Publication Date:
2008
abstract:
In Italy, a large percentage of the total forested area burned every year is affected by
few fires of large size but, at the same time, a great number of small fires affect areas
of few hectares each. Thus, an accurate operational mapping of fire affected areas by
satellite needs the employement of methods able to recognize the presence of both
the large burnt areas and the small or very small ones. Indeed, up to now very little
attention has been paid to the recognition and analysis, over large territories, of
areas of very few hectares affected by small fires. Nevertheless, the possibility to derive
by satellite data a map of burnt areas at regional or national scale which includes
also small burnt areas is of great importance for the choice of suitable environmental
management policies. When the task of locating burnt areas must be carried out
periodically on large areas of varying characteristics as the Tuscany Region (Italy),
the crucial problem is that of automatically locating the presence of fire scar on the
territory, reducing as much as possible the number of false alarms, that is, of pixels
that are erroneously flagged as burnt area.
In this work, pre- and post-fire Landsat-ETM images have been used to characterize
the ability of some spectral indices used as binary classifiers to detect small fire affected
areas, in particular to discriminate between pixels corresponding to burnt and
non-burnt areas in the Tuscany Region. Their efficiency was evaluated with regard to
commission and omission errors as a function of the threshold value.
Iris type:
04.02 Abstract in Atti di convegno
List of contributors:
Bonora, Laura; Carla', Roberto; Conese, Claudio
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