Multi-attribute vegetation maps of Forest Service lands in California supporting resource management decisions

J. Franklin, C. E. Woodcock, R. Warbington

Research output: Contribution to journalArticle

79 Citations (Scopus)

Abstract

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.

Original languageEnglish (US)
Pages (from-to)1209-1217
Number of pages9
JournalPhotogrammetric Engineering and Remote Sensing
Volume66
Issue number10
StatePublished - 2000
Externally publishedYes

Fingerprint

resource management
digital map
vegetation
vegetation type
Remote sensing
land cover
remote sensing
forest inventory
polygon
Land use
Landsat thematic mapper
Risk assessment
Geographic information systems
digital elevation model
Labels
Conservation
Fires
risk assessment
GIS
canopy

ASJC Scopus subject areas

  • Earth and Planetary Sciences (miscellaneous)
  • Computers in Earth Sciences

Cite this

Multi-attribute vegetation maps of Forest Service lands in California supporting resource management decisions. / Franklin, J.; Woodcock, C. E.; Warbington, R.

In: Photogrammetric Engineering and Remote Sensing, Vol. 66, No. 10, 2000, p. 1209-1217.

Research output: Contribution to journalArticle

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