Open AccessMapping Burned Areas in a Mediterranean Environment Using Soft Integration of Spectral Indices from High-Resolution Satellite Images
Author(s) -
Mirco Boschetti,
Daniela Stroppiana,
Pietro Alessandro Brivio
Publication year - 2010
Publication title -
earth interactions
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.309
H-Index - 38
ISSN - 1087-3562
DOI - 10.1175/2010ei349.1
Subject(s) - advanced spaceborne thermal emission and reflection radiometer , remote sensing , satellite , pixel , computer science , data set , image resolution , fuzzy logic , environmental science , artificial intelligence , geography , digital elevation model , engineering , aerospace engineering
This article presents a new method for burned area mapping using high-resolution satellite images in the Mediterranean ecosystem. In such a complex environment, high-resolution satellite images represent an appropriate data source for identifying fire-affected areas, and single postfire data are often the only available source of information. The method proposed here integrates several spectral indices into a fuzzy synthetic indicator of likelihood of burn. The indices are interpreted through fuzzy membership functions that have been derived with a partially data-driven approach exploiting training data and expert knowledge. The final map of fire-affected areas is produced by applying a region growing algorithm on the basis of seed pixels selected on a conservative threshold of the synthetic fuzzy score. The algorithm has been developed and tested on a set of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) scenes acquired over Southern Italy. Validation showed that the accuracy of the burned area maps is comparable or even better [overall accuracy (OA) > 90%, K > 0.76] than that obtained with approaches based on single index thresholds adapted to each image. The method described here provides an automatic approach for mapping fire-affected areas with very few false alarms (low commission error), whereas omission errors are mainly related to undetected small burned areas and are located in heterogeneous sparse vegetation cover.