Combining SAR and optical features in a SVM classifier for man-made structures detection

The increasing quality of satellite images has generated interests in extracting man-made structures in urban areas, such as buildings and roads. A classification adapted to urban areas can help to identify these structures. In this paper, SAR information are used to improve land-cover classification. We proposed a classification process using both radar and optical data, a segmentation and a classification with Support Vector Machines (SVM).