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

MULTI-CRITERIA FUZZY-BASED APPROACH FOR MAPPING BURNED
AREAS IN SOUTHERN ITALY WITH ASTER IMAGERY
Abstract: Burned area mapping algorithms developed for satellite images
often rely on the use of spectral/vegetation indices for discriminating
between burns and other surfaces. Since the choice of one or more indices
over the others might be subjective, we propose a semi-automated
approach for integrating indices into a synthetic indicator (score) of likelihood
of burn based on fuzzy set theory. The mapping method is based on
a region growing algorithm that uses seed pixels identified by a conservative
threshold on the synthetic score. The algorithm was tested on ASTER
images and validated with an independent data set. Burned area maps for
the Calabria region are presented and discussed.
1 - Introduction
M. Boschetti 1 , D. Stroppiana 1 & P.A. Brivio 1
1 CNR-IREA, Institute for Electromagnetic Sensing of the Environment,
Milan, Italy
boschetti.m@irea.cnr.it; stroppiana.d; brivio.pa
Forest fires in Italy destroy more than 50.000 ha of natural vegetation
every year. In this environment most of the burned surfaces are smaller
than ten hectares limiting the use of widely available moderate resolution
data and well accepted multi-temporal mapping methods. It is therefore
necessary in supporting fire monitoring activity to exploit high/very high
resolution (HR) multispectral data. Spectral Indices (SIs) are often proposed
as a suitable mapping method with single post fire HR data.
However, no agreement exists on the index that performs better than the
others and in which situation as to be preferred (Stroppiana et al., 2009;
Lasaponara et al., 2006). The objective of our research was to evaluate the
performance of some widely used spectral indices in separating burned surfaces
from other targets and to develop a semi-automated algorithm for
mapping fire affected areas based on the integration of different SIs and
on fuzzy set theory.
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