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Processing Multitemporal TM Imagery to Extract Forest Cover Change Features in Cleveland National Forest, Southern California
Project Start Date
01/01/2000
Project End Date
01/01/2003
Project Call Name
Regional_Initiative_Name
Solicitation
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Team Members:

Person Name Person role on project Affiliation
Janet Franklin Principal Investigator Arizona State University, San Diego, United States
Abstract

Multitemporal Spectral Mixture Analysis • Highly accurate in depicting changes in forest cover: Soil, NPV and GV are sensitive to inter-date change in ‘natural’ cover • Decision Tree Classifier outperformed a Conventional Maximum Likelihood Classifier by 10% overall and by an average of 9% for each cover change class • Inclusion of ancillary data sets to reduce spectral confusion and texture images to enhance accuracy