Author(s):
Pereira, José 
; Sousa, Adélia ; Sá, Ana
Date: 1999
Persistent ID: http://hdl.handle.net/10174/3655
Origin: Repositório Científico da Universidade de Évora
Subject(s): NOAA-AVHRR; Burnt area; NDVI; CART
Document details
Regional-scale burnt area mapping in Southern Europe using NOAA-AVHRR 1 km data
Description
A brief review of studies dealing with burnt area mapping using coarse spatial resolution satellite imagery is presented, followed by an ana lysis of areas burnt in Iberia during the 1991 and 1994 fire seasons, two of the worst on record in Portugal an Spain, respectively. In order to detect and map burnt areas, new multitemporal image compositing algorithms were developed. Burnt area mapping for the 1991 fire season relied on the Global Environment Monitoring Index (GEMI), albedo, and surface temperature. A rule-based classifier was induced from training data, using the classification and regression trees (CART) algorithm. Firesize estimates compared well to those derived with Landsat TM imagery, but appear unreliable for burns smaller than about 2000ha.The 1994 fire season data were analysed with a two-phase procedure. First, a new spectral index was specifically designed for burnt area detection. Images of this index were thresholded to detect clearly burnt pixelsand to avoid commission errors. Secondly, a distance-based multicriteria analysis technique was applied, combining spectral similarity and spatial contiguity criteria, to map the burns. The method detected over 80% of all large fires, and proved especially effective at mapping burns larger than 1000 ha.
A brief review of studies dealing with burnt area mapping using coarse spatial resolution satellite imagery is presented, followed by an ana lysis of areas burnt in Iberia during the 1991 and 1994 fire seasons, two of the worst on record in Portugal an Spain, respectively. In order to detect and map burnt areas, new multitemporal image compositing algorithms were developed. Burnt area mapping for the 1991 fire season relied on the Global Environment Monitoring Index (GEMI), albedo, and surface temperature. A rule-based classifier was induced from training data, using the classification and regression trees (CART) algorithm. Firesize estimates compared well to those derived with Landsat TM imagery, but appear unreliable for burns smaller than about 2000ha.The 1994 fire season data were analysed with a two-phase procedure. First, a new spectral index was specifically designed for burnt area detection. Images of this index were thresholded to detect clearly burnt pixelsand to avoid commission errors. Secondly, a distance-based multicriteria analysis technique was applied, combining spectral similarity and spatial contiguity criteria, to map the burns. The method detected over 80% of all large fires, and proved especially effective at mapping burns larger than 1000 ha.
Document Type
Part of book or chapter of book
Language English
Editor(s) Chuvieco, Emilio
Language English
Editor(s) Chuvieco, Emilio
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