7th Workshop on Forest Fire Management - EARSeL, European ...

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IV - BURNED LAND MAPPING, FIRE SEVERITY DETERMINATION, AND VEGETATION RECOVERY ASSESSMENT
to derive BAIM and NBR indexes.
The Simple Vegetation Index (SVI), the Normalized Difference Vegetation
Index (NDVI), the Transformed Vegetation Index (TVI) and the Soil Adjusted
Vegetation Index (SAVI) have been widely used for fire studies
(Nikolakopoulus, 2003) and have been selected in this case for ASTER burnt
pixels discrimination.
On the other hand, the Burnt Area Index for MODIS (BAIM) is an adaptation
of the BAI (Burnt Area Index) originally developed to be used with
NOAA-AVHRR, data as described in Martín et al. (2005). As convergence
values the percentiles 5 and 95 from reflectance values on NIR and SWIR
bands have been respectively used (González-Alonso et al., 2007), being
ρc IRC = 0,032 y ρc SWIR = 0,215. The Normalized Burnt Ratio (NBR) is a similar
ratio to the one described in the NDVI formulation, but using NIR and
SWIR bands (Key and Benson, 1999).
1.1 - Classification method
The algorithm Support Vector Machines (SVM) falls within the supervised
classification (Vapmik, 1995). After analyzing all kernels, the Radial Basis
Function (RBF) equation has been selected. We have come to this conclusion
after studying the Kappa ratios and percentages of success achieved
with each kernel, noting that the group of locals achieved values higher
than 91% with the sigmoid and RBF equations, while the results were
somewhat worst with global kernels, in which distant points have great
influence and the studied area presents a very diffuse boundary between
burned and unburned soil.
Using SVM algorithm we have analyzed the suitability of each ASTER index
to distinguish the burned area from the rest of the unburned island (Figure
1).