4.7 Article Proceedings Paper

Evaluation of RADARSAT-1 data for identification of burnt areas in Southern Europe

Journal

REMOTE SENSING OF ENVIRONMENT
Volume 92, Issue 3, Pages 370-375

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.rse.2004.03.018

Keywords

SAR image interpretation; RADARSAT-1; geometric and radiometric correction; incidence angle normalization; forest fires; burnt area mapping; neural network

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This study presents the combined analysis of RADARSAT products of different spatial resolutions acquired under different incidence angles for mapping burnt scars on forested areas of Central Portugal. Prior to the SAR data analysis, a number of pre-processing procedures were carried out. Noise was eliminated by adaptive texture preserving filtering. A specific algorithm for the geocoding of SAR images, based on a range-Doppler approach, enabled precise geocoding of the SAR data by means of a single very accurate ground control point. A novel incidence-angle-normalization for SAR imagery was applied to analyze the backscatter coefficient to a given incidence angles. Further, a backscatter coefficient analysis was performed according to the slope on forested areas and fire disturbed areas. A qualitative and quantitative investigation of the backscattering as related to the slope angle and time changes was performed. As a result of this analysis, the scenes that allowed maximizing the discrimination of burnt areas were selected as the input for the neural network classification. The investigation on the effect of the SAR incidence angle in burnt area discrimination determined that low incidence angles are required for discriminating burnt areas in hilly regions. It was also demonstrated that topography influences the level of discrimination of burnt areas since areas affected by forest fires on face-slopes presents higher backscatter coefficient than those back-slopes. Therefore, SAR data can play a significant role for burnt area mapping in Europe in those areas where optical data cannot be used due to persistent cloud cover. (C) 2004 Elsevier Inc. All rights reserved.

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