Research Papers

Optimal Envisat advanced synthetic aperture radar image parameters for mapping and monitoring Sahelian floodplains

[+] Author Affiliations
Toon Westra, Robert De Wulf, Frieke Van Coillie, Sarah Crabbe

Ghent University, Laboratory of Forest Management and Spatial Information Techniques (FORSIT), Coupre Links 653, Ghent, Eastern Planders 9000 Belgium

J. Appl. Remote Sens. 4(1), 043511 (March 2, 2010). doi:10.1117/1.3368722
History: Received November 5, 2009; Revised February 8, 2010; Accepted February 18, 2010; March 2, 2010; Online March 02, 2010
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Abstract

Floodplains in the Sahel region of Africa are of exceptional socio-economical and ecological importance. Due to their large extent and highly dynamic nature, monitoring these ecosystems can only be performed by means of remote sensing. The capability of the Envisat Advanced Synthetic Aperture Radar (ASAR) sensor to capture radar backscattering at various incident angles and with different polarization combinations, provides opportunities for improved wetland mapping and monitoring. However, little is known of the optimal image parameters, i.e. incident angle, polarization combination, and acquisition time. Backscatter σ° signatures of Land Use and Land Cover (LULC) classes in and around the Waza-Logone floodplain (Cameroon) were analyzed to determine these optimal image parameters. Based on Jeffries-Matusita (JM) distances between all LULC classes it was determined that best separation was obtained with images acquired in the middle of the flooding cycle at a steep incident angle. Furthermore, separability of cross-polarized images was higher than for co-polarized images. The combination of two and three ASAR Alternating Polarization images with highest separability were used as input for a LULC classification. Two methods were evaluated: Pixel-based Maximum Likelihood and object-based Nearest Neighbour (NN) classification. Best results were obtained with the object-based approach.

© 2010 Society of Photo-Optical Instrumentation Engineers

Citation

Toon Westra ; Robert De Wulf ; Frieke Van Coillie and Sarah Crabbe
"Optimal Envisat advanced synthetic aperture radar image parameters for mapping and monitoring Sahelian floodplains", J. Appl. Remote Sens. 4(1), 043511 (March 2, 2010). ; http://dx.doi.org/10.1117/1.3368722


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