological Survey |
| 2011 |
About GeoPDF data files
PDF (Portable Document Format) digital files are now available for US Geological Survey topographic quadrangle maps. Each file is essentially a scan of a topographic map with the added feature of being georegistered. The files can be used as a PDF file, enabling users to view topo maps onscreen.
The GeoPDF format is an extension to Adobe's PDF 1.3 and higher versions enabling GIS functionality within standard PDF files. This format is designed for the efficient distribution and communication of rich spatial data to anyone who needs to view, review, verify, update, or print it. Because GeoPDF files are highly compressed and encapsulated, they are smaller, faster, and easier to transmit than GIS data sets, without the overhead associated with typical GIS spatial data sets (or the management of database tables, external links, and dependencies). Using the GeoPDF format, publishers of spatial data can select the specific spatial data they want recipients to see and can publish GIS source files into a single GeoPDF file.
GeoPDF files are not a replacement for native GIS formats. GIS professionals still need the original files for editing or updating spatial data. GeoPDF files enable non-GIS professionals, field technicians, business executives, and their colleagues to utilize rich spatial information. Users can view and print GeoPDF files with the free and ubiquitous Adobe Reader ,and they can do more with the data using a free plug-in called TerraGo Toolbar. Users do not have to install this plug-in to view GeoPDF files.
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| U S Geological Survey |
| 2014 |
About GeoPDF data files
PDF (Portable Document Format) digital files are now available for US Geological Survey topographic quadrangle maps. Each file is essentially a scan of a topographic map with the added feature of being georegistered. The files can be used as a PDF file, enabling users to view topo maps onscreen.
The GeoPDF format is an extension to Adobe's PDF 1.3 and higher versions enabling GIS functionality within standard PDF files. This format is designed for the efficient distribution and communication of rich spatial data to anyone who needs to view, review, verify, update, or print it. Because GeoPDF files are highly compressed and encapsulated, they are smaller, faster, and easier to transmit than GIS data sets, without the overhead associated with typical GIS spatial data sets (or the management of database tables, external links, and dependencies). Using the GeoPDF format, publishers of spatial data can select the specific spatial data they want recipients to see and can publish GIS source files into a single GeoPDF file.
GeoPDF files are not a replacement for native GIS formats. GIS professionals still need the original files for editing or updating spatial data. GeoPDF files enable non-GIS professionals, field technicians, business executives, and their colleagues to utilize rich spatial information. Users can view and print GeoPDF files with the free and ubiquitous Adobe Reader ,and they can do more with the data using a free plug-in called TerraGo Toolbar. Users do not have to install this plug-in to view GeoPDF files.
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| U S Geological Survey |
| 2020 |
About GeoPDF data files
PDF (Portable Document Format) digital files are now available for US Geological Survey topographic quadrangle maps. Each file is essentially a scan of a topographic map with the added feature of being georegistered. The files can be used as a PDF file, enabling users to view topo maps onscreen.
The GeoPDF format is an extension to Adobe's PDF 1.3 and higher versions enabling GIS functionality within standard PDF files. This format is designed for the efficient distribution and communication of rich spatial data to anyone who needs to view, review, verify, update, or print it. Because GeoPDF files are highly compressed and encapsulated, they are smaller, faster, and easier to transmit than GIS data sets, without the overhead associated with typical GIS spatial data sets (or the management of database tables, external links, and dependencies). Using the GeoPDF format, publishers of spatial data can select the specific spatial data they want recipients to see and can publish GIS source files into a single GeoPDF file.
GeoPDF files are not a replacement for native GIS formats. GIS professionals still need the original files for editing or updating spatial data. GeoPDF files enable non-GIS professionals, field technicians, business executives, and their colleagues to utilize rich spatial information. Users can view and print GeoPDF files with the free and ubiquitous Adobe Reader ,and they can do more with the data using a free plug-in called TerraGo Toolbar. Users do not have to install this plug-in to view GeoPDF files.
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| U S Geological Survey |
| 2011 |
The USGS Historical Quadrangle Scanning Project (HQSP) is scanning all scales and all editions of topographic maps published by the U.S. Geological Survey (USGS) since the inception of the topographic mapping program in 1884. This map is provided as a general purpose map in GeoPDF for users who are not GIS experts.
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| U S Geological Survey |
| 2011 |
GeoPDF 30 x 60 Minute Quadrangle Map for Pennsylvania
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| U S Geological Survey |
| 2011 |
About GeoPDF data files
PDF (Portable Document Format) digital files are now available for US Geological Survey topographic quadrangle maps. Each file is essentially a scan of a topographic map with the added feature of being georegistered. The files can be used as a PDF file, enabling users to view topo maps onscreen.
The GeoPDF format is an extension to Adobe's PDF 1.3 and higher versions enabling GIS functionality within standard PDF files. This format is designed for the efficient distribution and communication of rich spatial data to anyone who needs to view, review, verify, update, or print it. Because GeoPDF files are highly compressed and encapsulated, they are smaller, faster, and easier to transmit than GIS data sets, without the overhead associated with typical GIS spatial data sets (or the management of database tables, external links, and dependencies). Using the GeoPDF format, publishers of spatial data can select the specific spatial data they want recipients to see and can publish GIS source files into a single GeoPDF file.
GeoPDF files are not a replacement for native GIS formats. GIS professionals still need the original files for editing or updating spatial data. GeoPDF files enable non-GIS professionals, field technicians, business executives, and their colleagues to utilize rich spatial information. Users can view and print GeoPDF files with the free and ubiquitous Adobe Reader ,and they can do more with the data using a free plug-in called TerraGo Toolbar. Users do not have to install this plug-in to view GeoPDF files.
Metadata
|
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| U S Geological Survey |
| 2011 |
The USGS Historical Quadrangle Scanning Project (HQSP) is scanning all scales and all editions of topographic maps published by the U.S. Geological Survey (USGS) since the inception of the topographic mapping program in 1884. This map is provided as a general purpose map in GeoPDF for users who are not GIS experts.
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| U S Geological Survey |
| 2011 |
The USGS Historical Quadrangle Scanning Project (HQSP) is scanning all scales and all editions of topographic maps published by the U.S. Geological Survey (USGS) since the inception of the topographic mapping program in 1884. This map is provided as a general purpose map in GeoPDF for users who are not GIS experts.
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| U S Geological Survey |
| 2011 |
About GeoPDF data files
PDF (Portable Document Format) digital files are now available for US Geological Survey topographic quadrangle maps. Each file is essentially a scan of a topographic map with the added feature of being georegistered. The files can be used as a PDF file, enabling users to view topo maps onscreen.
The GeoPDF format is an extension to Adobe's PDF 1.3 and higher versions enabling GIS functionality within standard PDF files. This format is designed for the efficient distribution and communication of rich spatial data to anyone who needs to view, review, verify, update, or print it. Because GeoPDF files are highly compressed and encapsulated, they are smaller, faster, and easier to transmit than GIS data sets, without the overhead associated with typical GIS spatial data sets (or the management of database tables, external links, and dependencies). Using the GeoPDF format, publishers of spatial data can select the specific spatial data they want recipients to see and can publish GIS source files into a single GeoPDF file.
GeoPDF files are not a replacement for native GIS formats. GIS professionals still need the original files for editing or updating spatial data. GeoPDF files enable non-GIS professionals, field technicians, business executives, and their colleagues to utilize rich spatial information. Users can view and print GeoPDF files with the free and ubiquitous Adobe Reader ,and they can do more with the data using a free plug-in called TerraGo Toolbar. Users do not have to install this plug-in to view GeoPDF files.
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| U S Geological Survey |
| 2005 |
This data set consists of 0.3-meter pixel resolution (approximately 1-foot), natural color orthoimages covering Mercer County, Pennsylvania. An orthoimage is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation have been mathematically removed. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. The design accuracy is estimated not to exceed 3-meter diagonal RMSE (2.12m RMSE in X or Y).
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| U S Geological Survey |
| 2005 |
This data set consists of 0.3-meter pixel resolution (approximately 1-foot), natural color orthoimages covering Mercer County, Pennsylvania. An orthoimage is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation have been mathematically removed. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. The design accuracy is estimated not to exceed 3-meter diagonal RMSE (2.12m RMSE in X or Y).
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| U S Geological Survey |
| 2005 |
This data set consists of 0.3-meter pixel resolution (approximately 1-foot), natural color orthoimages covering the Pittsburgh, PA Urban Area (Allegheny and Beaver Counties. An orthoimage is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation have been mathematically removed. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. The design accuracy is estimated not to exceed 3-meter diagonal RMSE (2.12m RMSE in X or Y).
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| U S Geological Survey |
| 2005 |
Tile Index - This data set consists of 0.3-meter pixel resolution (approximately 1-foot), natural color orthoimages covering the Pittsburgh, PA Urban Area (Allegheny and Beaver Counties. An orthoimage is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation have been mathematically removed. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. The design accuracy is estimated not to exceed 3-meter diagonal RMSE (2.12m RMSE in X or Y).
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| U S Geological Survey |
| 2011 |
"This task order consists of digital orthophoto production covering the Pittsburgh Area, Pennsylvania." An orthoimage is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation have been mathematically removed. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. There is no image overlap between adjacent files.
Data received at Earth Resources Observation and Science Center (EROS) were verified as:
Projection: NAD_1983_UTM_Zone_17N
Resolution: 0.3000 m
Type: Natural Color
and resampled to align to the U.S. National Grid (USNG) using The National Map. The naming convention is based on the U.S. National Grid (USNG), taking the coordinates of the SW corner of the orthoimage. The metadata were imported and updated for display through The National Map at http://nationalmap.gov/viewer.html Chip-level metadata are provided in HTML and XML format. Data were compressed utilizing IAS software. The compression was JPEG2000 Lossy Compressed. The file format created was .jp2.
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| U S Geological Survey |
| 2011 |
TILE INDEX -"This task order consists of digital orthophoto production covering the Pittsburgh Area, Pennsylvania." An orthoimage is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation have been mathematically removed. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. There is no image overlap between adjacent files.
Data received at Earth Resources Observation and Science Center (EROS) were verified as:
Projection: NAD_1983_UTM_Zone_17N
Resolution: 0.3000 m
Type: Natural Color
and resampled to align to the U.S. National Grid (USNG) using The National Map. The naming convention is based on the U.S. National Grid (USNG), taking the coordinates of the SW corner of the orthoimage. The metadata were imported and updated for display through The National Map at http://nationalmap.gov/viewer.html Chip-level metadata are provided in HTML and XML format. Data were compressed utilizing IAS software. The compression was JPEG2000 Lossy Compressed. The file format created was .jp2.
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| U S Geological Survey |
| 2012 |
"This task order consists of digital orthophoto production covering the Pittsburgh Area, Pennsylvania." An orthoimage is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation have been mathematically removed. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. There is no image overlap between adjacent files.
Data received at Earth Resources Observation and Science Center (EROS) were verified as:
Projection: NAD_1983_UTM_Zone_17N
Resolution: 0.3000 m
Type: Natural Color
and resampled to align to the U.S. National Grid (USNG) using The National Map. The naming convention is based on the U.S. National Grid (USNG), taking the coordinates of the SW corner of the orthoimage. The metadata were imported and updated for display through The National Map at http://nationalmap.gov/viewer.html Chip-level metadata are provided in HTML and XML format. Data were compressed utilizing IAS software. The compression was JPEG2000 Lossy Compressed. The file format created was .jp2.
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| U S Geological Survey |
| 2012 |
TILE INDEX -"This task order consists of digital orthophoto production covering the Pittsburgh Area, Pennsylvania." An orthoimage is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation have been mathematically removed. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. There is no image overlap between adjacent files.
Data received at Earth Resources Observation and Science Center (EROS) were verified as:
Projection: NAD_1983_UTM_Zone_17N
Resolution: 0.3000 m
Type: Natural Color
and resampled to align to the U.S. National Grid (USNG) using The National Map. The naming convention is based on the U.S. National Grid (USNG), taking the coordinates of the SW corner of the orthoimage. The metadata were imported and updated for display through The National Map at http://nationalmap.gov/viewer.html Chip-level metadata are provided in HTML and XML format. Data were compressed utilizing IAS software. The compression was JPEG2000 Lossy Compressed. The file format created was .jp2.
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| U S Geological Survey |
| 2009 |
One foot GSD, natural color (RGB), 8-bit digital orthophotography for the City of New Castle, Pennsylvania. The imagery was collected using the Leica Geosystems ADS40 sensor between October 19th and November 2nd, 2009 at an average altitude of 9,600 feet above ground level. The National Elevation Dataset (NED) was used as vertical control. Airborne GPS/IMU data was used as horizontal control. The orthophotography is georeferenced to UTM Zone 17 North, meter units, NAD83, NAVD88. The imagery was produced by Pixxures, Inc. under contract for DigitalGlobe, Inc." An orthoimage is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation have been mathematically removed. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. There is no image overlap between adjacent files. Data received at EROS as: Projection: NAD_1983_UTM_Zone_17N Resolution: 0.3 meter Type: Natural Color and chipped to the Standard Product as: Standard Product Projection: NAD_1983_UTM_Zone_17N Standard Product Resolution: 0.3000 m Rows: 5,000 Columns: 5,000.
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| U S Geological Survey |
| 2009 |
TILE INDEX - One foot GSD, natural color (RGB), 8-bit digital orthophotography for the City of New Castle, Pennsylvania. The imagery was collected using the Leica Geosystems ADS40 sensor between October 19th and November 2nd, 2009 at an average altitude of 9,600 feet above ground level. The National Elevation Dataset (NED) was used as vertical control. Airborne GPS/IMU data was used as horizontal control. The orthophotography is georeferenced to UTM Zone 17 North, meter units, NAD83, NAVD88. The imagery was produced by Pixxures, Inc. under contract for DigitalGlobe, Inc." An orthoimage is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation have been mathematically removed. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. There is no image overlap between adjacent files. Data received at EROS as: Projection: NAD_1983_UTM_Zone_17N Resolution: 0.3 meter Type: Natural Color and chipped to the Standard Product as: Standard Product Projection: NAD_1983_UTM_Zone_17N Standard Product Resolution: 0.3000 m Rows: 5,000 Columns: 5,000.
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| U S Geological Survey |
| 2019 |
These lidar data are processed Classified LAS 1.4 files, formatted to 1792 individual 2500 ft x 2500 ft tiles in NAD83(2011) State Plane Pennsylvania North FIPS 3701 Ft US. The vertical datum of NAVD88 Geoid12B Ft US; used to create intensity images, 3D breaklines and hydro-flattened DEMs as necessary.Geographic Extent: This task order requires lidar data to be acquired over an AOI surrounding Wilkes-Barre, PA (+/- 401.5 square miles) Dataset Description: WVSA, PA – 2017 Impervious Surface project called for the Planning, Acquisition, processing and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.35 meter. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base Lidar Specification, Version 1.2. The data was developed based on a horizontal projection/datum of NAD83(2011) State Plane Pennsylvania North FIPS3701 Ft US. The vertical datum of NAVD88 Geoid12B Ft US. Lidar data was delivered as flightline-extent unclassified LAS swaths, as processed Classified LAS 1.4 files, formatted to 1792 individual 2500 ft x 2500 ft tiles, as tiled Intensity Imagery, and as tiled bare earth DEMs; all tiled to the same 2500 ft x 2500 ft schema.Ground Conditions: Lidar was collected between November 23, 2017 and December 8, 2017 by Woolpert, while no snow was on the ground and rivers were at or below normal levels. In order to post process the lidar data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Woolpert established 35 ground control points that were used to calibrate the lidar to known ground locations established throughout the project area. Additional independent accuracy checkpoints were collected (35 NVA points and 23 VVA points) and used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data
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| U S Geological Survey |
| 2022 |
Geospatial data includes structures and other selected map features. It is a general purpose dataset for users who are not GIS experts. The geospatial data are from selected National Map data holdings and other government sources.
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| U S Geological Survey |
| 2022 |
Layers of geospatial data include roads, airports, trails, and railroads.
The geospatial data are from selected National Map data holdings and other government sources.
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| U S Geological Survey |
| 2019 |
Breakline data is used to hydroflatten the DEMs created for the WVSA, PA 2017 Lidar project project. Breaklines are reviewed against lidar intensity imagery to verify completeness of capture. The compilation procedure included use of lidar intensity, bare earth surface model, point cloud data, and open source imagery in an effort to manually compile hydrologic features in a 2-d environment. Following the compilation phase, a separate process was used to adjust the breakline data to best match the water level at the time of the lidar collection. Any ponds and/or lakes were adjusted to be at or just below the bank and to be at a constant elevation. Any streams were adjusted to be at or just below the bank and to be monotonic. Manual QAQC and peer-based QC review was performed on all delineated data to ensure horizontal placement quality and on all adjusted data to ensure vertical placement quality. Bridge breaklines were also compiled in efforts to generate an accurate DEM product. The final hydrologic and bridge breakline product was delivered in ESRI geodatabase format and was also used in the processing of the DEM deliverableGeographic Extent: This task order requires lidar data to be acquired over an AOI surrounding Wilkes-Barre, PA (+/- 401.5 square miles) Dataset Description: WVSA, PA – 2017 Impervious Surface project called for the Planning, Acquisition, processing and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.35 meter. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base Lidar Specification, Version 1.2. The data was developed based on a horizontal projection/datum of NAD83(2011) State Plane Pennsylvania North FIPS3701 Ft US. The vertical datum of NAVD88 Geoid12B Ft US. Lidar data was delivered as flightline-extent unclassified LAS swaths, as processed Classified LAS 1.4 files, formatted to 1792 individual 2500 ft x 2500 ft tiles, as tiled Intensity Imagery, and as tiled bare earth DEMs; all tiled to the same 2500 ft x 2500 ft schema.Ground Conditions: Lidar was collected between November 23, 2017 and December 8, 2017 by Woolpert, while no snow was on the ground and rivers were at or below normal levels. In order to post process the lidar data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Woolpert established 35 ground control points that were used to calibrate the lidar to known ground locations established throughout the project area. Additional independent accuracy checkpoints were collected (35 NVA points and 23 VVA points) and used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2019 |
These are Digital Elevation Model (DEM) data for WVSA PA 2017 Impervious Surface Lidar task as part of the required deliverables for WVSA PA 2017 Impervious Surface project. Class 2 (ground) lidar points in conjunction with the hydro breaklines and bridge breaklines were used to create a 1 foot hydro-flattened Raster DEM.Geographic Extent: This task order requires lidar data to be acquired over an AOI surrounding Wilkes-Barre, PA (+/- 401.5 square miles) Dataset Description: WVSA, PA – 2017 Impervious Surface project called for the Planning, Acquisition, processing and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.35 meter. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base Lidar Specification, Version 1.2. The data was developed based on a horizontal projection/datum of NAD83(2011) State Plane Pennsylvania North FIPS3701 Ft US. The vertical datum of NAVD88 Geoid12B Ft US. Lidar data was delivered as flightline-extent unclassified LAS swaths, as processed Classified LAS 1.4 files, formatted to 1792 individual 2500 ft x 2500 ft tiles, as tiled Intensity Imagery, and as tiled bare earth DEMs; all tiled to the same 2500 ft x 2500 ft schema.Ground Conditions: Lidar was collected between November 23, 2017 and December 8, 2017 by Woolpert, while no snow was on the ground and rivers were at or below normal levels. In order to post process the lidar data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Woolpert established 35 ground control points that were used to calibrate the lidar to known ground locations established throughout the project area. Additional independent accuracy checkpoints were collected (35 NVA points and 23 VVA points) and used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2019 |
These are Digital Elevation Model (DEM) data for WVSA PA 2017 Impervious Surface Lidar task as part of the required deliverables for WVSA PA 2017 Impervious Surface project. Class 2 (ground) lidar points in conjunction with the hydro breaklines and bridge breaklines were used to create a 1 foot hydro-flattened Raster DEM.Geographic Extent: This task order requires lidar data to be acquired over an AOI surrounding Wilkes-Barre, PA (+/- 401.5 square miles) Dataset Description: WVSA, PA – 2017 Impervious Surface project called for the Planning, Acquisition, processing and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.35 meter. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base Lidar Specification, Version 1.2. The data was developed based on a horizontal projection/datum of NAD83(2011) State Plane Pennsylvania North FIPS3701 Ft US. The vertical datum of NAVD88 Geoid12B Ft US. Lidar data was delivered as flightline-extent unclassified LAS swaths, as processed Classified LAS 1.4 files, formatted to 1792 individual 2500 ft x 2500 ft tiles, as tiled Intensity Imagery, and as tiled bare earth DEMs; all tiled to the same 2500 ft x 2500 ft schema.Ground Conditions: Lidar was collected between November 23, 2017 and December 8, 2017 by Woolpert, while no snow was on the ground and rivers were at or below normal levels. In order to post process the lidar data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Woolpert established 35 ground control points that were used to calibrate the lidar to known ground locations established throughout the project area. Additional independent accuracy checkpoints were collected (35 NVA points and 23 VVA points) and used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2016 |
Allentown, Pennsylvania, covering approximately 20 square miles in eastern Pennsylvania. Dataset Description: Allentown, Pennsylvania 2016 QL1 LiDAR project called for the planning, acquisition, processing, and production of products derivative of LIDAR data to be collected at a nominal pulse spacing (NPS) of 0.35 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LIDAR Specification, Version 1.2. The data was developed based on a horizontal projection/datum of NAD83 (2011) State Plane Pennsylvania South Zone, US survey feet and vertical datum of NAVD1988 (GEOID 12B), US survey feet. LiDAR data was delivered in RAW flight line swath format, processed to create Classified LAS 1.4 Files formatted to 129 individual 2,500-foot X 2,500-foot tiles, 1-foot hydro-flattened bare-earth raster DEMs in ERDAS .IMG format and intensity images in GeoTIFF format, tiled to the same 2,500-foot X 2,500-foot tile schema. Hydro-flattened breaklines were produced in Esri file geodatabase format. A mosaic of the hydro-flattened bare-earth raster DEMs was produced in ERDAS .IMG format. Ground Conditions: LiDAR was collected in spring of 2016, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications, A total of 18 calibration control points in order to calibrate the LIDAR to known ground locations established throughout the project area. The accuracy of the data was checked with 20 NVA points and 5 VVA points (25 total QC checkpoints).
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| U S Geological Survey |
| 2016 |
Allentown, Pennsylvania, covering approximately 20 square miles in eastern Pennsylvania. Dataset Description: Allentown, Pennsylvania 2016 QL1 LiDAR project called for the planning, acquisition, processing, and production of products derivative of LIDAR data to be collected at a nominal pulse spacing (NPS) of 0.35 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LIDAR Specification, Version 1.2. The data was developed based on a horizontal projection/datum of NAD83 (2011) State Plane Pennsylvania South Zone, US survey feet and vertical datum of NAVD1988 (GEOID 12B), US survey feet. LiDAR data was delivered in RAW flight line swath format, processed to create Classified LAS 1.4 Files formatted to 129 individual 2,500-foot X 2,500-foot tiles, 1-foot hydro-flattened bare-earth raster DEMs in ERDAS .IMG format and intensity images in GeoTIFF format, tiled to the same 2,500-foot X 2,500-foot tile schema. Hydro-flattened breaklines were produced in Esri file geodatabase format. A mosaic of the hydro-flattened bare-earth raster DEMs was produced in ERDAS .IMG format. Ground Conditions: LiDAR was collected in spring of 2016, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications, A total of 18 calibration control points in order to calibrate the LIDAR to known ground locations established throughout the project area. The accuracy of the data was checked with 20 NVA points and 5 VVA points (25 total QC checkpoints).
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| U S Geological Survey |
| 2016 |
Allentown, Pennsylvania, covering approximately 20 square miles in eastern Pennsylvania. Dataset Description: Allentown, Pennsylvania 2016 QL1 LiDAR project called for the planning, acquisition, processing, and production of products derivative of LIDAR data to be collected at a nominal pulse spacing (NPS) of 0.35 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LIDAR Specification, Version 1.2. The data was developed based on a horizontal projection/datum of NAD83 (2011) State Plane Pennsylvania South Zone, US survey feet and vertical datum of NAVD1988 (GEOID 12B), US survey feet. LiDAR data was delivered in RAW flight line swath format, processed to create Classified LAS 1.4 Files formatted to 129 individual 2,500-foot X 2,500-foot tiles, 1-foot hydro-flattened bare-earth raster DEMs in ERDAS .IMG format and intensity images in GeoTIFF format, tiled to the same 2,500-foot X 2,500-foot tile schema. Hydro-flattened breaklines were produced in Esri file geodatabase format. A mosaic of the hydro-flattened bare-earth raster DEMs was produced in ERDAS .IMG format. Ground Conditions: LiDAR was collected in spring of 2016, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications, A total of 18 calibration control points in order to calibrate the LIDAR to known ground locations established throughout the project area. The accuracy of the data was checked with 20 NVA points and 5 VVA points (25 total QC checkpoints).
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| U S Geological Survey |
| 2016 |
Allentown, Pennsylvania, covering approximately 20 square miles in eastern Pennsylvania. Dataset Description: Allentown, Pennsylvania 2016 QL1 LiDAR project called for the planning, acquisition, processing, and production of products derivative of LIDAR data to be collected at a nominal pulse spacing (NPS) of 0.35 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LIDAR Specification, Version 1.2. The data was developed based on a horizontal projection/datum of NAD83 (2011) State Plane Pennsylvania South Zone, US survey feet and vertical datum of NAVD1988 (GEOID 12B), US survey feet. LiDAR data was delivered in RAW flight line swath format, processed to create Classified LAS 1.4 Files formatted to 129 individual 2,500-foot X 2,500-foot tiles, 1-foot hydro-flattened bare-earth raster DEMs in ERDAS .IMG format and intensity images in GeoTIFF format, tiled to the same 2,500-foot X 2,500-foot tile schema. Hydro-flattened breaklines were produced in Esri file geodatabase format. A mosaic of the hydro-flattened bare-earth raster DEMs was produced in ERDAS .IMG format. Ground Conditions: LiDAR was collected in spring of 2016, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications, A total of 18 calibration control points in order to calibrate the LIDAR to known ground locations established throughout the project area. The accuracy of the data was checked with 20 NVA points and 5 VVA points (25 total QC checkpoints).
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| U S Geological Survey |
| 2016 |
Allentown, Pennsylvania, covering approximately 20 square miles in eastern Pennsylvania. Dataset Description: Allentown, Pennsylvania 2016 QL1 LiDAR project called for the planning, acquisition, processing, and production of products derivative of LIDAR data to be collected at a nominal pulse spacing (NPS) of 0.35 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LIDAR Specification, Version 1.2. The data was developed based on a horizontal projection/datum of NAD83 (2011) State Plane Pennsylvania South Zone, US survey feet and vertical datum of NAVD1988 (GEOID 12B), US survey feet. LiDAR data was delivered in RAW flight line swath format, processed to create Classified LAS 1.4 Files formatted to 129 individual 2,500-foot X 2,500-foot tiles, 1-foot hydro-flattened bare-earth raster DEMs in ERDAS .IMG format and intensity images in GeoTIFF format, tiled to the same 2,500-foot X 2,500-foot tile schema. Hydro-flattened breaklines were produced in Esri file geodatabase format. A mosaic of the hydro-flattened bare-earth raster DEMs was produced in ERDAS .IMG format. Ground Conditions: LiDAR was collected in spring of 2016, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications, A total of 18 calibration control points in order to calibrate the LIDAR to known ground locations established throughout the project area. The accuracy of the data was checked with 20 NVA points and 5 VVA points (25 total QC checkpoints).
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| U S Geological Survey |
| 2016 |
Allentown, Pennsylvania, covering approximately 20 square miles in eastern Pennsylvania. Dataset Description: Allentown, Pennsylvania 2016 QL1 LiDAR project called for the planning, acquisition, processing, and production of products derivative of LIDAR data to be collected at a nominal pulse spacing (NPS) of 0.35 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LIDAR Specification, Version 1.2. The data was developed based on a horizontal projection/datum of NAD83 (2011) State Plane Pennsylvania South Zone, US survey feet and vertical datum of NAVD1988 (GEOID 12B), US survey feet. LiDAR data was delivered in RAW flight line swath format, processed to create Classified LAS 1.4 Files formatted to 129 individual 2,500-foot X 2,500-foot tiles, 1-foot hydro-flattened bare-earth raster DEMs in ERDAS .IMG format and intensity images in GeoTIFF format, tiled to the same 2,500-foot X 2,500-foot tile schema. Hydro-flattened breaklines were produced in Esri file geodatabase format. A mosaic of the hydro-flattened bare-earth raster DEMs was produced in ERDAS .IMG format. Ground Conditions: LiDAR was collected in spring of 2016, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications, A total of 18 calibration control points in order to calibrate the LIDAR to known ground locations established throughout the project area. The accuracy of the data was checked with 20 NVA points and 5 VVA points (25 total QC checkpoints).
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| U S Geological Survey |
| 2016 |
Allentown, Pennsylvania, covering approximately 20 square miles in eastern Pennsylvania. Dataset Description: Allentown, Pennsylvania 2016 QL1 LiDAR project called for the planning, acquisition, processing, and production of products derivative of LIDAR data to be collected at a nominal pulse spacing (NPS) of 0.35 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LIDAR Specification, Version 1.2. The data was developed based on a horizontal projection/datum of NAD83 (2011) State Plane Pennsylvania South Zone, US survey feet and vertical datum of NAVD1988 (GEOID 12B), US survey feet. LiDAR data was delivered in RAW flight line swath format, processed to create Classified LAS 1.4 Files formatted to 129 individual 2,500-foot X 2,500-foot tiles, 1-foot hydro-flattened bare-earth raster DEMs in ERDAS .IMG format and intensity images in GeoTIFF format, tiled to the same 2,500-foot X 2,500-foot tile schema. Hydro-flattened breaklines were produced in Esri file geodatabase format. A mosaic of the hydro-flattened bare-earth raster DEMs was produced in ERDAS .IMG format. Ground Conditions: LiDAR was collected in spring of 2016, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications, A total of 18 calibration control points in order to calibrate the LIDAR to known ground locations established throughout the project area. The accuracy of the data was checked with 20 NVA points and 5 VVA points (25 total QC checkpoints).
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| U S Geological Survey |
| 2016 |
Tile Indexes - Allentown, Pennsylvania, covering approximately 20 square miles in eastern Pennsylvania. Dataset Description: Allentown, Pennsylvania 2016 QL1 LiDAR project called for the planning, acquisition, processing, and production of products derivative of LIDAR data to be collected at a nominal pulse spacing (NPS) of 0.35 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LIDAR Specification, Version 1.2. The data was developed based on a horizontal projection/datum of NAD83 (2011) State Plane Pennsylvania South Zone, US survey feet and vertical datum of NAVD1988 (GEOID 12B), US survey feet. LiDAR data was delivered in RAW flight line swath format, processed to create Classified LAS 1.4 Files formatted to 129 individual 2,500-foot X 2,500-foot tiles, 1-foot hydro-flattened bare-earth raster DEMs in ERDAS .IMG format and intensity images in GeoTIFF format, tiled to the same 2,500-foot X 2,500-foot tile schema. Hydro-flattened breaklines were produced in Esri file geodatabase format. A mosaic of the hydro-flattened bare-earth raster DEMs was produced in ERDAS .IMG format. Ground Conditions: LiDAR was collected in spring of 2016, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications, A total of 18 calibration control points in order to calibrate the LIDAR to known ground locations established throughout the project area. The accuracy of the data was checked with 20 NVA points and 5 VVA points (25 total QC checkpoints).
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| U S Geological Survey |
| 2017 |
The South Central Pennsylvania 2017 QL2 LiDAR project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 1.2. The data were developed based on a horizontal projection/datum of NAD 1983 (2011), UTM Zone 18, meters and vertical datum of NAVD 1988 (GEOID 12B), meters. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 7,975 individual 1,500-meter x 1,500-meter tiles, as tiled intensity imagery, and as tiled bare earth DEMs; all tiled to the same 1,500-meter x 1,500-meter schema. Continuous breaklines were produced in Esri file geodatabase format. Ground Conditions: LiDAR was collected in fall 2017, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Quantum Spatial, Inc. utilized a total of 150 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 245 independent accuracy checkpoints, 142 in Bare Earth and Urban landcovers (142 NVA points), 103 in Tall Weeds categories (103 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2017 |
The South Central Pennsylvania 2017 QL2 LiDAR project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 1.2. The data were developed based on a horizontal projection/datum of NAD 1983 (2011), UTM Zone 18, meters and vertical datum of NAVD 1988 (GEOID 12B), meters. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 7,975 individual 1,500-meter x 1,500-meter tiles, as tiled intensity imagery, and as tiled bare earth DEMs; all tiled to the same 1,500-meter x 1,500-meter schema. Continuous breaklines were produced in Esri file geodatabase format. Ground Conditions: LiDAR was collected in fall 2017, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Quantum Spatial, Inc. utilized a total of 150 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 245 independent accuracy checkpoints, 142 in Bare Earth and Urban landcovers (142 NVA points), 103 in Tall Weeds categories (103 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2017 |
The South Central Pennsylvania 2017 QL2 LiDAR project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 1.2. The data were developed based on a horizontal projection/datum of NAD 1983 (2011), UTM Zone 18, meters and vertical datum of NAVD 1988 (GEOID 12B), meters. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 7,975 individual 1,500-meter x 1,500-meter tiles, as tiled intensity imagery, and as tiled bare earth DEMs; all tiled to the same 1,500-meter x 1,500-meter schema. Continuous breaklines were produced in Esri file geodatabase format. Ground Conditions: LiDAR was collected in fall 2017, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Quantum Spatial, Inc. utilized a total of 150 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 245 independent accuracy checkpoints, 142 in Bare Earth and Urban landcovers (142 NVA points), 103 in Tall Weeds categories (103 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2017 |
The South Central Pennsylvania 2017 QL2 LiDAR project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 1.2. The data were developed based on a horizontal projection/datum of NAD 1983 (2011), UTM Zone 18, meters and vertical datum of NAVD 1988 (GEOID 12B), meters. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 7,975 individual 1,500-meter x 1,500-meter tiles, as tiled intensity imagery, and as tiled bare earth DEMs; all tiled to the same 1,500-meter x 1,500-meter schema. Continuous breaklines were produced in Esri file geodatabase format. Ground Conditions: LiDAR was collected in fall 2017, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Quantum Spatial, Inc. utilized a total of 150 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 245 independent accuracy checkpoints, 142 in Bare Earth and Urban landcovers (142 NVA points), 103 in Tall Weeds categories (103 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2016 |
The Dauphin County, PA 2016 QL2 LiDAR project called for the planning, acquisition, processing and derivative products of LIDAR data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LIDAR Specification, Version 1.2. The data was developed based on a horizontal projection/datum of NAD83 (2011) State Plane Pennsylvania South Zone, US survey feet; NAVD1988 (Geoid 12B), US survey feet. LiDAR data was delivered in RAW flight line swath format, processed to create Classified LAS 1.4 Files formatted to 711 individual 5,000-foot x 5,000-foot tiles. Tile names use the following naming schema: "YYYYXXXXPAd" where YYYY is the first 3 characters of the tile's upper left corner Y-coordinate, XXXX - the first 4 characters of the tile's upper left corner X-coordinate, PA = Pennsylvania, and d = 'N' for North or 'S' for South. Corresponding 2.5-foot gridded hydro-flattened bare earth raster tiled DEM files and intensity image files were created using the same 5,000-foot x 5,000-foot schema. Hydro-flattened breaklines were produced in Esri file geodatabase format. Continuous 2-foot contours were produced in Esri file geodatabase format. Ground Conditions: LiDAR collection began in Spring 2016, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications, Quantum Spatial established a total of 84 control points (24 calibration control points and 60 QC checkpoints). These were used to calibrate the LIDAR to known ground locations established throughout the project area.
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| U S Geological Survey |
| 2016 |
The Dauphin County, PA 2016 QL2 LiDAR project called for the planning, acquisition, processing and derivative products of LIDAR data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LIDAR Specification, Version 1.2. The data was developed based on a horizontal projection/datum of NAD83 (2011) State Plane Pennsylvania South Zone, US survey feet; NAVD1988 (Geoid 12B), US survey feet. LiDAR data was delivered in RAW flight line swath format, processed to create Classified LAS 1.4 Files formatted to 711 individual 5,000-foot x 5,000-foot tiles. Tile names use the following naming schema: "YYYYXXXXPAd" where YYYY is the first 3 characters of the tile's upper left corner Y-coordinate, XXXX - the first 4 characters of the tile's upper left corner X-coordinate, PA = Pennsylvania, and d = 'N' for North or 'S' for South. Corresponding 2.5-foot gridded hydro-flattened bare earth raster tiled DEM files and intensity image files were created using the same 5,000-foot x 5,000-foot schema. Hydro-flattened breaklines were produced in Esri file geodatabase format. Continuous 2-foot contours were produced in Esri file geodatabase format. Ground Conditions: LiDAR collection began in Spring 2016, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications, Quantum Spatial established a total of 84 control points (24 calibration control points and 60 QC checkpoints). These were used to calibrate the LIDAR to known ground locations established throughout the project area.
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| U S Geological Survey |
| 2016 |
The Dauphin County, PA 2016 QL2 LiDAR project called for the planning, acquisition, processing and derivative products of LIDAR data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LIDAR Specification, Version 1.2. The data was developed based on a horizontal projection/datum of NAD83 (2011) State Plane Pennsylvania South Zone, US survey feet; NAVD1988 (Geoid 12B), US survey feet. LiDAR data was delivered in RAW flight line swath format, processed to create Classified LAS 1.4 Files formatted to 711 individual 5,000-foot x 5,000-foot tiles. Tile names use the following naming schema: "YYYYXXXXPAd" where YYYY is the first 3 characters of the tile's upper left corner Y-coordinate, XXXX - the first 4 characters of the tile's upper left corner X-coordinate, PA = Pennsylvania, and d = 'N' for North or 'S' for South. Corresponding 2.5-foot gridded hydro-flattened bare earth raster tiled DEM files and intensity image files were created using the same 5,000-foot x 5,000-foot schema. Hydro-flattened breaklines were produced in Esri file geodatabase format. Continuous 2-foot contours were produced in Esri file geodatabase format. Ground Conditions: LiDAR collection began in Spring 2016, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications, Quantum Spatial established a total of 84 control points (24 calibration control points and 60 QC checkpoints). These were used to calibrate the LIDAR to known ground locations established throughout the project area.
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| U S Geological Survey |
| 2016 |
The Dauphin County, PA 2016 QL2 LiDAR project called for the planning, acquisition, processing and derivative products of LIDAR data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LIDAR Specification, Version 1.2. The data was developed based on a horizontal projection/datum of NAD83 (2011) State Plane Pennsylvania South Zone, US survey feet; NAVD1988 (Geoid 12B), US survey feet. LiDAR data was delivered in RAW flight line swath format, processed to create Classified LAS 1.4 Files formatted to 711 individual 5,000-foot x 5,000-foot tiles. Tile names use the following naming schema: "YYYYXXXXPAd" where YYYY is the first 3 characters of the tile's upper left corner Y-coordinate, XXXX - the first 4 characters of the tile's upper left corner X-coordinate, PA = Pennsylvania, and d = 'N' for North or 'S' for South. Corresponding 2.5-foot gridded hydro-flattened bare earth raster tiled DEM files and intensity image files were created using the same 5,000-foot x 5,000-foot schema. Hydro-flattened breaklines were produced in Esri file geodatabase format. Continuous 2-foot contours were produced in Esri file geodatabase format. Ground Conditions: LiDAR collection began in Spring 2016, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications, Quantum Spatial established a total of 84 control points (24 calibration control points and 60 QC checkpoints). These were used to calibrate the LIDAR to known ground locations established throughout the project area.
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| U S Geological Survey |
| 2016 |
The Dauphin County, PA 2016 QL2 LiDAR project called for the planning, acquisition, processing and derivative products of LIDAR data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LIDAR Specification, Version 1.2. The data was developed based on a horizontal projection/datum of NAD83 (2011) State Plane Pennsylvania South Zone, US survey feet; NAVD1988 (Geoid 12B), US survey feet. LiDAR data was delivered in RAW flight line swath format, processed to create Classified LAS 1.4 Files formatted to 711 individual 5,000-foot x 5,000-foot tiles. Tile names use the following naming schema: "YYYYXXXXPAd" where YYYY is the first 3 characters of the tile's upper left corner Y-coordinate, XXXX - the first 4 characters of the tile's upper left corner X-coordinate, PA = Pennsylvania, and d = 'N' for North or 'S' for South. Corresponding 2.5-foot gridded hydro-flattened bare earth raster tiled DEM files and intensity image files were created using the same 5,000-foot x 5,000-foot schema. Hydro-flattened breaklines were produced in Esri file geodatabase format. Continuous 2-foot contours were produced in Esri file geodatabase format. Ground Conditions: LiDAR collection began in Spring 2016, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications, Quantum Spatial established a total of 84 control points (24 calibration control points and 60 QC checkpoints). These were used to calibrate the LIDAR to known ground locations established throughout the project area.
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| U S Geological Survey |
| 2016 |
The Dauphin County, PA 2016 QL2 LiDAR project called for the planning, acquisition, processing and derivative products of LIDAR data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LIDAR Specification, Version 1.2. The data was developed based on a horizontal projection/datum of NAD83 (2011) State Plane Pennsylvania South Zone, US survey feet; NAVD1988 (Geoid 12B), US survey feet. LiDAR data was delivered in RAW flight line swath format, processed to create Classified LAS 1.4 Files formatted to 711 individual 5,000-foot x 5,000-foot tiles. Tile names use the following naming schema: "YYYYXXXXPAd" where YYYY is the first 3 characters of the tile's upper left corner Y-coordinate, XXXX - the first 4 characters of the tile's upper left corner X-coordinate, PA = Pennsylvania, and d = 'N' for North or 'S' for South. Corresponding 2.5-foot gridded hydro-flattened bare earth raster tiled DEM files and intensity image files were created using the same 5,000-foot x 5,000-foot schema. Hydro-flattened breaklines were produced in Esri file geodatabase format. Continuous 2-foot contours were produced in Esri file geodatabase format. Ground Conditions: LiDAR collection began in Spring 2016, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications, Quantum Spatial established a total of 84 control points (24 calibration control points and 60 QC checkpoints). These were used to calibrate the LIDAR to known ground locations established throughout the project area.
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| U S Geological Survey |
| 2016 |
The Dauphin County, PA 2016 QL2 LiDAR project called for the planning, acquisition, processing and derivative products of LIDAR data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LIDAR Specification, Version 1.2. The data was developed based on a horizontal projection/datum of NAD83 (2011) State Plane Pennsylvania South Zone, US survey feet; NAVD1988 (Geoid 12B), US survey feet. LiDAR data was delivered in RAW flight line swath format, processed to create Classified LAS 1.4 Files formatted to 711 individual 5,000-foot x 5,000-foot tiles. Tile names use the following naming schema: "YYYYXXXXPAd" where YYYY is the first 3 characters of the tile's upper left corner Y-coordinate, XXXX - the first 4 characters of the tile's upper left corner X-coordinate, PA = Pennsylvania, and d = 'N' for North or 'S' for South. Corresponding 2.5-foot gridded hydro-flattened bare earth raster tiled DEM files and intensity image files were created using the same 5,000-foot x 5,000-foot schema. Hydro-flattened breaklines were produced in Esri file geodatabase format. Continuous 2-foot contours were produced in Esri file geodatabase format. Ground Conditions: LiDAR collection began in Spring 2016, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications, Quantum Spatial established a total of 84 control points (24 calibration control points and 60 QC checkpoints). These were used to calibrate the LIDAR to known ground locations established throughout the project area.
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| U S Geological Survey |
| 2017 |
The South Central Pennsylvania 2017 QL2 LiDAR project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 1.2. The data were developed based on a horizontal projection/datum of NAD 1983 (2011), UTM Zone 18, meters and vertical datum of NAVD 1988 (GEOID 12B), meters. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 7,975 individual 1,500-meter x 1,500-meter tiles, as tiled intensity imagery, and as tiled bare earth DEMs; all tiled to the same 1,500-meter x 1,500-meter schema. Continuous breaklines were produced in Esri file geodatabase format. Ground Conditions: LiDAR was collected in fall 2017, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Quantum Spatial, Inc. utilized a total of 150 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 245 independent accuracy checkpoints, 142 in Bare Earth and Urban landcovers (142 NVA points), 103 in Tall Weeds categories (103 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2017 |
The South Central Pennsylvania 2017 QL2 LiDAR project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 1.2. The data were developed based on a horizontal projection/datum of NAD 1983 (2011), UTM Zone 18, meters and vertical datum of NAVD 1988 (GEOID 12B), meters. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 7,975 individual 1,500-meter x 1,500-meter tiles, as tiled intensity imagery, and as tiled bare earth DEMs; all tiled to the same 1,500-meter x 1,500-meter schema. Continuous breaklines were produced in Esri file geodatabase format. Ground Conditions: LiDAR was collected in fall 2017, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Quantum Spatial, Inc. utilized a total of 150 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 245 independent accuracy checkpoints, 142 in Bare Earth and Urban landcovers (142 NVA points), 103 in Tall Weeds categories (103 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2017 |
The South Central Pennsylvania 2017 QL2 LiDAR project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 1.2. The data were developed based on a horizontal projection/datum of NAD 1983 (2011), UTM Zone 18, meters and vertical datum of NAVD 1988 (GEOID 12B), meters. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 7,975 individual 1,500-meter x 1,500-meter tiles, as tiled intensity imagery, and as tiled bare earth DEMs; all tiled to the same 1,500-meter x 1,500-meter schema. Continuous breaklines were produced in Esri file geodatabase format. Ground Conditions: LiDAR was collected in fall 2017, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Quantum Spatial, Inc. utilized a total of 150 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 245 independent accuracy checkpoints, 142 in Bare Earth and Urban landcovers (142 NVA points), 103 in Tall Weeds categories (103 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2017 |
The South Central Pennsylvania 2017 QL2 LiDAR project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 1.2. The data were developed based on a horizontal projection/datum of NAD 1983 (2011), UTM Zone 18, meters and vertical datum of NAVD 1988 (GEOID 12B), meters. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 7,975 individual 1,500-meter x 1,500-meter tiles, as tiled intensity imagery, and as tiled bare earth DEMs; all tiled to the same 1,500-meter x 1,500-meter schema. Continuous breaklines were produced in Esri file geodatabase format. Ground Conditions: LiDAR was collected in fall 2017, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Quantum Spatial, Inc. utilized a total of 150 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 245 independent accuracy checkpoints, 142 in Bare Earth and Urban landcovers (142 NVA points), 103 in Tall Weeds categories (103 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2017 |
The South Central Pennsylvania 2017 QL2 LiDAR project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 1.2. The data were developed based on a horizontal projection/datum of NAD 1983 (2011), UTM Zone 18, meters and vertical datum of NAVD 1988 (GEOID 12B), meters. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 7,975 individual 1,500-meter x 1,500-meter tiles, as tiled intensity imagery, and as tiled bare earth DEMs; all tiled to the same 1,500-meter x 1,500-meter schema. Continuous breaklines were produced in Esri file geodatabase format. Ground Conditions: LiDAR was collected in fall 2017, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Quantum Spatial, Inc. utilized a total of 150 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 245 independent accuracy checkpoints, 142 in Bare Earth and Urban landcovers (142 NVA points), 103 in Tall Weeds categories (103 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2017 |
The South Central Pennsylvania 2017 QL2 LiDAR project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 1.2. The data were developed based on a horizontal projection/datum of NAD 1983 (2011), UTM Zone 18, meters and vertical datum of NAVD 1988 (GEOID 12B), meters. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 7,975 individual 1,500-meter x 1,500-meter tiles, as tiled intensity imagery, and as tiled bare earth DEMs; all tiled to the same 1,500-meter x 1,500-meter schema. Continuous breaklines were produced in Esri file geodatabase format. Ground Conditions: LiDAR was collected in fall 2017, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Quantum Spatial, Inc. utilized a total of 150 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 245 independent accuracy checkpoints, 142 in Bare Earth and Urban landcovers (142 NVA points), 103 in Tall Weeds categories (103 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2017 |
The South Central Pennsylvania 2017 QL2 LiDAR project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 1.2. The data were developed based on a horizontal projection/datum of NAD 1983 (2011), UTM Zone 18, meters and vertical datum of NAVD 1988 (GEOID 12B), meters. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 7,975 individual 1,500-meter x 1,500-meter tiles, as tiled intensity imagery, and as tiled bare earth DEMs; all tiled to the same 1,500-meter x 1,500-meter schema. Continuous breaklines were produced in Esri file geodatabase format. Ground Conditions: LiDAR was collected in fall 2017, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Quantum Spatial, Inc. utilized a total of 150 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 245 independent accuracy checkpoints, 142 in Bare Earth and Urban landcovers (142 NVA points), 103 in Tall Weeds categories (103 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2017 |
The South Central Pennsylvania 2017 QL2 LiDAR project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 1.2. The data were developed based on a horizontal projection/datum of NAD 1983 (2011), UTM Zone 18, meters and vertical datum of NAVD 1988 (GEOID 12B), meters. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 7,975 individual 1,500-meter x 1,500-meter tiles, as tiled intensity imagery, and as tiled bare earth DEMs; all tiled to the same 1,500-meter x 1,500-meter schema. Continuous breaklines were produced in Esri file geodatabase format. Ground Conditions: LiDAR was collected in fall 2017, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Quantum Spatial, Inc. utilized a total of 150 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 245 independent accuracy checkpoints, 142 in Bare Earth and Urban landcovers (142 NVA points), 103 in Tall Weeds categories (103 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2017 |
The South Central Pennsylvania 2017 QL2 LiDAR project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 1.2. The data were developed based on a horizontal projection/datum of NAD 1983 (2011), UTM Zone 18, meters and vertical datum of NAVD 1988 (GEOID 12B), meters. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 7,975 individual 1,500-meter x 1,500-meter tiles, as tiled intensity imagery, and as tiled bare earth DEMs; all tiled to the same 1,500-meter x 1,500-meter schema. Continuous breaklines were produced in Esri file geodatabase format. Ground Conditions: LiDAR was collected in fall 2017, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Quantum Spatial, Inc. utilized a total of 150 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 245 independent accuracy checkpoints, 142 in Bare Earth and Urban landcovers (142 NVA points), 103 in Tall Weeds categories (103 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2017 |
The South Central Pennsylvania 2017 QL2 LiDAR project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 1.2. The data were developed based on a horizontal projection/datum of NAD 1983 (2011), UTM Zone 18, meters and vertical datum of NAVD 1988 (GEOID 12B), meters. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 7,975 individual 1,500-meter x 1,500-meter tiles, as tiled intensity imagery, and as tiled bare earth DEMs; all tiled to the same 1,500-meter x 1,500-meter schema. Continuous breaklines were produced in Esri file geodatabase format. Ground Conditions: LiDAR was collected in fall 2017, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Quantum Spatial, Inc. utilized a total of 150 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 245 independent accuracy checkpoints, 142 in Bare Earth and Urban landcovers (142 NVA points), 103 in Tall Weeds categories (103 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2017 |
The South Central Pennsylvania 2017 QL2 LiDAR project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 1.2. The data were developed based on a horizontal projection/datum of NAD 1983 (2011), UTM Zone 18, meters and vertical datum of NAVD 1988 (GEOID 12B), meters. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 7,975 individual 1,500-meter x 1,500-meter tiles, as tiled intensity imagery, and as tiled bare earth DEMs; all tiled to the same 1,500-meter x 1,500-meter schema. Continuous breaklines were produced in Esri file geodatabase format. Ground Conditions: LiDAR was collected in fall 2017, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Quantum Spatial, Inc. utilized a total of 150 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 245 independent accuracy checkpoints, 142 in Bare Earth and Urban landcovers (142 NVA points), 103 in Tall Weeds categories (103 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2017 |
The South Central Pennsylvania 2017 QL2 LiDAR project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 1.2. The data were developed based on a horizontal projection/datum of NAD 1983 (2011), UTM Zone 18, meters and vertical datum of NAVD 1988 (GEOID 12B), meters. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 7,975 individual 1,500-meter x 1,500-meter tiles, as tiled intensity imagery, and as tiled bare earth DEMs; all tiled to the same 1,500-meter x 1,500-meter schema. Continuous breaklines were produced in Esri file geodatabase format. Ground Conditions: LiDAR was collected in fall 2017, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Quantum Spatial, Inc. utilized a total of 150 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 245 independent accuracy checkpoints, 142 in Bare Earth and Urban landcovers (142 NVA points), 103 in Tall Weeds categories (103 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2017 |
The South Central Pennsylvania 2017 QL2 LiDAR project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 1.2. The data were developed based on a horizontal projection/datum of NAD 1983 (2011), UTM Zone 18, meters and vertical datum of NAVD 1988 (GEOID 12B), meters. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 7,975 individual 1,500-meter x 1,500-meter tiles, as tiled intensity imagery, and as tiled bare earth DEMs; all tiled to the same 1,500-meter x 1,500-meter schema. Continuous breaklines were produced in Esri file geodatabase format. Ground Conditions: LiDAR was collected in fall 2017, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Quantum Spatial, Inc. utilized a total of 150 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 245 independent accuracy checkpoints, 142 in Bare Earth and Urban landcovers (142 NVA points), 103 in Tall Weeds categories (103 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.
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| U S Geological Survey |
| 2019 |
Layers of geospatial data include contours, boundaries, land cover, hydrography, roads, transportation, geographic names, structures, and other selected map features.
This dataset depicts geographic features on the surface of the earth. It is a general purpose dataset for users who are not GISexperts. The geospatial data in this dataset are from selected National Map data holdings and other government sources.
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| U S Geological Survey |
| 2008 |
The concern caused by the explosive spread of the zebra mussel, (Dreissena
polymorpha), within the United States resulted in passage of the
Nonindigenous Aquatic Nuisance Prevention and Control Act of 1990 (P.L.
101-646). The impact of this biofouling pest on the economy and
ecological processes in the U.S. and Canada has required prompt action on
a large scale to prevent further infestations and minimize ecological
degradation. This map layer is a compilation of reports of confirmed
zebra mussel sightings in the United States from 1988 to January 2008.
It provides geographical and historical information to show distribution
over time. The reports came from a variety of Federal, State, and
municipal agencies, public utilities, universities, engineering and
private consultant firms. The locations of confirmed sightings were
registered at 1:100,000-scale on EPA Reach File Version 3.0 and are
maintained as an ArcInfo export file. This is a revised version of the
June 2005 map layer.
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| U S Geological Survey |