Linear mixture model classification of burned forests in the Eastern Amazon

Abstract

A methodology is described for detecting and classifying burned forests in Amazonia. Linear mixture models using three image endmembers (vegetation, soil, shade) were used to separate forest from non-forest. Forested areas were unmixed using vegetation, non-photosynthetic vegetation (NPV) and shade endmembers and reclassified as unburned, recently burned and older burned forests. The NPV fraction provided the greatest separability of the forest classes and has potential for subclassification of burned areas into damage classes. For 184 km2 of burned forest, a conservative estimate of 9% (22 metric tons ha-1) of living biomass was lost due to forest fires between 1991-1993.