| Date | Title | Provider |
| 2006 |
Contour data was created as a result of a county flyover in the spring of 2004. Contours were created from a DTM Feature Dataset, upgraded by Baker and T-3 to support National Mapping Accuracy Standards (NMAS) for contours . Intermediate Contours are contours spaced at 5 foot intervals. Depression Contours are contours showing the edges and slope in a depression at 5 foot intervals. Contours are coded separately for delineation between depression and intermediate contours.
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| Allegheny County |
| 2017 |
Lidar Data Products for the Allegheny County, PA collection area including a 6ft DEM, hydrogrpahic breakines, and tiled 2ft Contours. The lidar dataset was collected to be utilized for the creation of a digital elevation model, hydrographic breaklines, and 2ft contours. Other uses expected.
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| Allegheny County |
| 2006 |
Spot Elevation data was created as a result of a county flyover in the spring of 2004. They were created from a DTM Feature Dataset, upgraded by Baker and T-3 to support National Mapping Accuracy Standards (NMAS). Spot Elevations are used to show additional elevation information. They are located in flat areas where contours may be sparse or spaced far apart, at road and railroad intersections, on the road centerline at the ends of bridges, on the road centerline over the center of culverts that have a span of five (5)-foot or greater, at the crest of all tops of hills, at saddles, within depressions and where the ground is visible in obscured areas.
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| Allegheny County |
| 2017 |
Lidar Data Products for the Allegheny County, PA collection area including a 6ft DEM, hydrogrpahic breakines, and tiled 2ft Contours. The lidar dataset was collected to be utilized for the creation of a digital elevation model, hydrographic breaklines, and 2ft contours. Other uses expected.
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| Allegheny County |
| 2017 |
Lidar Data Products for the Allegheny County, PA collection area including a 6ft DEM, hydrogrpahic breakines, and tiled 2ft Contours. The lidar dataset was collected to be utilized for the creation of a digital elevation model, hydrographic breaklines, and 2ft contours. Other uses expected.
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| Allegheny County |
| 2017 |
Lidar Data Products for the Allegheny County, PA collection area including a 6ft DEM, hydrogrpahic breakines, and tiled 2ft Contours. The lidar dataset was collected to be utilized for the creation of a digital elevation model, hydrographic breaklines, and 2ft contours. Other uses expected.
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| Allegheny County |
| 2017 |
Tile Index - Lidar Data Products for the Allegheny County, PA collection area including a 6ft DEM, hydrogrpahic breakines, and tiled 2ft Contours. The lidar dataset was collected to be utilized for the creation of a digital elevation model, hydrographic breaklines, and 2ft contours. Other uses expected.
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| Allegheny County |
| 2017 |
Lidar Data Products for the Allegheny County, PA collection area including a 6ft DEM, hydrogrpahic breakines, and tiled 2ft Contours. The lidar dataset was collected to be utilized for the creation of a digital elevation model, hydrographic breaklines, and 2ft contours. Other uses expected.
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| Allegheny County |
| 2026 |
The purpose of this project was to conduct an assessment of tree canopy change that occurred between 2015 and 2020 utiliing LiDAR data and a previously prepared canopy dataset. Comprehensive canopy change statistics are provided for various geographies down to the parcel-level scale. Tree canopy was extracted from LiDAR data collected in the fall of 2019 and spring of 2020 in ArcMap. A digital surface model (DSM) was created by interpolating the maximum values of the first returns of each laser pulse across a 3-foot grid surface (raster). A speckled output was created because some pulses can entirely or partially pass-through tree canopy before detecting a return, so maximum focal statistics in a 3 by 3 rectangular grid window were applied to the DSM to create a smooth surface. Another raster representing the elevations of solid surfaces which LiDAR does not penetrate - usually ground and buildings, but occasionally dense evergreens as well, was created by interpolating the minimum values of the last returns (which are also the first return in instances of single return). Mean focal statistics in a 3 by 3 cell window were applied to this raster. The last return raster was subtracted from the first return raster, creating a canopy height model (CHM) – a representation of the heights of objects with complex return structures above the ground. In addition to trees, this includes built structures such as power lines, poles, transmission towers, gantries, etc. The edges of buildings also appeared in the CHM as a result of different cell assignment and focal statistics types applied to the first and last return rasters. The heights of dense evergreens were underestimated due to the inability of LiDAR to penetrate to the ground for a proper base for height. A constant raster of CHM cells with a height greater than 15 feet was created. Holes less than 500 square feet were filled to eliminate dubious small gaps while preserving discernable canopy gaps. This raster was then shrunk by 2 cells and expanded back by 2 cells. This process eliminated narrow or small features such as building edges, power lines, and poles. This raster was then converted into a vector polygon format for editing.
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| Allegheny County |
| 2015 |
Lidar Data Products for the Allegheny County, PA collection area including a 6ft DEM, hydrogrpahic breakines, and tiled 2ft Contours. The lidar dataset was collected to be utilized for the creation of a digital elevation model, hydrographic breaklines, and 2ft contours. Other uses expected.
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| Allegheny County |
| 2015 |
Lidar Data Products for the Allegheny County, PA collection area including a 6ft DEM, hydrogrpahic breakines, and tiled 2ft Contours. The lidar dataset was collected to be utilized for the creation of a digital elevation model, hydrographic breaklines, and 2ft contours. Other uses expected.
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| Allegheny County |
| 2015 |
Lidar Data Products for the Allegheny County, PA collection area including a 6ft DEM, hydrogrpahic breakines, and tiled 2ft Contours. The lidar dataset was collected to be utilized for the creation of a digital elevation model, hydrographic breaklines, and 2ft contours. Other uses expected.
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| Allegheny County |
| 2015 |
Lidar Data Products for the Allegheny County, PA collection area including a 6ft DEM, hydrogrpahic breakines, and tiled 2ft Contours. The lidar dataset was collected to be utilized for the creation of a digital elevation model, hydrographic breaklines, and 2ft contours. Other uses expected.
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| Allegheny County |
| 2004 |
Planimetric Coverage containing the delineation of topographic contours at ten foot intervals. Annotation of Contour Line elevations exists. Annotation viewable at 1" = 200'. The city-wide contour download file is approximately 250 megabytes.
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| City of Philadelphia |
| 2004 |
Planimetric Coverage containing the delineation of topographic contours at two foot intervals. Annotation of Contour Line elevations exists. Annotation viewable at 1" = 200'. The city-wide contour download file is approximately 250 megabytes.
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| City of Philadelphia |
| 2008 |
LiDAR and LAS data was gathered for the City of Philadelphia in April 2008. DEMs were generated from the raw data.
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| City of Philadelphia |
| 2010 |
LiDAR and LAS data was gathered for the City of Philadelphia in April 2010. DEMs were generated from the raw data.
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| City of Philadelphia |
| 2015 |
The lidar dataset was collected to be utilized for the creation of a digital elevation model and 1ft contours. Other uses expected. The GIS Services Group at OIT generated these 10ft Contours for the 2015 1ft Contours.
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| City of Philadelphia |
| 2015 |
The lidar dataset was collected to be utilized for the creation of a digital elevation model and 1ft contours. Other uses expected. Lidar Data Products for the Philadelphia, PA collection area including a 5ft Digital Elevation Model (DEM), and tiled1ft Contours.
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| City of Philadelphia |
| 2015 |
The lidar dataset was collected to be utilized for the creation of a digital elevation model and 1ft contours. Other uses expected. The GIS Services Group at OIT generated these 2ft Contours from the 2015 1ft Contours.
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| City of Philadelphia |
| 2018 |
Planimetric Coverage containing the delineation of topographic contours at ten foot intervals. Annotation of Contour Line elevations exists. LiDAR and LAS data was gathered for the City of Philadelphia in April 2018. DEMs were generated from the raw data. This dataset is lidar point cloud data covering the City of Philadelphia, PA, approximately 239 sq miles total. Each LAS file contains LiDAR point information, which has been calibrated, controlled, and classified. At the time of capture ground conditions were leaf-off, snow free, and water was at normal levels
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| City of Philadelphia |
| 2018 |
Planimetric Coverage containing the delineation of topographic contours at two foot intervals. Annotation of Contour Line elevations exists. LiDAR and LAS data was gathered for the City of Philadelphia in April 2018. DEMs were generated from the raw data. This dataset is lidar point cloud data covering the City of Philadelphia, PA, approximately 239 sq miles total. Each LAS file contains LiDAR point information, which has been calibrated, controlled, and classified. At the time of capture ground conditions were leaf-off, snow free, and water was at normal levels.
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| City of Philadelphia |
| 2022 |
Topographic Contours 1ft - Planimetric Coverage containing the delineation of topographic contours at one foot intervals. Annotation of Contour Line elevations exists. LiDAR and LAS data was gathered for the City of Philadelphia in April 2022. DEMs were generated from the raw data. This dataset is lidar point cloud data covering the City of Philadelphia, PA, approximately 239 sq miles total. Each LAS file contains LiDAR point information, which has been calibrated, controlled, and classified. At the time of capture ground conditions were leaf-off, snow free, and water was at normal levels. For Additional Information see: https://www.pasda.psu.edu/download/phillyLiDAR/2022/Metadata_and_Reports/Lidar_Report/65221207_Philadelphia_Mapping_Report.pdf
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| City of Philadelphia |
| 1996 |
Planimetric Coverage containing the delineation of topographic contours. Annotation of Contour Line elevations exists. Annotation viewable at 1" = 200?
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| City of Philadelphia |
| 2011 |
Half meter GSD represented in Geographic Decimal Degrees, natural color (RGB), 8-bit per band digital orthophotography for approximately 14,035 square miles in Pennsylvania. The imagery was collected using the Leica Geosystems ADS40-SH51 during Fall, 2010 and Spring, 2011 at an average altitude of 4,800 meters above ground level. An auto correlated elevation model was used as vertical control. Airborne GPS/IMU was used as a basis for Analytical Aerial Triangulation (AT). Following rectification of imagery, manually placed seamlines were used to mosaic into a seamless coverage. The orthophotography is georeferenced to Geographic NAD83 decimal degrees.
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| DCNR PAMAP Program |
| 2011 |
Tile Index - Half meter GSD represented in Geographic Decimal Degrees, natural color (RGB), 8-bit per band digital orthophotography for approximately 14,035 square miles in Pennsylvania. The imagery was collected using the Leica Geosystems ADS40-SH51 during Fall, 2010 and Spring, 2011 at an average altitude of 4,800 meters above ground level. An auto correlated elevation model was used as vertical control. Airborne GPS/IMU was used as a basis for Analytical Aerial Triangulation (AT). Following rectification of imagery, manually placed seamlines were used to mosaic into a seamless coverage. The orthophotography is georeferenced to Geographic NAD83 decimal degrees.
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| DCNR PAMAP Program |
| 2010 |
(2010) Pennsylvania area natural color seamless orthoimagery acquired by Aerials Express at a 45cm pixel-resolution. Flight operations began on 12/11/09 and ended on 04/10/10 using an (DMC) camera with an approximate forward overlap of 60% and side overlap of 30% with an approximate Ground Sample Distance of (44 cm). The dataset is projected as Universal Transverse Mercator (UTM) 17 on the North American Datum of 1983. The PAMAP Program LiDAR Data of Pennsylvania; West Virginia Statewide Digital Elevation Models; USGS National Elevation Dataset (NED) - (Used in the respective sequential order) were utilized as the Digital Elevation Model in ortho-processing.
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| DCNR PAMAP Program |
| 2010 |
TILE INDEX North - (2010) Pennsylvania area natural color seamless orthoimagery acquired by Aerials Express at a 45cm pixel-resolution. Flight operations began on 12/11/09 and ended on 04/10/10 using an (DMC) camera with an approximate forward overlap of 60% and side overlap of 30% with an approximate Ground Sample Distance of (44 cm). The dataset is projected as Universal Transverse Mercator (UTM) 17 on the North American Datum of 1983. The PAMAP Program LiDAR Data of Pennsylvania; West Virginia Statewide Digital Elevation Models; USGS National Elevation Dataset (NED) - (Used in the respective sequential order) were utilized as the Digital Elevation Model in ortho-processing.
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| DCNR PAMAP Program |
| 2010 |
TILE INDEX South - (2010) Pennsylvania area natural color seamless orthoimagery acquired by Aerials Express at a 45cm pixel-resolution. Flight operations began on 12/11/09 and ended on 04/10/10 using an (DMC) camera with an approximate forward overlap of 60% and side overlap of 30% with an approximate Ground Sample Distance of (44 cm). The dataset is projected as Universal Transverse Mercator (UTM) 17 on the North American Datum of 1983. The PAMAP Program LiDAR Data of Pennsylvania; West Virginia Statewide Digital Elevation Models; USGS National Elevation Dataset (NED) - (Used in the respective sequential order) were utilized as the Digital Elevation Model in ortho-processing.
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| DCNR PAMAP Program |
| 2006 - 2008 |
Mosaics of PAMAP DEMs by PAMAP Lidar Delivery Zones -
This dataset, produced by the PAMAP Program, consists of a raster digital elevation model with a horizontal ground resolution of 3.2 feet. The model was constructed from PAMAP LiDAR (Light Detection and Ranging) elevation points. PAMAP data are organized into blocks, which do not have gaps or overlaps, that represent 10,000 feet by 10,000 feet on the ground. The coordinate system for blocks in the northern half of the state is Pennsylvania State Plane North (datum:NAD83, units: feet); blocks in the southern half of the state are in Pennsylvania State Plane South. A block name is formed by concatenating the first four digits of the State Plane northing and easting defining the block's northwest corner, the State identifier "PA", and the State Plane zone designator "N" or "S" (e.g. 45001210PAS).
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| DCNR PAMAP Program |
| 2006 - 2008 |
This dataset, produced by the PAMAP Program, consists of topographic contours mapped at an interval of 2 feet. Contours were derived from a bare-earth digital elevation model constructed from PAMAP LiDAR (Light Detection and Ranging) elevation points. PAMAP data are organized into blocks, which do not have gaps or overlaps, that represent 10,000 feet by 10,000 feet on the ground. The coordinate system for blocks in the northern half of the state is Pennsylvania State Plane North (datum:NAD83, units: feet); blocks in the southern half of the state are in Pennsylvania State Plane South. A block name is formed by concatenating the first four digits of the State Plane northing and easting defining the block's northwest corner, the State identifier "PA", and the State Plane zone designator "N" or "S" (e.g. 45001210PAS).
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| DCNR PAMAP Program |
| 2006 - 2008 |
This dataset, produced by the PAMAP Program, consists of a raster digital elevation model with a horizontal ground resolution of 3.2 feet. The model was constructed from PAMAP LiDAR (Light Detection and Ranging) elevation points. PAMAP data are organized into blocks, which do not have gaps or overlaps, that represent 10,000 feet by 10,000 feet on the ground. The coordinate system for blocks in the northern half of the state is Pennsylvania State Plane North (datum:NAD83, units: feet); blocks in the southern half of the state are in Pennsylvania State Plane South. A block name is formed by concatenating the first four digits of the State Plane northing and easting defining the block's northwest corner, the State identifier "PA", and the State Plane zone designator "N" or "S" (e.g. 45001210PAS).
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| DCNR PAMAP Program |
| 2006 - 2008 |
This dataset consists of classified LiDAR (Light Detection and Ranging) elevation points produced by the PAMAP Program. Additional information is available at the PAMAP website: www.dcnr.state.pa.us/topogeo/pamap.
PAMAP data are organized into blocks, which do not have gaps or overlaps, that represent 10,000 feet by 10,000 feet on the ground. The coordinate system for blocks in the northern half of the state is Pennsylvania State Plane North (datum:NAD83, units: feet); blocks in the southern half of the state are in Pennsylvania State Plane South. A block name is formed by concatenating the first four digits of the State Plane northing and easting defining the block's northwest corner, the State identifier "PA", and the State Plane zone designator "N" or "S" (e.g. 45001210PAS).
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| DCNR PAMAP Program |
| 2005 |
An elevation or topgraphic contour is a line that connects a series of points of equal elevation and is used to illustrate topography, or relief, on a map. It shows the height of ground above Mean Sea Level (M.S.L.). Numerous contour lines that are close together indicate hilly or mountainous terrain; when far apart, they represent a gentler slope. This layer consists of contours at a five foot interval for DVRPC's 9-county region and was generated from an aerial topographic survey in 2005.The Delaware Valley Regional Planning Commission's (DVRPC) 9-county region is made up of the following: Bucks, Chester, Delaware, Montgomery, and Philadelphia counties in Pennsylvania; and Burlington, Camden, Gloucester, and Mercer counties in New Jersey.
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| Delaware Valley Regional Planning Commission |
| 2005 |
A spot elevation is an elevation measurement taken at a single location. It shows the height of ground above Mean Sea Level (M.S.L.). This layer consists of spot elevations for DVRPC's 9-county region and was generated from an aerial topographic survey in 2005.The Delaware Valley Regional Planning Commission's (DVRPC) 9-county region is made up of the following: Bucks, Chester, Delaware, Montgomery, and Philadelphia counties in Pennsylvania; and Burlington, Camden, Gloucester, and Mercer counties in New Jersey.
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| Delaware Valley Regional Planning Commission |
| 2020 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2020 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2013 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2013 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2013 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2020 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2013 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2020 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2020 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2013 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2013 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2013 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2020 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2020 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2013 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2013 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2020 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2013 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2020 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2020 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2013 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2013 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2013 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2013 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2013 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2020 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2013 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2020 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2013 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2020 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2013 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2013 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2020 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2020 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2013 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2020 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2020 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2020 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2013 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2013 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2013 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2013 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2020 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2020 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2020 |
A 1% Annual Chance Flood Depth Grid represents the height of a 100 year flood surface elevation above ground or bottom of a stream channel measured in feet. The values are captured per cell of a defined area. The cell size for 1% Annual Chance Flood Depth Grids is variable. It is calculated by subtracting the height of the ground surface elevation from the surface height of the 1% annual chance flood. A Flood Depth Grid can assist a community in understanding, communicating, and relaying the variability and severity of flooding in a mapped floodplain.
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| Federal Emergency Management Agency |
| 2019 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2019 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2019 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2019 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2019 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2019 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2026 |
The FIRM is the basis for floodplain management, mitigation, and insurance activities for the National Flood Insurance Program (NFIP). Insurance applications include enforcement of the mandatory purchase requirement of the Flood Disaster Protection Act, which "... requires the purchase of flood insurance by property owners who are being assisted by Federal programs or by Federally supervised, regulated or insured agencies or institutions in the acquisition or improvement of land facilities located or to be located in identified areas having special flood hazards," Section 2 (b) (4) of the Flood Disaster Protection Act of 1973. In addition to the identification of Special Flood Hazard Areas (SFHAs), the risk zones shown on the FIRMs are the basis for the establishment of premium rates for flood coverage offered through the NFIP. The DFIRM Database presents the flood risk information depicted on the FIRM in a digital format suitable for use in electronic mapping applications. The DFIRM database is a subset of the Digital FIS database that serves to archive the information collected during the FIS. The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting
data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance
flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The DFIRM
Database is derived from Flood Insurance Studies (FISs), previously published Flood Insurance Rate Maps
(FIRMs), flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data,
where available. The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA).
The file is georeferenced to earth's surface using the UTM projection and coordinate system.The
specifications for the horizontal control of DFIRM data files are consistent with those required for
mapping at a scale of 1:12,000.
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| Federal Emergency Management Agency |
| 2005 |
various layers clipped to counties - The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting
data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance
flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The DFIRM
Database is derived from Flood Insurance Studies (FISs), previously published Flood Insurance Rate Maps
(FIRMs), flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data,
where available. The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA).
The file is georeferenced to earth's surface using the UTM projection and coordinate system. The
specifications for the horizontal control of DFIRM data files are consistent with those required for
mapping at a scale of 1:12,000.
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| Federal Emergency Management Agency |
| 2019 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2019 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2015 |
FEMA Historic Products - Once a FIRM or FIS has been superseded by a new version, it will be categorized as a Historic Product. After they move to this status, these products are no longer official and binding under the NFIP (National Flood Insurance Program). However, Historic Products may serve as valuable reference information and provide a record of an area's changing flood risks over time. They are made available on the Map Service Center for these purposes. Letters of Map Change (LOMC) that were issued to amend Historic Products when they were still effective are also listed here. A LOMC is a formal document that communicates an official modification to an effective Flood Insurance Rate Map (FIRM). LOMCs are issued in place of a physical alteration and re-publication of the map. Regulatory Mapping Products Flood Insurance Rate Map (FIRM) - The official map of a community on which FEMA has delineated both the special hazard areas and the risk premium zones applicable to the community. Full FIRM panels are quite large (36' x 25.875'), so most users will prefer to print out a smaller selected portion called a FIRMette. This can be accomplished by selecting "View" once you have located your FIRM or by using the FIRMette - Desktop application. Flood Insurance Study (FIS) - A compilation and presentation of flood risk data for specific watercourses, lakes and coastal flood hazard areas within a community. The FIS report provides a detailed written account of a flood hazard mapping study and its findings. Letters of Map Change (LOMC) - Documents, including different types of Letters of Map Revision (LOMR) and Letters of Map Amendment (LOMA), that are issued by FEMA to revise or amend the flood hazard information shown on the FIRM without requiring the FIRM to be physically revised and republished. In addition, FEMA issues a formal determination letter, called a LOMC Revalidation or LOMC-VALID letter - when one or more previously issued LOMCs are found to still be valid during a new flood mapping study of an area. Revalidation letters are included in the LOMC product results on this site.
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| Federal Emergency Management Agency |
| 2021 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2024 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2021 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2019 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2019 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2018 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2024 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2024 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2023 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2018 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2012 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2011 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2002 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2021 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2024 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2014 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2021 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2017 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2021 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2021 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2023 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2021 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2021 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2016 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2017 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2017 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2010 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2023 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2011 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2015 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2019 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2019 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2017 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2021 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2022 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2021 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2012 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2020 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2023 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2024 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2018 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2016 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2016 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2021 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2025 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2023 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2008 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2024 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2021 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2019 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2023 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2000 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2019 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2021 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2019 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2014 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2015 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2021 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2021 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2021 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2014 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2017 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2020 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2019 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2016 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2012 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2020 |
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).
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| Federal Emergency Management Agency |
| 2025 |
A building in which courts of law are regularly held.
USGS Structures from The National Map consists of data to include the name, function, location, and other core information and characteristics of selected manmade facilities. The types of structures collected are largely determined by the needs of disaster planning and emergency response, and homeland security organizations. Structures currently being collected are: School, Technical/Trade School, College/University, Fire Station/EMS Station, Law Enforcement/Police Station, Prison/Correctional Facility, State Capitol, Hospital/Medical Center, Ambulance Service, Cemetery, Post Office, Campground, Trailhead, and Visitor/Information Center. Structures data are designed to be used in general mapping and in the analysis of structure related activities using geographic information system technology. The National Map structures data is commonly combined with other data themes, such as boundaries, elevation, hydrography, and transportation, to produce general reference base maps. The National Map download client allows free downloads of public domain structures data in either Esri File Geodatabase or Shapefile formats. For additional information on the structures data model, go to https://www.usgs.gov/core-science-systems/ngp/tnm-corps/structures. See https://apps.nationalmap.gov/help/ for assistance with The National Map viewer, download client, services, or metadata. Data Refreshed January, 2025
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| Homeland Infrastructure Foundation Level Data HIFLD |
| 2025 |
Fire / EMS Station: A building that contains fire-fighting equipment and personnel or a provider of combined fire-fighting and rescue services.
USGS Structures from The National Map consists of data to include the name, function, location, and other core information and characteristics of selected manmade facilities. The types of structures collected are largely determined by the needs of disaster planning and emergency response, and homeland security organizations. Structures currently being collected are: School, Technical/Trade School, College/University, Fire Station/EMS Station, Law Enforcement/Police Station, Prison/Correctional Facility, State Capitol, Hospital/Medical Center, Ambulance Service, Cemetery, Post Office, Campground, Trailhead, and Visitor/Information Center. Structures data are designed to be used in general mapping and in the analysis of structure related activities using geographic information system technology. The National Map structures data is commonly combined with other data themes, such as boundaries, elevation, hydrography, and transportation, to produce general reference base maps. The National Map download client allows free downloads of public domain structures data in either Esri File Geodatabase or Shapefile formats. For additional information on the structures data model, go to https://www.usgs.gov/core-science-systems/ngp/tnm-corps/structures. See https://apps.nationalmap.gov/help/ for assistance with The National Map viewer, download client, services, or metadata
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| Homeland Infrastructure Foundation Level Data HIFLD |
| 2025 |
Locations of the world's volcanoes, from the Smithsonian Institution Global Volcanism Program.
The Volcano Locations Database is a global listing of over 1600 volcanoes which includes information on the latitude, longitude, elevation, type of volcano, and last known eruption. These data are from the Smithsonian Institution Global Volcanism Program (GVP), "Volcanoes of the World" publication. Please go to their website for additional volcano status and eruption information.
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| Homeland Infrastructure Foundation Level Data HIFLD |
| 2025 |
NCEI/WDS Significant Volcanic Events Database
The Significant Volcanic Events Database is a global listing of over 800 significant eruptions which includes information on the latitude, longitude, elevation, type of volcano, and last known eruption. A significant eruption is classified as one that meets at least one of the following criteria: caused fatalities, caused moderate damage (approximately $1 million or more), with a Volcanic Explosivity Index (VEI) of 6 or larger, caused a tsunami, or was associated with a major earthquake. For a complete list of current and past activity for all volcanoes on the planet active during the last 10,000 years, please see Smithsonian Institution's Global Volcanism Program (GVP). The database can also be displayed and extracted with the Natural Hazards Interactive Map.
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| Homeland Infrastructure Foundation Level Data HIFLD |
| 2025 |
The National Flood Hazard Layer (NFHL) is a compilation of GIS data that comprises a nationwide digital Flood Insurance Rate Map. The GIS data and services are designed to provide the user with the ability to determine the flood zone, base flood elevation, and floodway status for a particular location. It also has information about the NFIP communities, map panels, cross sections, hydraulic structures, Coastal Barrier Resource System, and base maps such as road, stream, and public land survey data. Through flood studies, FEMA produces Flood Insurance Study Reports, FIRM Panels, and FIRM Databases. FIRM Databases that become effective are incorporated into the NFHL. Updates to the NFHL are issued through Letters of Map Revision (LOMRs) and Letters of Map Amendment (LOMAs). Continuously updated, the NFHL serves as a Digital Flood Insurance Rate Map representing the current effective flood data for those communities where maps have been digitized. NFHL data can be viewed with widely available GIS software, including freely available programs that work with GIS shapefiles. For more information on the NFHL, see the online resources referenced herein. Using base maps: The minimum horizontal positional accuracy for base map hydrographic and transportation features used with the NFHL is the NSSDA radial accuracy of 38 feet. Letter of Map Amendment (LOMA) point locations are approximate. The location of the LOMA is referenced in the legal description of the letter itself. LOMA points can be viewed in the NFHL Interactive Map on the FEMA GeoPlatform.
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| Homeland Infrastructure Foundation Level Data HIFLD |
| 2025 |
Boundaries of National Forest System lands, including National Forests, defined by the U.S. Forest Service.
The USGS Governmental Unit Boundaries service from The National Map (TNM) represents major civil areas for the Nation, including States or Territories, counties (or equivalents), Federal and Native American areas, congressional districts, minor civil divisions, incorporated places (such as cities and towns), and unincorporated places. Boundaries data are useful for understanding the extent of jurisdictional or administrative areas for a wide range of applications, including mapping or managing resources, and responding to natural disasters. Boundaries data also include extents of forest, grassland, park, wilderness, wildlife, and other reserve areas useful for recreational activities, such as hiking and backpacking. Boundaries data are acquired from a variety of government sources. The data represents the source data with minimal editing or review by USGS. Please refer to the feature-level metadata for information on the data source. The National Map boundaries data is commonly combined with other data themes, such as elevation, hydrography, structures, and transportation, to produce general reference base maps. The National Map download client allows free downloads of public domain boundaries data in either Esri File Geodatabase or Shapefile formats. See https://apps.nationalmap.gov/help/ for assistance with The National Map viewer, download client, services, or metadata.
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| Homeland Infrastructure Foundation Level Data HIFLD |
| 2025 |
A building occupied by a state legislature.
USGS Structures from The National Map consists of data to include the name, function, location, and other core information and characteristics of selected manmade facilities. The types of structures collected are largely determined by the needs of disaster planning and emergency response, and homeland security organizations. Structures currently being collected are: School, Technical/Trade School, College/University, Fire Station/EMS Station, Law Enforcement/Police Station, Prison/Correctional Facility, State Capitol, Hospital/Medical Center, Ambulance Service, Cemetery, Post Office, Campground, Trailhead, and Visitor/Information Center. Structures data are designed to be used in general mapping and in the analysis of structure related activities using geographic information system technology. The National Map structures data is commonly combined with other data themes, such as boundaries, elevation, hydrography, and transportation, to produce general reference base maps. The National Map download client allows free downloads of public domain structures data in either Esri File Geodatabase or Shapefile formats. For additional information on the structures data model, go to https://www.usgs.gov/core-science-systems/ngp/tnm-corps/structures. See https://apps.nationalmap.gov/help/ for assistance with The National Map viewer, download client, services, or metadata.
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| Homeland Infrastructure Foundation Level Data HIFLD |
| 2025 |
Recreational trails of the United States, including National Scenic Trails.
The USGS Transportation downloadable data from The National Map (TNM) is based on TIGER/Line data provided through U.S. Census Bureau and supplemented with HERE road data to create tile cache base maps. Some of the TIGER/Line data includes limited corrections done by USGS. Transportation data consists of roads, railroads, trails, airports, and other features associated with the transport of people or commerce. The data include the name or route designator, classification, and location. Transportation data support general mapping and geographic information system technology analysis for applications such as traffic safety, congestion mitigation, disaster planning, and emergency response. The National Map transportation data is commonly combined with other data themes, such as boundaries, elevation, hydrography, and structures, to produce general reference base maps. The National Map viewer allows free downloads of public domain transportation data in either Esri File Geodatabase or Shapefile formats. For additional information on the transportation data model, go to https://www.usgs.gov/core-science-systems/national-geospatial-program/national-map. See https://apps.nationalmap.gov/help/ for assistance with The National Map viewer, download client, services, or metadata.
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| Homeland Infrastructure Foundation Level Data HIFLD |
| 2008 |
This dataset consists of lines representing elevation contours at a 5 foot interval, with index contours at a 25 foot interval.
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| Lancaster County |
| 2008 |
The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The DFIRM Database is derived from Flood Insurance Studies (FISs), previously published Flood Insurance Rate Maps (FIRMs), flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA). The file is georeferenced to earth's surface using the UTM projection and coordinate system. The specifications for the horizontal control of DFIRM data files are consistent with those required for mapping at a scale of 1:12,000.
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| Lycoming County |
| 2008 |
The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The DFIRM Database is derived from Flood Insurance Studies (FISs), previously published Flood Insurance Rate Maps (FIRMs), flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA). The file is georeferenced to earth's surface using the UTM projection and coordinate system. The specifications for the horizontal control of DFIRM data files are consistent with those required for mapping at a scale of 1:12,000.
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| Lycoming County |
| 2008 |
The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The DFIRM Database is derived from Flood Insurance Studies (FISs), previously published Flood Insurance Rate Maps (FIRMs), flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA). The file is georeferenced to earth's surface using the UTM projection and coordinate system. The specifications for the horizontal control of DFIRM data files are consistent with those required for mapping at a scale of 1:12,000.
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| Lycoming County |
| 2008 |
The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The DFIRM Database is derived from Flood Insurance Studies (FISs), previously published Flood Insurance Rate Maps (FIRMs), flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA). The file is georeferenced to earth's surface using the UTM projection and coordinate system. The specifications for the horizontal control of DFIRM data files are consistent with those required for mapping at a scale of 1:12,000.
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| Lycoming County |
| 2008 |
The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The DFIRM Database is derived from Flood Insurance Studies (FISs), previously published Flood Insurance Rate Maps (FIRMs), flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA). The file is georeferenced to earth's surface using the UTM projection and coordinate system. The specifications for the horizontal control of DFIRM data files are consistent with those required for mapping at a scale of 1:12,000.
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| Lycoming County |
| 2002 |
The Shuttle Radar Topography Mission (SRTM) is a partnership between
NASA and the National Geospatial-Intelligence Agency (NGA). Flown aboard the NASA
Space Shuttle Endeavour (11-22 February 2000), SRTM fulfilled its mission to map the
world in three dimensions. The USGS is under agreement with NGA and NASA's Jet
Propulsion Laboratory to distribute the C-band data. SRTM utilized dual Spaceborne
Imaging Radar (SIR-C) and dual X-band Synthetic Aperture Radar (X-SAR) configured as
a baseline interferometer to successfully collect data over 80 per cent of the
Earth's land surface, everything between 60 degrees North and 56 degrees South
latitude.
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| National Aeronautics and Space Administration NASA |
| 2023 |
PaGS assembled 214,851 relevant well records from Pennsylvania, GroundWater Information System (PaGWIS) and other unpublished PaGS reports. Each well used in the analysis contains a measurement of the depth to bedrock (in feet) and/or a notation indicating if bedrock was encountered during well drilling, these attributes allow well records to be separated into two datasets – bedrock wells (wells that penetrate bedrock) and drift wells (wells that did not encounter bedrock).Topographic Position Index (TPI) is a quantitative landform analysis that uses land surface elevation data to determine landforms such as ridge, upper slope, middle/flat slope, lower slope, and valley. A composite TPI raster for each of Pennsylvania’s 23 physiographic sections was generated. Each well data point was attributed to a physiographic section and assigned a TPI value based on its location. The square root of depth-to-bedrock was calculated for each well. A linear regression relationship between the TPI and the square root of sediment thickness was established for five TPI classes (ridge, upper slope, middle/flat slope, lower slope, and valley) in each of the 23 physiographic sections. This statistical relationship was used to create a surrogate model for depth to bedrock to predict sediment thickness across the state. Synthetic data points were generated from the surrogate model to fill in areas of low well data density. A combination of bedrock well data points and synthetic data points were used to generate the first-iteration sediment thickness model through a natural neighbor interpolation technique. Iterative refinements to the sediment thickness model were made by comparing model predictions to drift well data points. If the total depth of the drift well was less than the predicted thickness of sediment at that location, then the drift well data point was ignored. If the total depth of a drift well was greater than the predicted thickness of sediment at that location, then the drift well data point was added to dataset and a new sediment thickness model was generated. In total, 413, 474 data points were used in the modeling process – 207,130 empirically derived well points and 206, 344 synthetic points derived from the surrogate model.The final sediment thickness model was resampled to a 100-meter grid digital raster conforming to a similar resolution surface topography digital elevation raster. The surface topography grid was smoothed to remove detail before subtracting the sediment thickness to create a bedrock elevation map. The degree of smoothing was applied proportionally to the magnitude of sediment thickness. Portions of the surface topography grid that correspond to sediment thickness greater than 365 feet received the maximum amount of smoothing; likewise, portions of the surface topography grid that correspond to zero sediment thickness received no smoothing. The remaining portions of the surface topography grid that correspond to sediment thickness between 0 and 365 feet received gradational smoothing proportional to the sediment thickness.This 100-meter grid bedrock elevation raster was calculated by subtracting the sediment thickness model from the conditionally-smoothed surface topography digital elevation raster.
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| Pennsylvania Department of Conservation and Natural Resources |
| 2022 |
Maximum Elevations in Pennsylvania Counties
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| Pennsylvania Department of Conservation and Natural Resources |
| 2025 |
PaGS created a new subsurface geologic dataset based on existing borehole data, a re-interpreted seismic reflection profile, and previously published non-digital products through digitization of cross section traces and extraction of XYZ data from cross sections. The generated digital surface represents the base of the Mesozoic consolidated rock units within the Newark-Gettysburg basin. PaGS and Harrisburg University of Science and Technology (HUS&T) georeferenced and digitized 66 interpretive geologic cross sections that cross the boundary of the Newark-Gettysburg basin. The cross sections were retrieved from 22 publications by various authors from PaGS and USGS dated between 1931 to 2025. The cross sections were digitized into polylines and subsequently georeferenced by first georeferencing the scanned versions of the source maps, matching the start and end of each cross section to its corresponding transect line on the map (horizontal georeference), and then by performing a transformation calculation to assign Z values to the endpoints of the digitized cross section (vertical georeference). The polylines were then converted into points with XYZ coordinates. Each point from the digitized cross sections was attributed with publication source information and contact type (e.g., unconformity, fault, etc.). Arm Group, LLC provided a dataset of XYZ locations of the data shots and the elevations of the interpreted base of the Gettysburg basin from a reprocessed seismic reflection dataset originally collected in 1974 across the Gettysburg basin (Transect Line 1410-P-4). PaGS prepared a 3D model surface of the base of the Newark-Gettysburg basin in ESRI ArcPro version 3.1.4 by combining the point data from the 66 interpretive geologic cross sections, 2 available borehole logs, and 1 seismic reflection profile. For geologic cross sections not interpreted to bottom of the basin, the interpreted unconformity beneath the Triassic sedimentary units in each geologic cross section was extended in a linear fashion to ?20,000 feet or to a depth corresponding to a similar extension on the opposing side of the basin. Contour lines at 1,000-foot intervals were constructed in a 3D space between the interpreted geologic cross sections, extrapolated unconformity lines, and the interpreted seismic reflection data to create a model “scaffolding”. Two borehole logs were available to constrain the contour placement; one borehole extended below the unconformity and is the sole empirical subsurface input point for the model. A total of 8,169 points (surface and subsurface) were used as inputs for this modeling effort. Four tiered natural neighbor interpolations at varying grid cell sizes were performed using the constructed contour lines as inputs: “Tier 1” represents the confidence in the empirical data used in the project with a grid cell size of 40 feet; “Tier 2” represents the confidence in the interpreted data and resolution of the surficial geologic mapping with a grid cell size of 400 feet; “Tier 3” represents the confidence in the model space between the interpreted data points with a grid cell size of 800 feet; and “Tier 4” represents the confidence in the extrapolated data and model space between extrapolated data points with a grid cell size of 1,600 feet. Data points were extracted from each raster with the corresponding Z values of each cell attributed to the points. The resulting modeled surface is a point dataset with varying horizontal grids and was constructing by merging: Tier 1 points within 400 feet of the borehole data; Tier 2 points within 4,000 feet of the surficial border of Mesozoic formations and within 4,000 feet of the interpretive geologic cross sections or seismic transect; Tier 3 points within 8,000 feet of the contour lines directly connecting the geologic cross sections and seismic transect; and Tier 4 points located outside of the Tiers 1, 2, and 3 buffer zones.
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| Pennsylvania Department of Conservation and Natural Resources |
| 2023 |
An intermediate product of the Pennsylvania Hydrography Dataset (PAHD) generation. This product is the result of a conflation study with existing hydrography originated by the Allegheny County Division of Computer Services Geographic Information Systems Group. This product is not intended to be a finalized component of the Pennsylvania Hydrography Dataset (PAHD): these are provisional data that have undergone no manual refinement. The Modeled_PAHD_Flowpath geometries represent an intermediate product that was created from a workflow that was examining, among other things, the application of conflation steps, monotonicity, and Topographic Positioning Index (TPI) products toward an automated elevation-derived hydrography (EDH) workflow.
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| Pennsylvania Department of Conservation and Natural Resources |
| 1998 |
The land surface of Pennsylvania is anything but flat and horizontal. The surface comprises complex arrangements of differences in elevation above mean sea level. The spatial arrangement of these elevation differences comprises topography. Topography that has describable uniformity throughout some areal dimension is termed a landform. Landforms can be classified, boundaries can be drawn, and a map can be created. A preliminary landform map was compiled at approximately 1:605,500 scale. The map has four levels of landform subdivision: province, section, region, and district. These units range in size from many hundreds of square miles (province) to less than 200 square miles (district). The greatest topographic similarity for a given landform unit occurs in the smallest subdivision (district). The greatest topographic dissimilarity for a given landform unit occurs in the largest subdivision (province).
The landform map was digitized using ARC/INFO software. Polygon attributes include name of physiographic province, section, district, and area, and the numerical designation of the landform unit. Arcs were attributed according to whether they form the boundary of one or more of the following: province, section, region, district, or state.
These data sets are preliminary and will be superseded in 1999 by more detailed data sets prepared from 1:50,000-scale compilation maps having five levels of landform subdivision.
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| Pennsylvania Department of Conservation and Natural Resources |
| 2026 |
Points digitized from the historic Mylar tracking system, attributed with fields from BMP spreadsheet of Mylar index cards.A layer containing points of portal entries and coal seam elevations of coal mines. Data was converted over from the physical "Mylar Review" system for surface mine permit location look-ups. The physical topographic maps and mylar overlays have been scanned, georeferenced, and vectorized to create the point layers with an index number attribute. The corresponding index cards have been data entered in a spreadsheet. The point layers' attribute tables were joined with the spreadsheet. More recent coal feature points and attributes were digitized directly as shapefiles. This layer represents a combination of various coal mine tracking systems.
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| Pennsylvania Department of Environmental Protection |
| 2012 |
WPA Mapping was drawn in the 1930’s as part of the “Works Progress Administration”. All mining shown on the WPA Maps is assumed to have taken place ‘Prior to 1935’. The WPA Maps were laid out based on the 15’ USGS Topographic Quadrangles, consisting of nine (9) 5' sections. The lower right corner of the WPA Maps includes the sheet name and coal seam covered by the sheet. The latitude and longitude of each corner of the WPA Map is shown. The adjacent WPA Map is listed at each corner and mid way along each edge. The contour lines on the WPA Maps indicate the elevation of the coal seam in feet “above sea level”. The coal seam outcrop is shown using a heavy black line. The outcrop is the point where the coal seam elevation and the surface elevation are equal. The speckled areas on the maps indicate completely mined out areas. The symbol that looks like a ladder indicates a mined out area where passage ways ("Mains") were first developed. Clear areas, which are inside the outcrop, were not mined as of 1935. Occasionally mine names and operator names appear around the mined out areas, however clear mine boundaries are not shown. Oil and gas wells are shown on the maps as star-like symbols.
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| Pennsylvania Department of Environmental Protection |
| 2012 |
TILE INDEX - WPA Mapping was drawn in the 1930’s as part of the “Works Progress Administration”. All mining shown on the WPA Maps is assumed to have taken place ‘Prior to 1935’. The WPA Maps were laid out based on the 15’ USGS Topographic Quadrangles, consisting of nine (9) 5' sections. The lower right corner of the WPA Maps includes the sheet name and coal seam covered by the sheet. The latitude and longitude of each corner of the WPA Map is shown. The adjacent WPA Map is listed at each corner and mid way along each edge. The contour lines on the WPA Maps indicate the elevation of the coal seam in feet “above sea level”. The coal seam outcrop is shown using a heavy black line. The outcrop is the point where the coal seam elevation and the surface elevation are equal. The speckled areas on the maps indicate completely mined out areas. The symbol that looks like a ladder indicates a mined out area where passage ways ("Mains") were first developed. Clear areas, which are inside the outcrop, were not mined as of 1935. Occasionally mine names and operator names appear around the mined out areas, however clear mine boundaries are not shown. Oil and gas wells are shown on the maps as star-like symbols.
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| Pennsylvania Department of Environmental Protection |
| 2017 |
The National Guard Bureau (NGB) required high accruacy classified LiDAR data in combination with raster digital elevation models and hydrographic breaklines. For this effort, Continental Mapping Consultants (Continental) will collect and process high accuracy classified LiDAR data in .LAS format as well as a combination of raster digital elevation models.The National Guard Bureau (NGB) requires the collection and processing of high accuracy classified LiDAR data in .LAS format as well as a combination of raster digital elevation models and additional hydrographic breaklines. The data is to be acquired during the Spring 2017 timeframe, during leaf-off conditions. The acquired LiDAR data will be used for various planning, design, research and mapping purposes. The NGB requires this data collection for Fort Indiantown Gap near Lebanon, Pennsylvania.
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| Pennsylvania Department of Military Veterans Affairs |
| 2017 |
The National Guard Bureau (NGB) required high accruacy classified LiDAR data in combination with raster digital elevation models and hydrographic breaklines. For this effort, Continental Mapping Consultants (Continental) will collect and process high accuracy classified LiDAR data in .LAS format as well as a combination of raster digital elevation models.The National Guard Bureau (NGB) requires the collection and processing of high accuracy classified LiDAR data in .LAS format as well as a combination of raster digital elevation models and additional hydrographic breaklines. The data is to be acquired during the Spring 2017 timeframe, during leaf-off conditions. The acquired LiDAR data will be used for various planning, design, research and mapping purposes. The NGB requires this data collection for Fort Indiantown Gap near Lebanon, Pennsylvania.
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| Pennsylvania Department of Military Veterans Affairs |
| 2017 |
The National Guard Bureau (NGB) required high accruacy classified LiDAR data in combination with raster digital elevation models and hydrographic breaklines. For this effort, Continental Mapping Consultants (Continental) will collect and process high accuracy classified LiDAR data in .LAS format as well as a combination of raster digital elevation models.The National Guard Bureau (NGB) requires the collection and processing of high accuracy classified LiDAR data in .LAS format as well as a combination of raster digital elevation models and additional hydrographic breaklines. The data is to be acquired during the Spring 2017 timeframe, during leaf-off conditions. The acquired LiDAR data will be used for various planning, design, research and mapping purposes. The NGB requires this data collection for Fort Indiantown Gap near Lebanon, Pennsylvania.
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| Pennsylvania Department of Military Veterans Affairs |
| 2017 |
The National Guard Bureau (NGB) required high accruacy classified LiDAR data in combination with raster digital elevation models and hydrographic breaklines. For this effort, Continental Mapping Consultants (Continental) will collect and process high accuracy classified LiDAR data in .LAS format as well as a combination of raster digital elevation models.The National Guard Bureau (NGB) requires the collection and processing of high accuracy classified LiDAR data in .LAS format as well as a combination of raster digital elevation models and additional hydrographic breaklines. The data is to be acquired during the Spring 2017 timeframe, during leaf-off conditions. The acquired LiDAR data will be used for various planning, design, research and mapping purposes. The NGB requires this data collection for Fort Indiantown Gap near Lebanon, Pennsylvania.
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| Pennsylvania Department of Military Veterans Affairs |
| 2017 |
The National Guard Bureau (NGB) required high accruacy classified LiDAR data in combination with raster digital elevation models and hydrographic breaklines. For this effort, Continental Mapping Consultants (Continental) will collect and process high accuracy classified LiDAR data in .LAS format as well as a combination of raster digital elevation models.The National Guard Bureau (NGB) requires the collection and processing of high accuracy classified LiDAR data in .LAS format as well as a combination of raster digital elevation models and additional hydrographic breaklines. The data is to be acquired during the Spring 2017 timeframe, during leaf-off conditions. The acquired LiDAR data will be used for various planning, design, research and mapping purposes. The NGB requires this data collection for Fort Indiantown Gap near Lebanon, Pennsylvania.
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| Pennsylvania Department of Military Veterans Affairs |
| 2018 |
GIS raster datasets displaying Topographic Wetness Index (TWI) for Adams, Cumberland, Dauphin, Franklin, Lancaster, and York Counties, PA. The TWI rasters were derived from 2016 LiDAR for Dauphin County, 2015 LiDAR for Lancaster and York Counties, and 2006-08 LiDAR for Adams, Cumberland, and Franklin Counties. The TWI rasters were derived from 2015 LiDAR for Lancaster and York Counties and 2006-08 LiDAR for Adams and Franklin Counties. The TauDEM extension (D-Infinity tools) for ArcMap was used to create flow direction, slope, and contributing area rasters. TWI was then calculated using the following equation: Ln (Contributing Area/Slope). The methodology was described by Cody Fink in his 2013 thesis entitled Dynamic Soil Property Change in Response to Natural Gas Development in Pennsylvania. TWI results in a dimensionless raster and should be displayed using a red (low values representing no flow) to blue (high, representing high probability flowpaths) color gradient. TWI results vary depending on raster size and analysis options so value thresholds for probability-based overland flowpaths for water should be field verified.
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| Susquehanna River Basin Commission SRBC |
| 2017 |
The National High Altitude Photography (NHAP) program was coordinated by the USGS as an interagency project to acquire cloud-free aerial photographs at an altitude of 40,000 feet above mean terrain elevation. Two different camera systems were used to obtain simultaneous coverage of black-and-white (BW) and color infrared (CIR) aerial photographs over the conterminous United States. The color-infrared photographs were taken with an 8.25-inch focal length lens and are at a scale of 1:58,000. The black-and-white photographs were taken with a 6-inch focal length lens and are at a scale of 1:80,000. The NHAP program, which was operational from 1980 to 1989, consists of approximately 500,000 images. Photographs were acquired on 9-inch film and centered over USGS 7.5-minute quadrangles. Not Georeferenced. Statewide historic aerial images for Pennsylvania. Color-infrared photographs from the National High Altitude Photography (NHAP) program, conducted by the USGS. Pennsylvaina imagery was captured between 03/27/1980 & 05/13/1987. The USGS "The National High Altitude Photography (NHAP) program, which was operated from 1980-1989, was coordinated by the U.S. Geological Survey as an interagency project to eliminate duplicate photography in various Government programs. The aim of the program was to cover the 48 conterminous states over a 5-year span. In the NHAP program, black-and-white and color-infrared aerial photographs were obtained on 9-inch film from an altitude of 40,000 feet above mean terrain elevation and are centered over USGS 7.5-minute quadrangles. The color-infrared photographs are at a scale of 1:58,000 (1 inch equals about .9 miles). All NHAP flights were flown in a North to South direction. These photographs are offered as digital images" (https://catalog.data.gov/dataset/nhap-national-high-altitude-aerial-photography-1980-1989 , April 2017). In 2016, Donald W. Hamer Center for Maps & Geospatial Information at The Pennsylvania State University obtained high quality digital images of 9x9 film from USDA - FSA Aerial Photography Field Office (APFO). Digital images were captured at 2,032 dpi with Wehrli and Associates, Inc. RM-6 and RM-3 photogrammetric scanners. The complete collection of 2,607 images contain 60% forward and 30% side to side overlapping coverage for all of Pennsylvania.
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| The Pennsylvania State University |
| 2017 |
Lake Erie Watershed 2015 Ortho/LiDAR/Hydro Project will consist the following: • New project – wide 1”=100’ scale color digital orthoimagery (with a 6-inch pixel resolution) • New project wide 0.7-meter LiDAR (average point density) • New project wide hydrology • Crest Delineation This task is for a high resolution data set of lidar covering approximately 512 square miles of the Lake Erie Shoreline, PA. The lidar data was acquired and processed under the requirements identified in this task order. Lidar data is a remotely sensed high resolution elevation data collected by an airborne platform. The lidar sensor uses a combination of laser range finding, GPS positioning, and inertial measurement technologies. The lidar systems collect data point clouds that are used to produce highly detailed Digital Elevation Models (DEMs) of the earth's terrain, man-made structures, and vegetation. The task required the LiDAR data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. The final products include classified LAS, 2.5' pixel raster DEMs of the bare-earth surface in ERDAS IMG Format. Each LAS file contains lidar point information, which has been calibrated, controlled, and classified. Additional deliverables include hydrologic breakline data, 8-bit intensity images, control data, tile index, lidar processing and survey reports in PDF format, FGDC metadata files for each data deliverable in .xml format. Ground conditions: Water at normal levels; no unusual inundation; no snow; leaf off. To better understand one of the state’s most vital natural resources and accurately plan for the future, the Pennsylvania Department of Environmental Protection (PADEP), through grant funding provided to the Pennsylvania Sea Grant (PASG) College Program, partnered with Woolpert to acquire imagery and lidar data for the entire Pennsylvania Lake Erie Watershed and all 77 miles of shoreline. - See more at: http://www.xyht.com/aerialuas/heights-april-2017-mapping-the-pennsylvania-lake-erie-watershed/#sthash.n3pVphR6.dpuf
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| The Pennsylvania State University |
| 2017 |
Lake Erie Watershed 2015 Ortho/LiDAR/Hydro Project will consist the following: • New project – wide 1”=100’ scale color digital orthoimagery (with a 6-inch pixel resolution) • New project wide 0.7-meter LiDAR (average point density) • New project wide hydrology • Crest Delineation This task is for a high resolution data set of lidar covering approximately 512 square miles of the Lake Erie Shoreline, PA. The lidar data was acquired and processed under the requirements identified in this task order. Lidar data is a remotely sensed high resolution elevation data collected by an airborne platform. The lidar sensor uses a combination of laser range finding, GPS positioning, and inertial measurement technologies. The lidar systems collect data point clouds that are used to produce highly detailed Digital Elevation Models (DEMs) of the earth's terrain, man-made structures, and vegetation. The task required the LiDAR data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. The final products include classified LAS, 2.5' pixel raster DEMs of the bare-earth surface in ERDAS IMG Format. Each LAS file contains lidar point information, which has been calibrated, controlled, and classified. Additional deliverables include hydrologic breakline data, 8-bit intensity images, control data, tile index, lidar processing and survey reports in PDF format, FGDC metadata files for each data deliverable in .xml format. Ground conditions: Water at normal levels; no unusual inundation; no snow; leaf off. To better understand one of the state’s most vital natural resources and accurately plan for the future, the Pennsylvania Department of Environmental Protection (PADEP), through grant funding provided to the Pennsylvania Sea Grant (PASG) College Program, partnered with Woolpert to acquire imagery and lidar data for the entire Pennsylvania Lake Erie Watershed and all 77 miles of shoreline. - See more at: http://www.xyht.com/aerialuas/heights-april-2017-mapping-the-pennsylvania-lake-erie-watershed/#sthash.n3pVphR6.dpuf
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| The Pennsylvania State University |
| 2017 |
Lake Erie Watershed 2015 Ortho/LiDAR/Hydro Project will consist the following: • New project – wide 1”=100’ scale color digital orthoimagery (with a 6-inch pixel resolution) • New project wide 0.7-meter LiDAR (average point density) • New project wide hydrology • Crest Delineation This task is for a high resolution data set of lidar covering approximately 512 square miles of the Lake Erie Shoreline, PA. The lidar data was acquired and processed under the requirements identified in this task order. Lidar data is a remotely sensed high resolution elevation data collected by an airborne platform. The lidar sensor uses a combination of laser range finding, GPS positioning, and inertial measurement technologies. The lidar systems collect data point clouds that are used to produce highly detailed Digital Elevation Models (DEMs) of the earth's terrain, man-made structures, and vegetation. The task required the LiDAR data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. The final products include classified LAS, 2.5' pixel raster DEMs of the bare-earth surface in ERDAS IMG Format. Each LAS file contains lidar point information, which has been calibrated, controlled, and classified. Additional deliverables include hydrologic breakline data, 8-bit intensity images, control data, tile index, lidar processing and survey reports in PDF format, FGDC metadata files for each data deliverable in .xml format. Ground conditions: Water at normal levels; no unusual inundation; no snow; leaf off. To better understand one of the state’s most vital natural resources and accurately plan for the future, the Pennsylvania Department of Environmental Protection (PADEP), through grant funding provided to the Pennsylvania Sea Grant (PASG) College Program, partnered with Woolpert to acquire imagery and lidar data for the entire Pennsylvania Lake Erie Watershed and all 77 miles of shoreline. - See more at: http://www.xyht.com/aerialuas/heights-april-2017-mapping-the-pennsylvania-lake-erie-watershed/#sthash.n3pVphR6.dpuf
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| The Pennsylvania State University |
| 2017 |
Lake Erie Watershed 2015 Ortho/LiDAR/Hydro Project will consist the following: • New project – wide 1”=100’ scale color digital orthoimagery (with a 6-inch pixel resolution) • New project wide 0.7-meter LiDAR (average point density) • New project wide hydrology • Crest Delineation This task is for a high resolution data set of lidar covering approximately 512 square miles of the Lake Erie Shoreline, PA. The lidar data was acquired and processed under the requirements identified in this task order. Lidar data is a remotely sensed high resolution elevation data collected by an airborne platform. The lidar sensor uses a combination of laser range finding, GPS positioning, and inertial measurement technologies. The lidar systems collect data point clouds that are used to produce highly detailed Digital Elevation Models (DEMs) of the earth's terrain, man-made structures, and vegetation. The task required the LiDAR data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. The final products include classified LAS, 2.5' pixel raster DEMs of the bare-earth surface in ERDAS IMG Format. Each LAS file contains lidar point information, which has been calibrated, controlled, and classified. Additional deliverables include hydrologic breakline data, 8-bit intensity images, control data, tile index, lidar processing and survey reports in PDF format, FGDC metadata files for each data deliverable in .xml format. Ground conditions: Water at normal levels; no unusual inundation; no snow; leaf off. To better understand one of the state’s most vital natural resources and accurately plan for the future, the Pennsylvania Department of Environmental Protection (PADEP), through grant funding provided to the Pennsylvania Sea Grant (PASG) College Program, partnered with Woolpert to acquire imagery and lidar data for the entire Pennsylvania Lake Erie Watershed and all 77 miles of shoreline. - See more at: http://www.xyht.com/aerialuas/heights-april-2017-mapping-the-pennsylvania-lake-erie-watershed/#sthash.n3pVphR6.dpuf
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| The Pennsylvania State University |
| 2017 |
Lake Erie Watershed 2015 Ortho/LiDAR/Hydro Project will consist the following: • New project – wide 1”=100’ scale color digital orthoimagery (with a 6-inch pixel resolution) • New project wide 0.7-meter LiDAR (average point density) • New project wide hydrology • Crest Delineation This task is for a high resolution data set of lidar covering approximately 512 square miles of the Lake Erie Shoreline, PA. The lidar data was acquired and processed under the requirements identified in this task order. Lidar data is a remotely sensed high resolution elevation data collected by an airborne platform. The lidar sensor uses a combination of laser range finding, GPS positioning, and inertial measurement technologies. The lidar systems collect data point clouds that are used to produce highly detailed Digital Elevation Models (DEMs) of the earth's terrain, man-made structures, and vegetation. The task required the LiDAR data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. The final products include classified LAS, 2.5' pixel raster DEMs of the bare-earth surface in ERDAS IMG Format. Each LAS file contains lidar point information, which has been calibrated, controlled, and classified. Additional deliverables include hydrologic breakline data, 8-bit intensity images, control data, tile index, lidar processing and survey reports in PDF format, FGDC metadata files for each data deliverable in .xml format. Ground conditions: Water at normal levels; no unusual inundation; no snow; leaf off. To better understand one of the state’s most vital natural resources and accurately plan for the future, the Pennsylvania Department of Environmental Protection (PADEP), through grant funding provided to the Pennsylvania Sea Grant (PASG) College Program, partnered with Woolpert to acquire imagery and lidar data for the entire Pennsylvania Lake Erie Watershed and all 77 miles of shoreline. - See more at: http://www.xyht.com/aerialuas/heights-april-2017-mapping-the-pennsylvania-lake-erie-watershed/#sthash.n3pVphR6.dpuf
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| The Pennsylvania State University |
| 2017 |
Lake Erie Watershed 2015 Ortho/LiDAR/Hydro Project will consist the following: • New project – wide 1”=100’ scale color digital orthoimagery (with a 6-inch pixel resolution) • New project wide 0.7-meter LiDAR (average point density) • New project wide hydrology • Crest Delineation This task is for a high resolution data set of lidar covering approximately 512 square miles of the Lake Erie Shoreline, PA. The lidar data was acquired and processed under the requirements identified in this task order. Lidar data is a remotely sensed high resolution elevation data collected by an airborne platform. The lidar sensor uses a combination of laser range finding, GPS positioning, and inertial measurement technologies. The lidar systems collect data point clouds that are used to produce highly detailed Digital Elevation Models (DEMs) of the earth's terrain, man-made structures, and vegetation. The task required the LiDAR data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. The final products include classified LAS, 2.5' pixel raster DEMs of the bare-earth surface in ERDAS IMG Format. Each LAS file contains lidar point information, which has been calibrated, controlled, and classified. Additional deliverables include hydrologic breakline data, 8-bit intensity images, control data, tile index, lidar processing and survey reports in PDF format, FGDC metadata files for each data deliverable in .xml format. Ground conditions: Water at normal levels; no unusual inundation; no snow; leaf off. To better understand one of the state’s most vital natural resources and accurately plan for the future, the Pennsylvania Department of Environmental Protection (PADEP), through grant funding provided to the Pennsylvania Sea Grant (PASG) College Program, partnered with Woolpert to acquire imagery and lidar data for the entire Pennsylvania Lake Erie Watershed and all 77 miles of shoreline. - See more at: http://www.xyht.com/aerialuas/heights-april-2017-mapping-the-pennsylvania-lake-erie-watershed/#sthash.n3pVphR6.dpuf
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| The Pennsylvania State University |
| 2017 |
Lake Erie Watershed 2015 Ortho/LiDAR/Hydro Project will consist the following: • New project – wide 1”=100’ scale color digital orthoimagery (with a 6-inch pixel resolution) • New project wide 0.7-meter LiDAR (average point density) • New project wide hydrology • Crest Delineation This task is for a high resolution data set of lidar covering approximately 512 square miles of the Lake Erie Shoreline, PA. The lidar data was acquired and processed under the requirements identified in this task order. Lidar data is a remotely sensed high resolution elevation data collected by an airborne platform. The lidar sensor uses a combination of laser range finding, GPS positioning, and inertial measurement technologies. The lidar systems collect data point clouds that are used to produce highly detailed Digital Elevation Models (DEMs) of the earth's terrain, man-made structures, and vegetation. The task required the LiDAR data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. The final products include classified LAS, 2.5' pixel raster DEMs of the bare-earth surface in ERDAS IMG Format. Each LAS file contains lidar point information, which has been calibrated, controlled, and classified. Additional deliverables include hydrologic breakline data, 8-bit intensity images, control data, tile index, lidar processing and survey reports in PDF format, FGDC metadata files for each data deliverable in .xml format. Ground conditions: Water at normal levels; no unusual inundation; no snow; leaf off. To better understand one of the state’s most vital natural resources and accurately plan for the future, the Pennsylvania Department of Environmental Protection (PADEP), through grant funding provided to the Pennsylvania Sea Grant (PASG) College Program, partnered with Woolpert to acquire imagery and lidar data for the entire Pennsylvania Lake Erie Watershed and all 77 miles of shoreline. - See more at: http://www.xyht.com/aerialuas/heights-april-2017-mapping-the-pennsylvania-lake-erie-watershed/#sthash.n3pVphR6.dpuf
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| The Pennsylvania State University |
| 2025 |
This dataset is a compilation of airborne lidar derived digital elevation models for Pennsylvania, organized by HUC8 watershed boundaries and sampled at 3 m resolution. Source data was downloaded from the US Geological Survey National Map, primarily from the 2019 Pennsylvania 3D Elevation Program lidar survey, but supplemented with other available datasets where needed to ensure continuous coverage. This project was funded by the Pennsylvania Department of Environmental Protection (PADEP) through its Water Program. April 2025.
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| The Pennsylvania State University |
| 2025 |
This dataset represents the upstream flow accumulation, or contributing drainage area, in units of square meters, calculated from the dataset “Pennsylvania 3m lidar digital elevation models 2019”, organized by HUC8 watershed. Flow accumulation was calculated using the “carve” approach in TopoToolbox (Schwanghart and Scherler, 2014). Flow accumulation does not account for incoming flow from outside HUC8 regions, and so should be used with caution when interpreting large trunk streams that cross HUC 8 regions. This project was funded by the Pennsylvania Department of Environmental Protection (PADEP) through its Water Program. April 2025. Schwanghart, W., Scherler, D., 2014. TopoToolbox 2 – MATLAB-based software for topographic analysis and modeling in Earth surface sciences. Earth Surface Dynamics, 2, 1-7. https://doi.org/10.5194/esurf-2-1-2014
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| The Pennsylvania State University |
| 2025 |
Geomorphons (geomorphologic phonotypes) are landforms computed from a digital elevation model based on the principle of pattern recognition and the concept of computer line of sight (Jasiewicz and Stepinski 2013). This geomorphon map was calculated using ArcGIS Pro following the same approach as the dataset “Pennsylvania Geomorphon Landform Maps 2021”, but using the topographic dataset “Pennsylvania 3m lidar digital elevation models 2019”.
The final product includes 10 most common landforms: flat (FL - 1), peak (PK- 2), ridge (RI - 3), shoulder (SH - 4), spur (SP - 5), slope (SL -6), hollow (HL - 7), footslope (FS - 8), valley (VL - 9), and pit (PT - 10). This project was funded by the Pennsylvania Department of Environmental Protection (PADEP) through its Water Program. April 2025.
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| The Pennsylvania State University |
| 2025 |
This dataset represents local slope angle in units of degrees, calculated from the dataset “Pennsylvania 3m lidar digital elevation models 2019”, organized by HUC8 watershed. Slope was calculated using the Spatial Analyst Slope tool in ArcGIS Pro. This project was funded by the Pennsylvania Department of Environmental Protection (PADEP) through its Water Program. April 2025.
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| The Pennsylvania State University |
| 2000 |
This layer represents a potential habitat model for birds in Pennsylvania at 30 meter resolution. The model associates occurrence of suitable habitat with key environmental factors that can be mapped over the entire region. These key factors include vegetative land cover, presence of human activity, elevation, topographic position, wetland characteristics and stream size and proximity. Areas of potential species presence were tabulated based on current and historical information and a series of conditional statements proceeded using layers derived to depict the key factors on a landscape scale.
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| The Pennsylvania State University |
| 2000 |
This layer represents a potential habitat model for birds in Pennsylvania at 90 meter resolution. The model associates occurrence of suitable habitat with key environmental factors that can be mapped over the entire region. These key factors include vegetative land cover, presence of human activity, elevation, topographic position, wetland characteristics and stream size and proximity. Areas of potential species presence were tabulated based on current and historical information and a series of conditional statements proceeded using layers derived to depict the key factors on a landscape scale.
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| The Pennsylvania State University |
| 2000 |
This layer represents a potential habitat model for Fish in Pennsylvania at 90 meter resolution. The model associates occurrence of suitable habitat with key environmental factors that can be mapped over the entire region. These key factors include vegetative land cover, presence of human activity, elevation, topographic position, wetland characteristics and stream size and proximity. Areas of potential species presence were tabulated based on current and historical information and a series of conditional statements proceeded using layers derived to depict the key factors on a landscape scale.
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| The Pennsylvania State University |
| 2000 |
This layer represents a potential habitat model for Herpetilies in Pennsylvania at 30 meter resolution. The model associates occurrence of suitable habitat with key environmental factors that can be mapped over the entire region. These key factors include vegetative land cover, presence of human activity, elevation, topographic position, wetland characteristics and stream size and proximity. Areas of potential species presence were tabulated based on current and historical information and a series of conditional statements proceeded using layers derived to depict the key factors on a landscape scale.
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| The Pennsylvania State University |
| 2000 |
This layer represents a potential habitat model for Herpetilies in Pennsylvania at 90 meter resolution. The model associates occurrence of suitable habitat with key environmental factors that can be mapped over the entire region. These key factors include vegetative land cover, presence of human activity, elevation, topographic position, wetland characteristics and stream size and proximity. Areas of potential species presence were tabulated based on current and historical information and a series of conditional statements proceeded using layers derived to depict the key factors on a landscape scale.
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| The Pennsylvania State University |
| 2000 |
This layer represents a potential habitat model for Mammals in Pennsylvania at 30 meter resolution. The model associates occurrence of suitable habitat with key environmental factors that can be mapped over the entire region. These key factors include vegetative land cover, presence of human activity, elevation, topographic position, wetland characteristics and stream size and proximity. Areas of potential species presence were tabulated based on current and historical information and a series of conditional statements proceeded using layers derived to depict the key factors on a landscape scale.
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| The Pennsylvania State University |
| 2000 |
This layer represents a potential habitat model for Mammals in Pennsylvania at 90 meter resolution. The model associates occurrence of suitable habitat with key environmental factors that can be mapped over the entire region. These key factors include vegetative land cover, presence of human activity, elevation, topographic position, wetland characteristics and stream size and proximity. Areas of potential species presence were tabulated based on current and historical information and a series of conditional statements proceeded using layers derived to depict the key factors on a landscape scale.
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| The Pennsylvania State University |
| 2020 |
GIS raster datasets displaying Topographic Wetness Index (TWI) for Pennsylvania by County. TWI raster datasets were derived from 2006-2008 LiDAR (Light Detection and Ranging) elevation points produced by the PAMAP Program. The coordinate system for blocks in the northern half of the state is Pennsylvania State Plane North (datum: NAD83, units: feet); blocks in the southern half are in Pennsylvania State Plane South. Raster spatial resolution is 9.6 ft (approximately 3 m).
The TWI, also called Compound Topographic Index (CTI) or Topographic Convergence Index (TCI), is a hydrological-based topographic index that describes the tendency of a cell or area to accumulate and retain water under steady-state conditions. TWI is defined as Ln(Contributing Area/Slope angle). It balances contributing areas capturing the tendency to receive water versus slope angles capturing the tendency to evacuate water. An automated procedure was developed in ArcMap® for the TWI computation. Contributing areas (i.e. cumulative contributing area per unit contour length) were determined based on the D-Infinity model proposed by Tarboton, D. (1997). Lengths were measured considering cell size and whether the direction is adjacent or diagonal. Land surface slope was computed using the Horn’s method.
The project was funded by the Pennsylvania Department of Environmental Protection (PADEP) through its Water Program. August 2020.
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| The Pennsylvania State University |
| 1996 |
30-meter contours, digital elevation model for the geographic
area coverage of the Spring Creek Watershed
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| The Pennsylvania State University |
| 2026 |
Spatial features stewarded within the FSVeg Spatial application are organized in a hierarchy. Vegetation polygons and sample points represent the base level spatial features. Sample points fall within their parent vegetation polygon. Vegetation polygons are organized into locations. Locations fall within a ranger district and ranger districts fall within a proclaimed forest. There may be one or more proclaimed forests within the administrative forest. Finally, a region oversees the administrative forests within their geographic area. Location polygons are derived by dissolving the vegetation polygons within the NRIS_VegPoly feature class where the location identifiers are the same. A location thus represents an organized collection of vegetation polygons. National Forests will either define locations based on watershed boundaries or for management convenience based on roads or other natural features. Locations based on roads and/or other features are typically referred to as compartments.
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| U S Department of Agriculture |
| 2026 |
This feature class depicts warrants and lots within and immediately outside the proclamation boundary of the Allegheny National Forest (ANF).
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| U S Department of Agriculture |
| 2026 |
Management Areas on the Allegheny National Forest (ANF) are areas with a unique emphasis, a desired condition, a list of suitable uses, and standards and guidelines.
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| U S Department of Agriculture |
| 2026 |
The aim of landscape ecosystem classification and mapping is to distinguish appropritely sized ecosystems - useful and functional land units that differ significantly from one another in abiotic characteristics as well as their related biotic components. This subdivision of a large area into distinctive landscape ecosystems provides a much needed framework for integrated resource management planning; for biological conservation; and for comparison of differences in composition, occurrence, interactions, and productivity of plants and animals among ecosystems on the Allegheny National Forest (ANF).
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| U S Department of Agriculture |
| 2000 |
This map layer shows polygons of average annual precipitation in the
contiguous United States, for the climatological period 1961-1990.
Parameter-elevation Regressions on Independent Slopes Model (PRISM)
derived raster data is the underlying data set from which the polygons
and vectors were created. PRISM is an analytical model that uses point
data and a digital elevation model (DEM) to generate gridded estimates
of annual, monthly and event-based climatic parameters
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| U S Department of Agriculture |
| 2004 |
This map layer is commonly called Bailey's ecoregions and shows
ecosystems of regional extent in the United States, Puerto Rico, and the
U.S. Virgin Islands. Four levels of detail are included to show a
hierarchy of ecosystems. The largest ecosystems are domains, which are
groups of related climates and which are differentiated based on
precipitation and temperature. Divisions represent the climates within
domains and are differentiated based on precipitation levels and patterns
as well as temperature. Divisions are subdivided into provinces, which
are differentiated based on vegetation or other natural land covers. The
finest level of detail is described by subregions, called sections, which
are subdivisions of provinces based on terrain features. Also identified
are mountainous areas that exhibit different ecological zones based on
elevation.
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| U S Department of Agriculture |
| 2002 |
The USDA, NASS Cropland Data Layer (CDL) is a raster, geo-referenced, crop-specific land cover data layer. The CDL has a ground resolution of 30 meters. The CDL is produced using satellite imagery from the Landsat 8 OLI/TIRS sensor, Landsat 7 ETM+ sensor, and the Disaster Monitoring Constellation (DMC) DEIMOS-1 and UK2 sensors collected during the current growing season. Some CDL states used additional satellite imagery and ancillary inputs to supplement and improve the classification. These additional sources can include the United States Geological Survey (USGS) National Elevation Dataset (NED), the imperviousness and canopy data layers from the USGS National Land Cover Database 2006 (NLCD 2006), and the National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) 250 meter 16 day Normalized Difference Vegetation Index (NDVI) composites. Agricultural training and validation data are derived from the Farm Service Agency (FSA) Common Land Unit (CLU) Program. The NLCD 2006 is used as non-agricultural training and validation data. Please refer to the 'Supplemental_Information' Section of this metadata file for a complete list of all imagery, ancillary data, and training/validation data used to generate this state's CDL. The strength and emphasis of the CDL is agricultural land cover. Please note that no farmer reported data are derivable from the Cropland Data Layer.
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| U S Department of Agriculture |
| 2008 |
The USDA, NASS Cropland Data Layer (CDL) is a raster, geo-referenced, crop-specific land cover data layer. The CDL has a ground resolution of 30 meters. The CDL is produced using satellite imagery from the Landsat 8 OLI/TIRS sensor, Landsat 7 ETM+ sensor, and the Disaster Monitoring Constellation (DMC) DEIMOS-1 and UK2 sensors collected during the current growing season. Some CDL states used additional satellite imagery and ancillary inputs to supplement and improve the classification. These additional sources can include the United States Geological Survey (USGS) National Elevation Dataset (NED), the imperviousness and canopy data layers from the USGS National Land Cover Database 2006 (NLCD 2006), and the National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) 250 meter 16 day Normalized Difference Vegetation Index (NDVI) composites. Agricultural training and validation data are derived from the Farm Service Agency (FSA) Common Land Unit (CLU) Program. The NLCD 2006 is used as non-agricultural training and validation data. Please refer to the 'Supplemental_Information' Section of this metadata file for a complete list of all imagery, ancillary data, and training/validation data used to generate this state's CDL. The strength and emphasis of the CDL is agricultural land cover. Please note that no farmer reported data are derivable from the Cropland Data Layer.
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| U S Department of Agriculture |
| 2009 |
The USDA, NASS Cropland Data Layer (CDL) is a raster, geo-referenced, crop-specific land cover data layer. The CDL has a ground resolution of 30 meters. The CDL is produced using satellite imagery from the Landsat 8 OLI/TIRS sensor, Landsat 7 ETM+ sensor, and the Disaster Monitoring Constellation (DMC) DEIMOS-1 and UK2 sensors collected during the current growing season. Some CDL states used additional satellite imagery and ancillary inputs to supplement and improve the classification. These additional sources can include the United States Geological Survey (USGS) National Elevation Dataset (NED), the imperviousness and canopy data layers from the USGS National Land Cover Database 2006 (NLCD 2006), and the National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) 250 meter 16 day Normalized Difference Vegetation Index (NDVI) composites. Agricultural training and validation data are derived from the Farm Service Agency (FSA) Common Land Unit (CLU) Program. The NLCD 2006 is used as non-agricultural training and validation data. Please refer to the 'Supplemental_Information' Section of this metadata file for a complete list of all imagery, ancillary data, and training/validation data used to generate this state's CDL. The strength and emphasis of the CDL is agricultural land cover. Please note that no farmer reported data are derivable from the Cropland Data Layer.
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| U S Department of Agriculture |
| 2010 |
The USDA, NASS Cropland Data Layer (CDL) is a raster, geo-referenced, crop-specific land cover data layer. The CDL has a ground resolution of 30 meters. The CDL is produced using satellite imagery from the Landsat 8 OLI/TIRS sensor, Landsat 7 ETM+ sensor, and the Disaster Monitoring Constellation (DMC) DEIMOS-1 and UK2 sensors collected during the current growing season. Some CDL states used additional satellite imagery and ancillary inputs to supplement and improve the classification. These additional sources can include the United States Geological Survey (USGS) National Elevation Dataset (NED), the imperviousness and canopy data layers from the USGS National Land Cover Database 2006 (NLCD 2006), and the National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) 250 meter 16 day Normalized Difference Vegetation Index (NDVI) composites. Agricultural training and validation data are derived from the Farm Service Agency (FSA) Common Land Unit (CLU) Program. The NLCD 2006 is used as non-agricultural training and validation data. Please refer to the 'Supplemental_Information' Section of this metadata file for a complete list of all imagery, ancillary data, and training/validation data used to generate this state's CDL. The strength and emphasis of the CDL is agricultural land cover. Please note that no farmer reported data are derivable from the Cropland Data Layer.
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| U S Department of Agriculture |
| 2011 |
The USDA, NASS Cropland Data Layer (CDL) is a raster, geo-referenced, crop-specific land cover data layer. The CDL has a ground resolution of 30 meters. The CDL is produced using satellite imagery from the Landsat 8 OLI/TIRS sensor, Landsat 7 ETM+ sensor, and the Disaster Monitoring Constellation (DMC) DEIMOS-1 and UK2 sensors collected during the current growing season. Some CDL states used additional satellite imagery and ancillary inputs to supplement and improve the classification. These additional sources can include the United States Geological Survey (USGS) National Elevation Dataset (NED), the imperviousness and canopy data layers from the USGS National Land Cover Database 2006 (NLCD 2006), and the National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) 250 meter 16 day Normalized Difference Vegetation Index (NDVI) composites. Agricultural training and validation data are derived from the Farm Service Agency (FSA) Common Land Unit (CLU) Program. The NLCD 2006 is used as non-agricultural training and validation data. Please refer to the 'Supplemental_Information' Section of this metadata file for a complete list of all imagery, ancillary data, and training/validation data used to generate this state's CDL. The strength and emphasis of the CDL is agricultural land cover. Please note that no farmer reported data are derivable from the Cropland Data Layer.
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| U S Department of Agriculture |
| 2012 |
The USDA, NASS Cropland Data Layer (CDL) is a raster, geo-referenced, crop-specific land cover data layer. The CDL has a ground resolution of 30 meters. The CDL is produced using satellite imagery from the Landsat 8 OLI/TIRS sensor, Landsat 7 ETM+ sensor, and the Disaster Monitoring Constellation (DMC) DEIMOS-1 and UK2 sensors collected during the current growing season. Some CDL states used additional satellite imagery and ancillary inputs to supplement and improve the classification. These additional sources can include the United States Geological Survey (USGS) National Elevation Dataset (NED), the imperviousness and canopy data layers from the USGS National Land Cover Database 2006 (NLCD 2006), and the National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) 250 meter 16 day Normalized Difference Vegetation Index (NDVI) composites. Agricultural training and validation data are derived from the Farm Service Agency (FSA) Common Land Unit (CLU) Program. The NLCD 2006 is used as non-agricultural training and validation data. Please refer to the 'Supplemental_Information' Section of this metadata file for a complete list of all imagery, ancillary data, and training/validation data used to generate this state's CDL. The strength and emphasis of the CDL is agricultural land cover. Please note that no farmer reported data are derivable from the Cropland Data Layer.
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| U S Department of Agriculture |
| 2013 |
The USDA, NASS Cropland Data Layer (CDL) is a raster, geo-referenced, crop-specific land cover data layer. The CDL has a ground resolution of 30 meters. The CDL is produced using satellite imagery from the Landsat 8 OLI/TIRS sensor, Landsat 7 ETM+ sensor, and the Disaster Monitoring Constellation (DMC) DEIMOS-1 and UK2 sensors collected during the current growing season. Some CDL states used additional satellite imagery and ancillary inputs to supplement and improve the classification. These additional sources can include the United States Geological Survey (USGS) National Elevation Dataset (NED), the imperviousness and canopy data layers from the USGS National Land Cover Database 2006 (NLCD 2006), and the National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) 250 meter 16 day Normalized Difference Vegetation Index (NDVI) composites. Agricultural training and validation data are derived from the Farm Service Agency (FSA) Common Land Unit (CLU) Program. The NLCD 2006 is used as non-agricultural training and validation data. Please refer to the 'Supplemental_Information' Section of this metadata file for a complete list of all imagery, ancillary data, and training/validation data used to generate this state's CDL. The strength and emphasis of the CDL is agricultural land cover. Please note that no farmer reported data are derivable from the Cropland Data Layer.
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| U S Department of Agriculture |
| 2014 |
The USDA, NASS Cropland Data Layer (CDL) is a raster, geo-referenced, crop-specific land cover data layer. The CDL has a ground resolution of 30 meters. The CDL is produced using satellite imagery from the Landsat 8 OLI/TIRS sensor, Landsat 7 ETM+ sensor, and the Disaster Monitoring Constellation (DMC) DEIMOS-1 and UK2 sensors collected during the current growing season. Some CDL states used additional satellite imagery and ancillary inputs to supplement and improve the classification. These additional sources can include the United States Geological Survey (USGS) National Elevation Dataset (NED), the imperviousness and canopy data layers from the USGS National Land Cover Database 2006 (NLCD 2006), and the National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) 250 meter 16 day Normalized Difference Vegetation Index (NDVI) composites. Agricultural training and validation data are derived from the Farm Service Agency (FSA) Common Land Unit (CLU) Program. The NLCD 2006 is used as non-agricultural training and validation data. Please refer to the 'Supplemental_Information' Section of this metadata file for a complete list of all imagery, ancillary data, and training/validation data used to generate this state's CDL. The strength and emphasis of the CDL is agricultural land cover. Please note that no farmer reported data are derivable from the Cropland Data Layer.
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| U S Department of Agriculture |
| 2015 |
The USDA, NASS Cropland Data Layer (CDL) is a raster, geo-referenced, crop-specific land cover data layer. The CDL has a ground resolution of 30 meters. The CDL is produced using satellite imagery from the Landsat 8 OLI/TIRS sensor, Landsat 7 ETM+ sensor, and the Disaster Monitoring Constellation (DMC) DEIMOS-1 and UK2 sensors collected during the current growing season. Some CDL states used additional satellite imagery and ancillary inputs to supplement and improve the classification. These additional sources can include the United States Geological Survey (USGS) National Elevation Dataset (NED), the imperviousness and canopy data layers from the USGS National Land Cover Database 2006 (NLCD 2006), and the National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) 250 meter 16 day Normalized Difference Vegetation Index (NDVI) composites. Agricultural training and validation data are derived from the Farm Service Agency (FSA) Common Land Unit (CLU) Program. The NLCD 2006 is used as non-agricultural training and validation data. Please refer to the 'Supplemental_Information' Section of this metadata file for a complete list of all imagery, ancillary data, and training/validation data used to generate this state's CDL. The strength and emphasis of the CDL is agricultural land cover. Please note that no farmer reported data are derivable from the Cropland Data Layer.
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| U S Department of Agriculture |
| 2016 |
The USDA, NASS Cropland Data Layer (CDL) is a raster, geo-referenced, crop-specific land cover data layer. The CDL has a ground resolution of 30 meters. The CDL is produced using satellite imagery from the Landsat 8 OLI/TIRS sensor, Landsat 7 ETM+ sensor, and the Disaster Monitoring Constellation (DMC) DEIMOS-1 and UK2 sensors collected during the current growing season. Some CDL states used additional satellite imagery and ancillary inputs to supplement and improve the classification. These additional sources can include the United States Geological Survey (USGS) National Elevation Dataset (NED), the imperviousness and canopy data layers from the USGS National Land Cover Database 2006 (NLCD 2006), and the National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) 250 meter 16 day Normalized Difference Vegetation Index (NDVI) composites. Agricultural training and validation data are derived from the Farm Service Agency (FSA) Common Land Unit (CLU) Program. The NLCD 2006 is used as non-agricultural training and validation data. Please refer to the 'Supplemental_Information' Section of this metadata file for a complete list of all imagery, ancillary data, and training/validation data used to generate this state's CDL. The strength and emphasis of the CDL is agricultural land cover. Please note that no farmer reported data are derivable from the Cropland Data Layer.
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| U S Department of Agriculture |
| 2017 |
The USDA, NASS Cropland Data Layer (CDL) is a raster, geo-referenced, crop-specific land cover data layer. The CDL has a ground resolution of 30 meters. The CDL is produced using satellite imagery from the Landsat 8 OLI/TIRS sensor, Landsat 7 ETM+ sensor, and the Disaster Monitoring Constellation (DMC) DEIMOS-1 and UK2 sensors collected during the current growing season. Some CDL states used additional satellite imagery and ancillary inputs to supplement and improve the classification. These additional sources can include the United States Geological Survey (USGS) National Elevation Dataset (NED), the imperviousness and canopy data layers from the USGS National Land Cover Database 2006 (NLCD 2006), and the National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) 250 meter 16 day Normalized Difference Vegetation Index (NDVI) composites. Agricultural training and validation data are derived from the Farm Service Agency (FSA) Common Land Unit (CLU) Program. The NLCD 2006 is used as non-agricultural training and validation data. Please refer to the 'Supplemental_Information' Section of this metadata file for a complete list of all imagery, ancillary data, and training/validation data used to generate this state's CDL. The strength and emphasis of the CDL is agricultural land cover. Please note that no farmer reported data are derivable from the Cropland Data Layer.
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| U S Department of Agriculture |
| 2018 |
The USDA, NASS Cropland Data Layer (CDL) is a raster, geo-referenced, crop-specific land cover data layer. The CDL has a ground resolution of 30 meters. The CDL is produced using satellite imagery from the Landsat 8 OLI/TIRS sensor, Landsat 7 ETM+ sensor, and the Disaster Monitoring Constellation (DMC) DEIMOS-1 and UK2 sensors collected during the current growing season. Some CDL states used additional satellite imagery and ancillary inputs to supplement and improve the classification. These additional sources can include the United States Geological Survey (USGS) National Elevation Dataset (NED), the imperviousness and canopy data layers from the USGS National Land Cover Database 2006 (NLCD 2006), and the National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) 250 meter 16 day Normalized Difference Vegetation Index (NDVI) composites. Agricultural training and validation data are derived from the Farm Service Agency (FSA) Common Land Unit (CLU) Program. The NLCD 2006 is used as non-agricultural training and validation data. Please refer to the 'Supplemental_Information' Section of this metadata file for a complete list of all imagery, ancillary data, and training/validation data used to generate this state's CDL. The strength and emphasis of the CDL is agricultural land cover. Please note that no farmer reported data are derivable from the Cropland Data Layer.
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| U S Department of Agriculture |
| 2019 |
The USDA, NASS Cropland Data Layer (CDL) is a raster, geo-referenced, crop-specific land cover data layer. The CDL has a ground resolution of 30 meters. The CDL is produced using satellite imagery from the Landsat 8 OLI/TIRS sensor, Landsat 7 ETM+ sensor, and the Disaster Monitoring Constellation (DMC) DEIMOS-1 and UK2 sensors collected during the current growing season. Some CDL states used additional satellite imagery and ancillary inputs to supplement and improve the classification. These additional sources can include the United States Geological Survey (USGS) National Elevation Dataset (NED), the imperviousness and canopy data layers from the USGS National Land Cover Database 2006 (NLCD 2006), and the National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) 250 meter 16 day Normalized Difference Vegetation Index (NDVI) composites. Agricultural training and validation data are derived from the Farm Service Agency (FSA) Common Land Unit (CLU) Program. The NLCD 2006 is used as non-agricultural training and validation data. Please refer to the 'Supplemental_Information' Section of this metadata file for a complete list of all imagery, ancillary data, and training/validation data used to generate this state's CDL. The strength and emphasis of the CDL is agricultural land cover. Please note that no farmer reported data are derivable from the Cropland Data Layer.
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| U S Department of Agriculture |
| 2020 |
The USDA, NASS Cropland Data Layer (CDL) is a raster, geo-referenced, crop-specific land cover data layer. The CDL has a ground resolution of 30 meters. The CDL is produced using satellite imagery from the Landsat 8 OLI/TIRS sensor, Landsat 7 ETM+ sensor, and the Disaster Monitoring Constellation (DMC) DEIMOS-1 and UK2 sensors collected during the current growing season. Some CDL states used additional satellite imagery and ancillary inputs to supplement and improve the classification. These additional sources can include the United States Geological Survey (USGS) National Elevation Dataset (NED), the imperviousness and canopy data layers from the USGS National Land Cover Database 2006 (NLCD 2006), and the National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) 250 meter 16 day Normalized Difference Vegetation Index (NDVI) composites. Agricultural training and validation data are derived from the Farm Service Agency (FSA) Common Land Unit (CLU) Program. The NLCD 2006 is used as non-agricultural training and validation data. Please refer to the 'Supplemental_Information' Section of this metadata file for a complete list of all imagery, ancillary data, and training/validation data used to generate this state's CDL. The strength and emphasis of the CDL is agricultural land cover. Please note that no farmer reported data are derivable from the Cropland Data Layer.
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| U S Department of Agriculture |
| 2021 |
The USDA, NASS Cropland Data Layer (CDL) is a raster, geo-referenced, crop-specific land cover data layer. The CDL has a ground resolution of 30 meters. The CDL is produced using satellite imagery from the Landsat 8 OLI/TIRS sensor, Landsat 7 ETM+ sensor, and the Disaster Monitoring Constellation (DMC) DEIMOS-1 and UK2 sensors collected during the current growing season. Some CDL states used additional satellite imagery and ancillary inputs to supplement and improve the classification. These additional sources can include the United States Geological Survey (USGS) National Elevation Dataset (NED), the imperviousness and canopy data layers from the USGS National Land Cover Database 2006 (NLCD 2006), and the National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) 250 meter 16 day Normalized Difference Vegetation Index (NDVI) composites. Agricultural training and validation data are derived from the Farm Service Agency (FSA) Common Land Unit (CLU) Program. The NLCD 2006 is used as non-agricultural training and validation data. Please refer to the 'Supplemental_Information' Section of this metadata file for a complete list of all imagery, ancillary data, and training/validation data used to generate this state's CDL. The strength and emphasis of the CDL is agricultural land cover. Please note that no farmer reported data are derivable from the Cropland Data Layer.
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| U S Department of Agriculture |
| 2025 |
The USDA National Agricultural Statistics Service (NASS) Cropland Data Layer (CDL) is an annual raster, geo-referenced, crop-specific land cover data layer produced using satellite imagery and extensive agricultural ground reference data. The program began in 1997 with limited coverage and in 2008 forward expanded coverage to the entire Continental United States. Please note that no farmer reported data are derivable from the Cropland Data Layer.
New for the 2024 10-meter CDL, the crop classification utilized remote sensing data from harmonized Sentinel-2 MSI Level-2A, Landsat 8, and Landsat 9 Level-2 Collection 2 Tier-1 products, providing surface reflectance (SR) data across multiple spectral bands, including GREEN, RED, NIR, SWIR1, SWIR2, and RedEdge bands 1-4. To mitigate cloud cover, 10-day median composites of surface reflectance and NDVI were created from the cloud-masked Landsat-Sentinel multi-sensor data for the growing season of 2024. An impervious layer from USGS NLCD 2021 and a digital elevation model from USGS 3DEP were also included ancillary input variables. In addition, mixed sampling strategies and localized training and were applied to the 2024 10m CDL production. Additional information: Z. Li, R. Mueller, Z. Yang, D. Johnson and P. Willis, "Cloud-Powered Agricultural Mapping: A Revolution Toward 10m Resolution Cropland Data Layers," IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, Athens, Greece, 2024, pp. 4081-4084, doi: 10.1109/IGARSS53475.2024.10641079. PDF available at .
The 2024 CDL has a spatial resolution of 10 meters and was produced using satellite imagery from Landsat 8 and 9 OLI/TIRS and ESA SENTINEL-2A and -2B collected throughout the growing season. Additional ancillary inputs were used to supplement and improve the land cover classification including the United States Geological Survey (USGS) 3D Elevation Program (3DEP) Elevation Dataset (NED), and the USGS National Land Cover Database imperviousness data layer. Agricultural training and validation data are derived from the Farm Service Agency (FSA) Common Land Unit (CLU) Program. Some CDL states incorporate additional crop-specific ground reference obtained from the following non-FSA sources which are detailed in the 'Lineage' Section of this metadata: US Bureau of Reclamation, NASS Citrus Data Layer (internal use only), California Department of Water Resources, Florida Department of Agriculture and Consumer Services Office of Agricultural Water Policy, Cornell University grape/vineyard data, Utah Department of Water Resources, and Washington State Department of Agriculture. The 2021 NLCD was used as non-agricultural training and validation data for the 2024 CDL. Please visit the CDL FAQs and metadata webpages at to view a complete list of imagery, ancillary inputs, and ground reference used for a specific state and year.
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| U S Department of Agriculture |
| 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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| 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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| 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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| U S Geological Survey |
| 2025 |
The 3D Hydrography Program (3DHP) data is an integrated, National, 3D-enabled hydrologic dataset derived from the USGS 3D Elevation Program (3DEP) data. For areas where Elevation-derived Hydrography (EDH) has not yet been collected, 3DHP data is supplemented by hydrologic vector data from the National Hydrography Dataset (NHD). As further EDH data is collected, it will replace the NHD data in those areas. 3DHP data ingested from EDH sources includes ‘value added’ catchments and flowline network derivative attributes. All the data is open and non-proprietary. However, users should be aware that temporal changes may have occurred since this dataset was collected and that some parts of this data may no longer represent actual surface conditions. Users should not use this data for critical applications without a full awareness of its limitations. This dataset is not intended to be used for site-specific regulatory determinations. 3DHP datasets include a three-dimensional (3D) hydrography network generated from, and integrated with, elevation data from the 3DEP to better represent stream gradients and channel conditions, along with waterbodies, hydrologic units, hydrologically enhanced elevation and other surfaces, and more consistent and accurate attributes. This product is new in federal fiscal year 2025 (FY25), and consists only of vector data in a series of feature classes. The product represents the 3DHP dataset and the schema in which it is contained as of September 30, 2024 Future Annual Staged Product releases will reflect the schema at the time the product is generated and include more EDH-sourced data holdings.
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| U S Geological Survey |
| 2025 |
The 3D Hydrography Program (3DHP) data is an integrated, National, 3D-enabled hydrologic dataset derived from the USGS 3D Elevation Program (3DEP) data. For areas where Elevation-derived Hydrography (EDH) has not yet been collected, 3DHP data is supplemented by hydrologic vector data from the National Hydrography Dataset (NHD). As further EDH data is collected, it will replace the NHD data in those areas. 3DHP data ingested from EDH sources includes ‘value added’ catchments and flowline network derivative attributes. All the data is open and non-proprietary. However, users should be aware that temporal changes may have occurred since this dataset was collected and that some parts of this data may no longer represent actual surface conditions. Users should not use this data for critical applications without a full awareness of its limitations. This dataset is not intended to be used for site-specific regulatory determinations. 3DHP datasets include a three-dimensional (3D) hydrography network generated from, and integrated with, elevation data from the 3DEP to better represent stream gradients and channel conditions, along with waterbodies, hydrologic units, hydrologically enhanced elevation and other surfaces, and more consistent and accurate attributes. This product is new in federal fiscal year 2025 (FY25), and consists only of vector data in a series of feature classes. The product represents the 3DHP dataset and the schema in which it is contained as of September 30, 2024 Future Annual Staged Product releases will reflect the schema at the time the product is generated and include more EDH-sourced data holdings.
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| U S Geological Survey |
| 2025 |
The 3D Hydrography Program (3DHP) data is an integrated, National, 3D-enabled hydrologic dataset derived from the USGS 3D Elevation Program (3DEP) data. For areas where Elevation-derived Hydrography (EDH) has not yet been collected, 3DHP data is supplemented by hydrologic vector data from the National Hydrography Dataset (NHD). As further EDH data is collected, it will replace the NHD data in those areas. 3DHP data ingested from EDH sources includes ‘value added’ catchments and flowline network derivative attributes. All the data is open and non-proprietary. However, users should be aware that temporal changes may have occurred since this dataset was collected and that some parts of this data may no longer represent actual surface conditions. Users should not use this data for critical applications without a full awareness of its limitations. This dataset is not intended to be used for site-specific regulatory determinations. 3DHP datasets include a three-dimensional (3D) hydrography network generated from, and integrated with, elevation data from the 3DEP to better represent stream gradients and channel conditions, along with waterbodies, hydrologic units, hydrologically enhanced elevation and other surfaces, and more consistent and accurate attributes. This product is new in federal fiscal year 2025 (FY25), and consists only of vector data in a series of feature classes. The product represents the 3DHP dataset and the schema in which it is contained as of September 30, 2024 Future Annual Staged Product releases will reflect the schema at the time the product is generated and include more EDH-sourced data holdings.
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| U S Geological Survey |
| 2025 |
The 3D Hydrography Program (3DHP) data is an integrated, National, 3D-enabled hydrologic dataset derived from the USGS 3D Elevation Program (3DEP) data. For areas where Elevation-derived Hydrography (EDH) has not yet been collected, 3DHP data is supplemented by hydrologic vector data from the National Hydrography Dataset (NHD). As further EDH data is collected, it will replace the NHD data in those areas. 3DHP data ingested from EDH sources includes ‘value added’ catchments and flowline network derivative attributes. All the data is open and non-proprietary. However, users should be aware that temporal changes may have occurred since this dataset was collected and that some parts of this data may no longer represent actual surface conditions. Users should not use this data for critical applications without a full awareness of its limitations. This dataset is not intended to be used for site-specific regulatory determinations. 3DHP datasets include a three-dimensional (3D) hydrography network generated from, and integrated with, elevation data from the 3DEP to better represent stream gradients and channel conditions, along with waterbodies, hydrologic units, hydrologically enhanced elevation and other surfaces, and more consistent and accurate attributes. This product is new in federal fiscal year 2025 (FY25), and consists only of vector data in a series of feature classes. The product represents the 3DHP dataset and the schema in which it is contained as of September 30, 2024 Future Annual Staged Product releases will reflect the schema at the time the product is generated and include more EDH-sourced data holdings.
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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 |
| 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 |
| 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 |
| 2025 |
Landslides are damaging and deadly, and they occur in every U.S. state. However, our current ability to understand landslide hazards at the national scale is limited, in part because spatial data on landslide occurrence across the U.S. varies greatly in quality, accessibility, and extent. Landslide inventories are typically collected and maintained by different agencies and institutions, usually within specific jurisdictional boundaries, and often with varied objectives and information attributes or even in disparate formats. The purpose of this data release is to provide an openly accessible, centralized map of existing information about landslide occurrence across the entire U.S.
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| U S Geological Survey |
| 2025 |
Landslides are damaging and deadly, and they occur in every U.S. state. However, our current ability to understand landslide hazards at the national scale is limited, in part because spatial data on landslide occurrence across the U.S. varies greatly in quality, accessibility, and extent. Landslide inventories are typically collected and maintained by different agencies and institutions, usually within specific jurisdictional boundaries, and often with varied objectives and information attributes or even in disparate formats. The purpose of this data release is to provide an openly accessible, centralized map of existing information about landslide occurrence across the entire U.S.
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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 |
| 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 |
| 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 |
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 |
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 |
| 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 |
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 |
| 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 |
| 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 |
| 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 |
| 2024 |
This dataset is Elevation-derived hydrography (EDH) for the 140G0223F0100 PA_Northeast_Susquehanna_D23_H project covering HU 02050301. The hydrography layer contains line features representing stream rivers and polygons representing waterbody. The EDH was derived from 1m light detection and ranging (lidar) Digital Elevation Models. 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).
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| U S Geological Survey |
| 2024 |
This dataset is Elevation-derived hydrography (EDH) for the 140G0223F0100 PA_Northeast_Susquehanna_D23_H project covering HU 02050301. The hydrography layer contains line features representing stream rivers and polygons representing waterbody. The EDH was derived from 1m light detection and ranging (lidar) Digital Elevation Models. 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).
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| U S Geological Survey |
| 2024 |
This dataset is Elevation-derived hydrography (EDH) for the 140G0223F0100 PA_Northeast_Susquehanna_D23_H project covering HU 02050301. The hydrography layer contains line features representing stream rivers and polygons representing waterbody. The EDH was derived from 1m light detection and ranging (lidar) Digital Elevation Models. 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).
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| U S Geological Survey |
| 2025 |
This dataset is Elevation-derived hydrography (EDH) for the 300294 PA_LakeErie_B24_H project covering work unit PA_LakeErie_1_B24. The hydrography layer contains line features representing stream rivers and polygons representing waterbodies. The EDH was derived from 1 meter lidar Digital Elevation Models. 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).
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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 |
| 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 |
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 |
| 2025 |
These are Digital Elevation Model (DEM) data for Pennsylvania as part of the required deliverables for the USGS_PA_AllentownOrthoLidar_1_D24 project. Class 2 (ground) LiDAR points in conjunction with the hydro breaklines were used to create a 1 foot hydro-flattened Raster DEM.Geographic Extent: 1 counties in Pennsylvania, covering approximately 28 total square miles.Dataset Description: The USGS_PA_AllentownOrthoLidar_1_D24 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, 2023 Rev. A. 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 18, Foot US. LiDAR data were delivered as processed Classified LAS 1.4 files formatted to 129 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. Continuous breaklines were produced in Esri file geodatabase format.Ground Conditions: LiDAR was collected in fall 2024, 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 utilized a total of 5 ground control points that were used to calibrate the LiDAR to known ground locations established throughout the project area. An additional 65 independent accuracy checkpoints, 33 in Bare Earth and Urban landcovers (33 NVA points), 32 in Tall Weeds categories (32 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 |
Area of Interest: Allegheny River, 15 miles, north of Clarion County, in Forest and Warren counties These files contain rasterized topobathy lidar elevations generated from data collected by the Coastal Zone Mapping and Imaging Lidar (CZMIL) system and topographic lidar elevations generated from data collected using a Teledyne ALTM Galaxy PRIME sensor. CZMIL integrates a lidar sensor with simultaneous topographic and bathymetric capabilities, a digital camera and a hyperspectral imager on a single remote sensing platform for use in coastal mapping and charting activities. Native lidar data is not generally in a format accessible to most Geographic Information Systems (GIS). Specialized in-house and commercial software packages are used to process the native lidar data into 3-dimensional positions that can be imported into GIS software for visualization and further analysis. Horizontal positions, provided in decimal degrees of latitude and longitude, are referenced to the North American Datum of 1983 National Adjustment of 2011 (NAD83 (2011). Vertical positions are referenced to the NAD83 (2011) ellipsoid and provided in meters. The National Geodetic Survey's (NGS) GEOID12B model is used to transform the vertical positions from ellipsoid to orthometric heights referenced to the North American Vertical Datum of 1988 (NAVD88). The 3-D position data are sub-divided into a series of LAS files, which are tiled into 1-km by 1-km boxes defined by the Military Grid Reference System. The LAS file index is provided by the shape files, "MGRS_1km_17T.shp ", and the numbers used to identify files are in the "Box" field of the shape file. The data file naming convention is based on the year, effort, area, "Box" number and data product type. An example file name is "2020_ERDC_PA_17TPF2793_1mGrid.tif", where 2020 is the year of data collection, ERDC is the effort under which data were collected, PA is the area of data collection, 17TPF2793 is the "Box" number and 1mGrid is the data product type
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| United States Army Corps of Engineers USACE |