TY - JOUR
T1 - Multi-attribute vegetation maps of Forest Service lands in California supporting resource management decisions
AU - Franklin, J.
AU - Woodcock, C. E.
AU - Warbington, R.
PY - 2000/1/1
Y1 - 2000/1/1
N2 - Vegetation databases (digital maps) for USDA Forest Service lands in California (approximately 10 million ha) have been developed over the last decade using remote sensing and GIS methods. The databases are intended to support national and regional land-cover inventory and monitoring, interagency conservation and fire risk assessment, and wildlife habitat evaluation, as well as more traditional uses including land management planning and forest inventory within each National Forest. The digital maps are fine-scale relative to their extent, being derived from 30-m-resolution Landsat Thematic Mapper (TM) data and digital elevation models (DEMs). Map attributes included a vegetation life form class, a vegetation type, and canopy cover and size class estimates for forested polygons. Land-cover and vegetation type labels were more accurate than forest structure estimates. However, the mapping methodology is not static. New remote sensing data and analysis methods offer some promise to improve map attribute estimation. The database is being provided by the Forest Service to agency personnel, cooperators, and the public.
AB - Vegetation databases (digital maps) for USDA Forest Service lands in California (approximately 10 million ha) have been developed over the last decade using remote sensing and GIS methods. The databases are intended to support national and regional land-cover inventory and monitoring, interagency conservation and fire risk assessment, and wildlife habitat evaluation, as well as more traditional uses including land management planning and forest inventory within each National Forest. The digital maps are fine-scale relative to their extent, being derived from 30-m-resolution Landsat Thematic Mapper (TM) data and digital elevation models (DEMs). Map attributes included a vegetation life form class, a vegetation type, and canopy cover and size class estimates for forested polygons. Land-cover and vegetation type labels were more accurate than forest structure estimates. However, the mapping methodology is not static. New remote sensing data and analysis methods offer some promise to improve map attribute estimation. The database is being provided by the Forest Service to agency personnel, cooperators, and the public.
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M3 - Review article
AN - SCOPUS:0033816239
SN - 0099-1112
VL - 66
SP - 1209
EP - 1217
JO - Photogrammetric Engineering and Remote Sensing
JF - Photogrammetric Engineering and Remote Sensing
IS - 10
ER -