DETECTION OF LAND USE CHANGE IN URBAN AGGLOMERATION USING SENTINEL-1 SAR DATA

Urban agglomeration becomes increasingly important because of the globalization of world economies. Change detection of urban agglomeration based on remote sensing technology is one of the hotspots of research. In this paper, an automatic change detection method using Sentinel-1 SAR data over a large area is proposed. After the image is segmented into several blocks of the same size by using multi-scale chessboard segmentation method, combining bimodal detection method with skewness coefficient, the decision rules are designed to search blocks containing balanced mixture of positive and unchanged region, as well as blocks containing balanced mixture of negative and unchanged region. Taking the urban agglomerations of Suzhou, Wuxi and Changzhou as examples, the change detection research is carried out. The experimental results show that the proposed change detection method can effectively identify new construction land and damage areas, and provide effective basic data support for urban managers.