Fuzzy logic merger of spectral and ecological information for improved montane forest mapping.

Geocarto International
By: , and 



Environmental data are often utilized to guide interpretation of spectral information based on context, however, these are also important in deriving vegetation maps themselves, especially where ecological information can be mapped spatially. A vegetation classification procedure is presented which combines a classification of spectral data from Landsat‐5 Thematic Mapper (TM) and environmental data based on topography and fire history. These data were combined utilizing fuzzy logic where assignment of each pixel to a single vegetation category was derived comparing the partial membership of each vegetation category within spectral and environmental classes. Partial membership was assigned from canopy cover for forest types measured from field sampling. Initial classification of spectral and ecological data produced map accuracies of less than 50% due to overlap between spectrally similar vegetation and limited spatial precision for predicting local vegetation types solely from the ecological information. Combination of environmental data through fuzzy logic increased overall mapping accuracy (70%) in coniferous forest communities of northwestern Montana, USA.

Study Area

Publication type Article
Publication Subtype Journal Article
Title Fuzzy logic merger of spectral and ecological information for improved montane forest mapping.
Series title Geocarto International
DOI 10.1080/10106040208542226
Volume 17
Issue 1
Year Published 2002
Language English
Publisher Taylor and Francis
Publisher location Hong Kong
Contributing office(s) Northern Rocky Mountain Science Center
Description 8 p.
First page 61
Last page 68
Country United States
State Montana
Other Geospatial North fork of the Flathead River
Online Only (Y/N) N
Additional Online Files (Y/N) N
Google Analytic Metrics Metrics page
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