Detecting spatio-temporal urban surface changes using identified temporary coherent scatterers

作     者：HU Fengming WU Jicang HU Fengming;WU Jicang

作者机构：Key Laboratory for Information Science of Electromagnetic WavesFudan UniversityShanghai 200433China College of Surveying and Geo-InformaticsTongji UniversityShanghai 200092China 

出 版 物：《Journal of Systems Engineering and Electronics》 (系统工程与电子技术（英文版）)

年 卷 期：2021年第32卷第6期

页      面：1304-1317页

核心收录：

学科分类：080904[工学-电磁场与微波技术] 081802[工学-地球探测与信息技术] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 0810[工学-信息与通信工程] 083002[工学-环境工程] 0830[工学-环境科学与工程（可授工学、理学、农学学位）] 0818[工学-地质资源与地质工程] 081105[工学-导航、制导与控制] 081602[工学-摄影测量与遥感] 0816[工学-测绘科学与技术] 0703[理学-化学] 0714[理学-统计学（可授理学、经济学学位）] 081001[工学-通信与信息系统] 081002[工学-信号与信息处理] 0825[工学-航空宇航科学与技术] 0701[理学-数学] 0811[工学-控制科学与工程] 

基　　金：supported by the National Natural Science Foundation of China (42074022) 

主　　题：change detection temporary coherent scatterer multi-temporal interferometric synthetic aperture radar(InSAR) amplitude analysis 

摘      要：Synthetic aperture radar(SAR) is able to detect surface changes in urban areas with a short revisit time, showing its capability in disaster assessment and urbanization *** presented change detection methods are conducted using couples of SAR amplitude images. However, a prior date of surface change is required to select a feasible image pair. We propose an automatic spatio-temporal change detection method by identifying the temporary coherent scatterers. Based on amplitude time series, χ^(2)-test and iterative single pixel change detection are proposed to identify all step-times: the moments of the surface change. Then the parameters, e.g., deformation velocity and relative height, are estimated and corresponding coherent periods are identified by using interferometric phase time series. With identified temporary coherent scatterers, different types of temporal surface changes can be classified using the location of the coherent periods and spatial significant changes are identified combining point density and F values. The main advantage of our method is automatically detecting spatio-temporal surface changes without prior information. Experimental results by the proposed method show that both appearing and disappearing buildings with their step-times are successfully identified and results by ascending and descending SAR images show a good agreement.