Name: Tree_Canopy_2018_2020_Chg_Py
Display Field: CLASS_NAME
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: This layer is a high-resolution tree canopy change-detection layer for Prince George's County, Maryland. It contains three tree-canopy classes for the period 2018-2020: (1) No Change; (2) Gain; and (3) Loss. It was created by extracting tree canopy from existing high-resolution land-cover maps for 2018 and 2020 and then comparing the mapped trees directly. Tree canopy that existed during both time periods was assigned to the No Change category while trees removed by development, storms, or disease were assigned to the Loss class. Trees planted during the interval were assigned to the Gain category, as were the edges of existing trees that expanded noticeably. Direct comparison was possible because both the 2018 and 2020 maps 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 will be subjected to manual review and correction.
Service Item Id: 1fc5eeeed72f4333b8ad38c90c04ff81
Copyright Text: University of Vermont Spatial Analysis Laboratory and Sanborn Map Company in collaboration with Prince George's Tree Canopy Change Assessment.
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Spatial Reference: 102685
(2248)
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