Paper
23 October 2012 Integration of optical and SAR remotely sensed data for monitoring wildfires in Mediterranean forests
Ramin Azar, Daniela Stroppiana, Mirco Boschetti, Pietro Alessandro Brivio, Antonio Pepe, Luca Paglia, Fabiana Calò, Riccardo Lanari
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Abstract
Large wildfires in forests of southern European countries such as Portugal, Spain, Greece, France and Italy are one key ecological disturbance of the Mediterranean environment. Optical data have been largely used for burned area mapping and literature provides an extensive reference for the typical spectral signal of burns and the methodologies applied to extract burn perimeters. However, optical remote sensing techniques have the major limitation of a reduced frequency of clear images due to cloud cover; moreover, for the specific application of burned area mapping, unburned targets such as shadows, can be spectrally confused and misclassified as burns. For this reason radar images could be integrated as an additional source of information. We developed an approach for mapping burned areas in Mediterranean regions based on Landsat TM/ETM+ data and vegetation indices that provided satisfactory results. However, we are currently working for further improving our approach by exploiting the synergy between optical and radar data. In this paper we present the first results of the analysis of the SAR backscatter over burned areas for future integration into the formal framework previously developed. Although results are preliminary, they encourage us to test the approach over different regions of the Mediterranean environment to evaluate its robustness.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ramin Azar, Daniela Stroppiana, Mirco Boschetti, Pietro Alessandro Brivio, Antonio Pepe, Luca Paglia, Fabiana Calò, and Riccardo Lanari "Integration of optical and SAR remotely sensed data for monitoring wildfires in Mediterranean forests", Proc. SPIE 8531, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIV, 85312D (23 October 2012); https://doi.org/10.1117/12.974725
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Cited by 2 scholarly publications.
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KEYWORDS
Backscatter

Vegetation

Synthetic aperture radar

Earth observing sensors

Landsat

Agriculture

Statistical analysis

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