SAR-based analysis of urban areas: Joint exploitation of segments and statistical features

The aim of this paper is to analyze a procedure aimed at human settlement extraction from SAR images based on Local Indicators of Spatial Association (LISA) and textural features, followed by a refined classification scheme using the same features to extract more detailed land use classes according to the CORINE nomenclature. A segmentation technique is exploited in order to identify statistically homogeneous regions and eventually a supervised classification of the selected features allows assigning each region to a class. Tests on the areas of Shanghai show potentials for the use of these techniques in urban area monitoring using moderate resolution SAR.