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Proceedings Paper

Accuracy of fuzzy burned area mapping as a function of the aerosol parameterization of atmospheric correction
Author(s): Ramin Azar; Daniela Stroppiana; Mariano Bresciani; Claudia Giardino; Mirco Boschetti; Pietro A. Brivio
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Paper Abstract

Mediterranean forests are every year affected by wildfires which have a significant effect on the ecosystem. Mapping burned areas is an important field of application for optical remote sensing techniques and several methodologies have been developed in order to improve mapping accuracy. We developed an automated procedure based on spectral indices and fuzzy theory for mapping burned areas from atmospherically corrected Landsat TM images. The algorithm proved to provide consistent accuracy over Mediterranean areas. We further tested algorithm’s performance to assess the influence of the atmospheric correction on the accuracy of burned areas. In particular, we ran the Second Simulation of a Satellite Signal in the Solar Spectrum (6S) code with different Atmospheric Optical Thickness (AOT) levels and two aerosol models (continental and maritime) on one TM image acquired over Portugal (12/08/2003). Burned area maps derived from atmospherically corrected images and from the non corrected image (Top Of Atmosphere, TOA) have been analyzed. In the output burned areas maps the omission error varies in the range 4.6-6.5% and the commission error fluctuates between 11.9 and 22.2%; the highest omission (commission) errors occur with the continental (maritime) model. The accuracy of burned area maps derived from non corrected image is very low, with omission error greater than 90%. These results show that, although atmospheric correction is needed for the application of the algorithm, the AOT value does not significantly affect the performance.

Paper Details

Date Published: 16 October 2013
PDF: 8 pages
Proc. SPIE 8887, Remote Sensing for Agriculture, Ecosystems, and Hydrology XV, 88870M (16 October 2013); doi: 10.1117/12.2029011
Show Author Affiliations
Ramin Azar, CNR-Istituto per il Rilevamento Elettromagnetico dell'Ambiente (Italy)
Politecnico di Milano (Italy)
Daniela Stroppiana, CNR-Istituto per il Rilevamento Elettromagnetico dell'Ambiente (Italy)
Mariano Bresciani, CNR-Istituto per il Rilevamento Elettromagnetico dell'Ambiente (Italy)
Claudia Giardino, CNR-Istituto per il Rilevamento Elettromagnetico dell'Ambiente (Italy)
Mirco Boschetti, CNR-Istituto per il Rilevamento Elettromagnetico dell'Ambiente (Italy)
Pietro A. Brivio, CNR-Istituto per il Rilevamento Elettromagnetico dell'Ambiente (Italy)


Published in SPIE Proceedings Vol. 8887:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XV
Christopher M. U. Neale; Antonino Maltese, Editor(s)

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