Change monitoring of land use based on Sentinel-1A data
Obtaining optical remote sensing data continuously in Guangdong is difficult because of the cloudy and rainy weather,while synthetic aperture radars(SARs)can offer solutions to the problems of delayed updates and blind spots in high-frequency land use monitoring caused by the lack of optical images.Although the public welfare Sentinel-1A satellite data has low cost and is easy to obtain,the accuracy of change monitoring is poor,and practical application is difficult.Therefore,this paper proposed a new building recognition method integrating the intensity and phase information of Sentinel-1A and external elevation information.Firstly,the paper preprocessed the SAR images to obtain backscatter coefficient maps and used the logarithmic ratio method to construct difference maps for multi-temporal images.Then,the paper used the threshold segmentation algorithm to extract the changing regions and calculated the coherence coefficient and slope with complex images and a digital elevation model,so as to eliminate the false-changing polygons with a large slope and high coherence coefficient and obtain the final changing polygon.The experimental result shows that more reliable change monitoring results can be obtained by considering slope and coherence information on the basis of the difference map,with an overall accuracy improvement of about 18%,which is of great significance for the high-frequency land use monitoring by remote sensing in Guangdong.
国家科技期刊平台
NSTL
万方数据
