Performance of Wishart Classification Algorithm to Map Mangrove Forest Using Fully Polarimetric Synthetic Aperture Radar at C-, L- and P-bands

Author :
  1. Bambang H. Trisasongko, Department of Soil Science and Land Resources. Bogor Agricultural University
  2. Dyah R. Panuju, Department of Soil Science and Land Resources. Bogor Agricultural University

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Forested landscapes such as mangrove have drawn many attentions due to their importance in carbon stock. Many attempts were conducted to obtain suitable mangrove map using multi-spectral remote sensing imagery. However, atmospheric disturbance including cloud limits multi-spectral sensors. In many cases, observation through Synthetic Aperture Radar (SAR) is then required. In this research, C-, L- and P-band fully polarimetric SAR data were evaluated to provide a mangrove map exploiting Wishart classifier. Results indicated that Ceriops was the only distinguishable species at C-band. Observation using longer wavelengths (L- and P-bands) revealed fairly strong attenuation from soil background. However, overall accuracy suggested that P-band produced lowest classification error, hence it was suitable to produce a highly accurate map.

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Publisher School of Electrical Engineering and Informatics Institut Teknologi Bandung
Index at 29 January 2013 7:00 a.m.
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