20260323 14155000 1.0 FALSE TreeCanopyChange_2010_2022_DelawareCountyPA_revised.tif 002 2570000.000000 2682000.000000 178146.011000 277201.011000 1 Projected GCS_North_American_1983 Linear Unit: Foot_US (0.304801) NAD_1983_StatePlane_Pennsylvania_South_FIPS_3702_Feet <ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.0.0'><WKT>PROJCS["NAD_1983_StatePlane_Pennsylvania_South_FIPS_3702_Feet",GEOGCS["GCS_North_American_1983",DATUM["D_North_American_1983",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic"],PARAMETER["False_Easting",1968500.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-77.75],PARAMETER["Standard_Parallel_1",39.93333333333333],PARAMETER["Standard_Parallel_2",40.96666666666667],PARAMETER["Latitude_Of_Origin",39.33333333333334],UNIT["Foot_US",0.3048006096012192],AUTHORITY["EPSG",2272]]</WKT><XOrigin>-119214200</XOrigin><YOrigin>-96198500</YOrigin><XYScale>37163717.489134133</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.0032808333333333331</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>102729</WKID><LatestWKID>2272</LatestWKID></ProjectedCoordinateSystem> 8 FALSE LZW 1 TIFF TRUE continuous unsigned integer 0 20250530 10580100 20250530 10580100 Paige Brochu University of Vermont Spatial Analysis Laboratory Director 802-656-3324 802-656-8683 Aiken Room 205 81 Carrigan Drive Burlington VT 05405 US Paige.Brochu@uvm.edu 20250513 ArcGIS Metadata 1.0 Tree Canopy Change for Delaware County, Pennsylvania, 2010-2022 2025-05-15 University of Vermont Spatial Analysis Laboratory remote-sensing image This layer is a high-resolution tree canopy change-detection layer for Delaware County, Pennsylvania. Tree canopy change was mapped by using remotely sensed data from two time periods (2010 and 2022). Tree canopy was assigned to three classes: 1) no change, 2) gain, and 3) loss. No change represents tree canopy that remained the same from one time period to the next. Gain represents tree canopy that increased or was newly added, from one time period to the next. Loss represents the tree canopy that was removed from one time period to the next. Mapping was carried out using an approach that integrated automated feature extraction with manual edits. Care was taken to ensure that changes to the tree canopy were due to actual change in the land cover as opposed to differences in the remotely sensed data stemming from lighting conditions or image parallax. Direct comparison was possible because land-cover maps from both time periods were created using object-based image analysis (OBIA) and included similar source datasets (LiDAR-derived surface models, multispectral imagery, and thematic GIS inputs). OBIA systems work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to insure that the end product is both accurate and cartographically pleasing. No accuracy assessment was conducted, but the dataset was subjected to manual review and correction. This dataset was developed as part of an Urban Tree Canopy (UTC) assessment for Delaware County, Pennsylvania. It shows how tree canopy changed during the period 2010-2022, highlighting trees that were gained or lost during the 5-year period. It is intended for use in monitoring patterns of change in Delaware County, Pennsylvania tree canopy. University of Vermont Spatial Analysis Laboratory in collaboration with Delaware County PA, SavATree. imageryBaseMapsEarthCover tree canopy change detection urban imageryBaseMapsEarthCover tree canopy change detection urban Dataset represents the change in tree canopy within the boundary of Delaware County, Pennsylvania from 2010 to 2022. 0702 2022-05-17 This assessment was completed by the University of Vermont's Spatial Analysis Laboratory with funding from the Delaware County, PA. The methods used were developed by the University of Vermont Spatial Analysis Laboratory in partnership with the USDA Forest Service. Tree canopy assessments have been conducted for numerous communities throughout the U.S. where the results have been instrumental in helping to establishing tree canopy goals. Esri ArcGIS 13.0.3.36057 1 -75.609035 -75.200412 40.074181 39.794196 No accuracy assessment was conducted, but the dataset was subject to a thorough manual quality control (QC). Accuracy assessments from previous UTC land cover datasets indicate that the use OBIA techniques in combination with a detailed QC yield an overall accuracy of 95% or better. Valid raster dataset. Complete coverage for the study area using the most recent boundary data. Automated feature extraction using eCognition. 2022 tree-canopy was derived from the land cover dataset and compared directly to the equivalent map for 2010, identifying tree canopy that did not change during the period, new trees that were gained through planting or existing trees that exhibited noticeable growth, and trees that were lost to natural and anthropogenic forces. 2025-01-31 Manual corrections made using photo interpretation between 2010 and 2022 imagery and data to detect tree canopy change or no change. 2025-05-05 2022 Land Cover raster developed as part of the same project for which the current Tree Canopy Change dataset was created. 2022 Land Cover for Delaware County, Pennsylvania LandCover_2022_DelawareCountyPA.tif TreeCanopyChange_2010_2022_DelawareCountyPA.tif Table 3 OID OID OID 4 0 0 Internal feature number. Esri Sequential unique whole numbers that are automatically generated. Value Tree-canopy change classes University of Vermont Spatial Analysis Laboratory 1 No Change University of Vermont Spatial Analysis Laboratory 2 Gain University of Vermont Spatial Analysis Laboratory 3 Loss University of Vermont Spatial Analysis Laboratory Count # pixels per tree canopy change class Internal Number of pixels per tree canopy change class Class Class String 254 0 0 Raster Dataset dataset EPSG 6.12(9.0.0) 2 1 0 2570000.000000 178146.011000 2570000.000000 277201.011000 2682000.000000 277201.011000 2682000.000000 178146.011000 2626000.000000 227673.511000 112000 1.000000 99055 1.000000 Band_1 3.000000 1.000000 8