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Description: High resolution land cover dataset for [CITY OR COUNTY, STATE]. Seven land cover classes were mapped: (1) tree canopy, (2) grass/shrub, (3) bare earth, (4) water, (5) buildings, (6) roads, and (7) other paved surfaces. The primary sources used to derive this land cover layer were 2014 LiDAR data and 2014 NAIP imagery. Ancillary data sources included GIS data provided by the city of San Diego or created by the UVM Spatial Analysis Laboratory. Object-based image analysis techniques (OBIA) were employed to extract land cover information using the best available remotely sensed and vector GIS datasets. 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. Following the automated OBIA mapping a detailed manual review of the dataset was carried out at a scale of 1:3000 and all observable errors were corrected. It is important to note that this data was mapped to the extent of the 2014 LiDAR dataset recieved from the City of San Diego (generally coastal areas).
Service Item Id: 2c559935559c433198204670460be5db
Copyright Text: University of Vermont Spatial Analysis Laboratory
Spatial Reference:
102646
(2230)
Initial Extent:
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Spatial Reference: 102646
(2230)
Full Extent:
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XMax: 6390000.736606643
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Spatial Reference: 102646
(2230)
Units: esriFeet
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Supports ApplyEdits With Global Ids: true
Supports Dynamic Layers: false
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