Comparative Performance Of ALOS PALSAR Polarization Bands And Its Combination With ALOS AVNIR-2 Data For Land Cover Classification

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Date
2012
Authors
Sim, Chong Keat
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Universiti Sains Malaysia
Abstract
Microwave Remote Sensing data have been widely used for land cover classification in our environment. In this study, ALOS PALSAR polarization bands were used to identify land cover features in three study areas in Malaysia. The study area consists of Penang, Perak and Kedah. The aims of this research are to investigate the performance of ALOS PALSAR datasets which are assessed independently and combination of these data with ALOS AVNIR-2 for land cover classification. ASF MapReady program from Alaska satellite Facility Geographical Institute at the University of Alaska Fairbanks was used for the preprocessing of ALOS PALSAR data. In addition, different image processing techniques included Speckle Filtering, Texture measures, and Principal Component Analysis (PCA) were applied to the ALOS PALSAR datasets. Standard supervised classification method Maximum Likelihood Classifier (MLC) was applied to the ALOS PALSAR images for land cover classification analysis. Various land cover classes were identified and assessed using the Transformed Divergence (TD) separability measures. The PALSAR data training areas were chosen based on the information obtained from ALOS AVNIR-2 datasets. The original data gave very poor results in identifying land cover classes due to the presence of immense speckle. Frost Filter significantly improved the classification accuracies but still not adequate for accurate land cover classification.
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Comparative performance of ALOS PALSAR polarization bands , combination with ALOS AVNIR-2 data for land cover classification
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