Pennsylvania Spatial Data Access

Abstract:

This dataset is a representation of forest patches derived from the tree canopy class in the 2010-2011 high-resolution land cover dataset for the northern section of the Delaware River Basin. Three classes of forest patches were derived: 1) small, 2) medium, and 3) large. A customized algorithm using object-based image analysis techniques within the eCognition software package was to divide the tree canopy into the forest patch classes based on a combination of a combination of size, edge to perimeter ratio, length, and width. In general, small patches represent individual trees or small rows of trees. Medium patches represent clumps of trees, often in suburban or agricultural settings, that are fragmented and may or may not have a duff layer. Large forest patches consist of forested stands that in most cases will have a duff layer.End users of this layer should note that this forest patch classification is one approach and the dataset should be evaluated so as to understand its capabilities and limitations before using for decision making purposes.

Purpose:

This dataset is a representation of forest patches based on 2010-2011 high-resolution land cover for the northern section of the Delaware River Basin.

Supplemental_Information:

This data set was developed for the Delaware River Basin Commission with a grant from the William Penn Foundation. The methods used were developed by the University of Vermont Spatial Analysis Laboratory with funding from the USDA Forest Service..

Currentness_Reference:

ground condition

Use_Constraints:

None

Address:

Aiken Room 205

Address:

81 Carrigan Drive

Address:

81 Carrigan Drive

Address:

Aiken Center Room 205

Data_Set_Credit:

University of Vermont Spatial Analysis Laboratory

Logical_Consistency_Report:

Topology check for overlaps and gaps.

Completeness_Report:

Complete for the study area.

Source_Contribution:

National Agricultural Imagery Program 4-band data, Broome County, NY.

Source_Contribution:

National Agricultural Imagery Program 4-band data, Chenango, NY

Source_Contribution:

National Agricultural Imagery Program 4-band data, Delaware County, NY.

Source_Contribution:

National Agricultural Imagery Program 4-band data, Orange County, NY

Source_Contribution:

National Agricultural Imagery Program 4-band data, Sullivan County, NY.

Source_Contribution:

Normalized Digital Surface Model, Broome County, NY

Source_Contribution:

Normalized Digital Surface Model, Chenango County, NY

Source_Contribution:

Normalized Digital Surface Model, Delaware County, NY.

Source_Contribution:

Normalized Digital Surface Model, Orange County, NY

Source_Contribution:

Normalized Digital Surface Model, Sullivan County, NY

Source_Contribution:

Normalized Digital Surface Model, Ulster County, NY

Source_Contribution:

National Agricultural Imagery Program 4-band data, Ulster County, NY

Source_Contribution:

National Agricultural Imagery Program 4-band data, Ulster County, NY.

Source_Contribution:

National Agricultural Imagery Program 4-band data, Lackawanna County, PA

Source_Contribution:

National Agricultural Imagery Program 4-band data, Monroe County, PA.

Source_Contribution:

National Agricultural Imagery Program 4-band data, Pike County, PA.

Source_Contribution:

National Agricultural Imagery Program 4-band data, Wayne County, PA.

Source_Contribution:

Normalized Digital Surface Model, Lackawanna County, PA.

Source_Contribution:

Normalized Digital Surface Model, Monroe County, PA.

Source_Contribution:

Normalized Digital Surface Model, Pike County, PA.

Source_Contribution:

Normalized Digital Surface Model, Wayne County, PA

Source_Contribution:

Vector GIS Data

Process_Description:

Object based image analysis (OBIA) using a rule-based expert system

Process_Description:

Manual corrections to land cover classification

Attribute_Definition:

Internal feature number.

Attribute_Definition_Source:

Esri

Attribute_Definition:

Feature geometry.

Attribute_Definition_Source:

Esri

Attribute_Definition:

Three classes of forest patches were derived: 1) small, 2) medium, and 3) large.  A customized algorithm using object-based image analysis techniques within the eCognition software package was to divide the tree canopy into the forest patch classes based on a combination of a combination of size, edge to perimeter ratio, length, and width.  In general, small patches represent individual trees or small rows of trees.  Medium patches represent clumps of trees, often in suburban or agricultural settings, that are fragmented and may or may not have a duff layer.  Large forest patches consist of forested stands that in most cases will have a duff layer.

Attribute_Definition_Source:

Project

Address:

115 Land and Water Building

Distribution_Liability:

The USER shall indemnify, save harmless, and, if requested, defend those parties involved with the development and distribution of this data, their officers, agents, and employees from and against any suits, claims, or actions for injury, death, or property damage arising out of the use of or any defect in the FILES or any accompanying documentation. Those parties involved with the development and distribution excluded any and all implied warranties, including warranties or merchantability and fitness for a particular purpose and makes no warranty or representation, either express or implied, with respect to the FILES or accompanying documentation, including its quality, performance, merchantability, or fitness for a particular purpose. The FILES and documentation are provided "as is" and the USER assumes the entire risk as to its quality and performance. Those parties involved with the development and distribution of this data will not be liable for any direct, indirect, special, incidental, or consequential damages arising out of the use or inability to use the FILES or any accompanying documentation.

Address:

81 Carrigan Drive

Address:

Aiken Center Room 205

Forest Patch Classification, Delaware River Basin, Northern Section, 2010-2011