EVALUATION OF DECISION TREE CLASSIFICATION ACCURACY TO MAP LAND COVER IN CAPIXABA, ACRE
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Abstract
This study evaluated the accuracy of mapping land cover in Capixaba, state of Acre, Brazil, using decision trees. Eleven attributes were used to build the decision trees: TM Landsat datafrom bands 1, 2, 3, 4, 5, and 7; fraction images derived from linear spectral unmixing; and the normalized difference vegetation index (NDVI). The Kappa values were greater than 0,83, producing excellent classification results and demonstrating that the technique is promising for mapping land cover in the study area.
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