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Remote Sens. 2013, 5(11), 5680-5701; doi:10.3390/rs5115680

Evaluation of ALOS PALSAR Imagery for Burned Area Mapping in Greece Using Object-Based Classification

Laboratory of Forest Management and Remote Sensing, Aristotle University of Thessaloniki, P.O. Box 248, GR-54124 Thessaloniki, Greece
Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91109, USA
KSAT, Prestvannvegen 38, N-9291 Tromsø, Norway
Author to whom correspondence should be addressed.
Received: 30 September 2013 / Revised: 24 October 2013 / Accepted: 24 October 2013 / Published: 4 November 2013
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In this work, the potential of Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) imagery to map burned areas was evaluated in two study areas in Greece. For this purpose, we developed an object-based classification scheme to map the fire-disturbed areas using the PALSAR imagery acquired before and shortly after fire events. The advantage of employing an object-based approach was not only the use of the temporal variation of the backscatter coefficient, but also the incorporation in the classification of topological features, such as neighbor objects, and class related features, such as objects classified as burned. The classification scheme resulted in mapping the burned areas with satisfactory results: 0.71 and 0.82 probabilities of detection for the two study areas. Our investigation revealed that the pre-fire vegetation conditions and fire severity should be taken in consideration when mapping burned areas using PALSAR in Mediterranean regions. Overall, findings suggest that the developed scheme could be applied for rapid burned area assessment, especially to areas where cloud cover and fire smoke inhibit accurate mapping of burned areas when optical data are used.
Keywords: fire severity; Mediterranean landscape; multi-temporal SAR fire severity; Mediterranean landscape; multi-temporal SAR
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Polychronaki, A.; Gitas, I.Z.; Veraverbeke, S.; Debien, A. Evaluation of ALOS PALSAR Imagery for Burned Area Mapping in Greece Using Object-Based Classification. Remote Sens. 2013, 5, 5680-5701.

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