Monitoring of recent ground surface subsidence in the Cangzhou region by the use of the InSAR time-series technique with multi-orbit Sentinel-1 TOPS imagery. Issue 22 (17th November 2018)

• Record Type: Journal Article
• Authors: Zhou, Hongyue; Wang, Yunjia; Yan, Shiyong; Li, Yi; Liu, Xixi; Zhang, Feiyue
• Is Part Of: International journal of remote sensing. Volume 39:Issue 22(2018)
• Page Start: 8113
• Page End: 8128
• Publication Date: 2018-11-17
• Subjects: Remote sensing -- Periodicals; Télédétection -- Périodiques; 621.3678
• DOI: 10.1080/01431161.2018.1482020
• Languages: English
• ISSNs: 0143-1161

Abstract

ABSTRACT: By collecting 39 scenes of descending images and 26 scenes of ascending images of Sentinel-1 synthetic aperture radar (SAR), we monitored the ground subsidence situation of Cangzhou in China during the period from March 2015 to February 2017 with the advanced synthetic aperture radar interferometry (InSAR) time-series technique and obtained the time-series subsidence rates of Cangzhou. We then selected the two sets of results of the monitoring obtained during the same period (from July 2015 to December 2016) to verify the results' accuracy, considering three overlapping areas (Xinhua District, Botou County, and Dongguang County). This analysis clearly indicated that both types of results have good consistency, and the maximum subsidence occurred in Dongguang County. By further study of the central area of Dongguang and the related urban development, we found that the subsidence reached about 80.0 mm over the study period and there was a close relationship between the subsidence trend and the main direction of the city development. Moreover, by combining the two sets of results, we confirmed that there has been subsidence of the high-speed railway line in the whole of the Cangzhou area, among which the most obvious subsidence has occurred in Dongguang and Qing Counties. Finally, it was proved that the Sentinel-1 data can be used to monitor ground surface subsidence, and the data are especially effective in identifying persistent scatterer points along a linear feature. Therefore, this article could provide reliable data to assist with important decisions about urban development projects in the Cangzhou area in the next few years.