Tree Canopy Change, 2010-2015 Allegheny County, PA

Tree canopy change in Allegheny County Pennsylvania for the years 2010 to 2015. This tree canopy change data set consists of three classes: no change, gain, and loss. No change polygons are those in which the tree canopy remained the same between the two time periods. Gain polygons are those in which tree canopy increased between the two time periods. Loss polygons are those in which tree canopy decrease between the two time periods. 2010 tree canopy can be calculated by adding the “no change” and loss classes. Tree canopy for 2015 can be calculated by adding the “no change” and “gain” classes.Several data sets were used to map tree canopy change. The starting point was the 2010 high-resolution land cover data set developed for Allegheny County. Change was then mapped using leaf-off lidar data collected in 2006, 4-band leaf-on National Agriculture Imagery Program (NAIP) data collected in 2010, leaf off lidar data collected in 2015, and 4-band leaf-on NAIP data collected in 2015. All four data sets were integratedinto an object-based image analysis system (OBIA), which a rule-based expert system. A combination of segmentation, classification, and morphology algorithms were employed to determine if tree canopy had changed between the two time periods. The data set was then manually edited at a scale of 1:5000. The main factors determining change were a decrease in height, indicating tree removal, as identified by the lidar, and the change in the spectral characteristics, as identified in the aerial imagery. There were spatial misalignment issues between all four of the data sets. As a result, very fine scale changes at the edges of tree canopy could not be determined. The data set can thus be considered to be slightly biased towards tree canopy loss, and fine-scale tree canopy gains could not be determined. Most of the gain identified is not new growth, but rather canopy from trees that were too small to be detected in the original 2010 mapping.The incorporation of newer lidar data enabled a revisit of the original 2010 tree canopy mapping. The 2015 lidar data was substantially higher quality than the 2006 lidar data used for the 2010 high-resolution land cover mapping project. This enabled errors of omission and commission in the original 2010 tree canopy mapping to be corrected. Examples include shrubby areas in 2010 falsely classified as tree canopy and tall trees that were not clearly visible in the data used to map tree canopy in 2010. This data set should be considered to be the most accurate depiction of tree canopy for both the 2010 and 2015 time periods.

Data and Resources

This dataset has no data

Field Value
access_constraints ["Use Constraints: The University of Vermont makes no representations of any kind, including but not limited to the warranties of merchantability or fitness for a particular use, nor are any such warranties to be implied with respect to the data.", "Access Constraints: None"]
bbox-east-long -79.677803
bbox-north-lat 40.682772
bbox-south-lat 40.185665
bbox-west-long -80.368057
contact-email joneildu@uvm.edu
coupled-resource []
dataset-reference-date [{"type": "publication", "value": "2020-01-01"}]
frequency-of-update notPlanned
licence ["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."]
metadata-date 2019-05-09
metadata-language eng; USA
metadata_type geospatial
progress completed
resource-type dataset
responsible-party [{"name": "University of Vermont", "roles": ["pointOfContact"]}]
spatial {"type": "Polygon", "coordinates": [[[-80.368057, 40.185665], [-79.677803, 40.185665], [-79.677803, 40.682772], [-80.368057, 40.682772], [-80.368057, 40.185665]]]}
spatial_harvester true
temporal-extent-begin 2010-08-01
temporal-extent-end 2015-08-01
Groups
  • AmeriGEOSS
  • National Provider
  • North America
Tags
  • amerigeo
  • amerigeoss
  • change-detection
  • ckan
  • geo
  • geoss
  • land-cover
  • national
  • north-america
  • tree-canopy
  • united-states
isopen False
metadata_created 2025-11-21T04:35:41.156027
metadata_modified 2025-11-21T04:35:41.156032
notes Tree canopy change in Allegheny County Pennsylvania for the years 2010 to 2015. This tree canopy change data set consists of three classes: no change, gain, and loss. No change polygons are those in which the tree canopy remained the same between the two time periods. Gain polygons are those in which tree canopy increased between the two time periods. Loss polygons are those in which tree canopy decrease between the two time periods. 2010 tree canopy can be calculated by adding the “no change” and loss classes. Tree canopy for 2015 can be calculated by adding the “no change” and “gain” classes.Several data sets were used to map tree canopy change. The starting point was the 2010 high-resolution land cover data set developed for Allegheny County. Change was then mapped using leaf-off lidar data collected in 2006, 4-band leaf-on National Agriculture Imagery Program (NAIP) data collected in 2010, leaf off lidar data collected in 2015, and 4-band leaf-on NAIP data collected in 2015. All four data sets were integratedinto an object-based image analysis system (OBIA), which a rule-based expert system. A combination of segmentation, classification, and morphology algorithms were employed to determine if tree canopy had changed between the two time periods. The data set was then manually edited at a scale of 1:5000. The main factors determining change were a decrease in height, indicating tree removal, as identified by the lidar, and the change in the spectral characteristics, as identified in the aerial imagery. There were spatial misalignment issues between all four of the data sets. As a result, very fine scale changes at the edges of tree canopy could not be determined. The data set can thus be considered to be slightly biased towards tree canopy loss, and fine-scale tree canopy gains could not be determined. Most of the gain identified is not new growth, but rather canopy from trees that were too small to be detected in the original 2010 mapping.The incorporation of newer lidar data enabled a revisit of the original 2010 tree canopy mapping. The 2015 lidar data was substantially higher quality than the 2006 lidar data used for the 2010 high-resolution land cover mapping project. This enabled errors of omission and commission in the original 2010 tree canopy mapping to be corrected. Examples include shrubby areas in 2010 falsely classified as tree canopy and tall trees that were not clearly visible in the data used to map tree canopy in 2010. This data set should be considered to be the most accurate depiction of tree canopy for both the 2010 and 2015 time periods.
num_resources 0
num_tags 11
title Tree Canopy Change, 2010-2015 Allegheny County, PA