Description

The first of two objectives for the study was to develop and test efficient and effective methods for semi-automated vegetation mapping of the recovering plant communities on SCI, specifically using hierarchical object-based classification with a rule-based expert system, ultra-high spatial resolution (UHSR) multispectral imagery, and lidar-derived digital canopy height data.A secondobjective was to map the distribution and quantify the cover of vegetation alliances over the entirety of SCI.The final vegetation map portrays the distribution of 19 vegetation communities across SCI, with the largest areas comprised of California Annual and Perennial Grassland (35 percent) and three types of coastal sage scrub and maritime succulent scrub, comprising a combined 53 percent of the area. Map accuracy was assessed to be 79 percent based on fuzzy methods and 61 percent with a traditional accuracy assessment. The accuracy of tree identification was assessed to be 81 percent, but species-level tree accuracy was 45 percent.

Resources

Name	Format	Description	Link
	3		https://services2.arcgis.com/Uq9r85Potqm3MfRV/arcgis/rest/services/biosds2962_fpu/FeatureServer/0
	8		https://data-cdfw.opendata.arcgis.com/api/download/v1/items/929994537763435d9364342e655a5d9b/csv?layers=0
	21		https://data-cdfw.opendata.arcgis.com/maps/CDFW::vegetation-san-clemente-island-ds2962
	15		https://data-cdfw.opendata.arcgis.com/api/download/v1/items/929994537763435d9364342e655a5d9b/geojson?layers=0
	57		https://data-cdfw.opendata.arcgis.com/api/download/v1/items/929994537763435d9364342e655a5d9b/shapefile?layers=0
	25		https://data-cdfw.opendata.arcgis.com/api/download/v1/items/929994537763435d9364342e655a5d9b/kml?layers=0

Vegetation - San Clemente Island [ds2962]

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