EVALUATION OF SPECTRAL INDICES FOR DETECTION OF BURNED AREAS IN AN ENVIRONMENTAL PROTECTION AREA USING SPOT-5 IMAGES

Abstract

The Cerrado biome has great importance in ecological biodiversity, but deforestation has accelerated in recent decades. The Rio Preto-BA Environmental Preservation Area, known for the high agricultural activity of grains, continually suffers from forest fires and loss of native vegetation. Satellite remote sensing is proposed as an alternative to accurately locate and quantify fire-affected surfaces and their impacts on the landscape. With the recent free availability of SPOT-5 images, it has made it possible to detect burned areas with considerable spatial and spectral resolution. The objective of the present study was to determine the ideal spectral index for detection of the burned area inserted in the APA Rio Preto through two SPOT-5 scenes and the application of the Support Vector Machines (SVM) model. The burned areas detected were submitted to the calculation of five spectral indices, BAI, BAIM, NBR, NDVI and EVI2. The ability of each index to discriminate burned areas was estimated by comparing them with each other using a statistical separability index, SVM regression and accuracy analysis. BAIM was identified as the index with the greatest potential for discriminating burnt areas with maximum separability and classification accuracy above 90%, while the NDVI and EVI2 indices had low performance. It is hoped that these results can be used to evaluate and prioritize monitoring areas, contribute to the implementation of a fire management plan in the APA and to support subsequent studies on fire dynamics in forest systems integrated with advanced computational technologies.