Combining ASTER multispectral imagery analysis and support vector machines for rapid and cost-effective post-fire assessment : A case study from the Greek wildland fires of 2007
Remote sensing is increasingly being used as a cost-effective and practical solution for the rapid evaluation of impacts from wildland fires. The present study investigates the use of the support vector machine (SVM) classification method with multispectral data from the Advanced Spectral Emission and Reflection Radiometer (ASTER) for obtaining a rapid and cost effective post-fire assessment in a