Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W7, 675-682, 2017
https://doi.org/10.5194/isprs-archives-XLII-2-W7-675-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
 
13 Sep 2017
STUDY ON LAND SUBSIDENCE INCANGZHOU AREA BASEDON SENTINEL-1A/B DATA
H. Zhou1,2, Y. Wang1,2, and S. Yan1,2 1School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China
2National Administration of Surveying, Mapping and Geo-Information (NASG) Key Laboratory of Land Environment and Disaster Monitoring, Xuzhou, China
Keywords: Sentinel-1A/B, Time Series InSAR, Cangzhou area, Land Subsidence Abstract. This paper, obtaining 39scenesof images of the Sentinel-1 A/B, monitored the Cangzhou area subsidence from Mar. 2015 to Dec. 2016 basing on using PS-InSAR technique. The annual average subsidence rate and accumulative subsidence were obtained. The results showed that the ground surface of Xian County,Cang County, Cangzhou urban area had a rebound trend; Qing County, the east of Cang County ,the west of Nanpi County and Dongguang County appeared obvious subsidence, and the accumulated subsidence in Hezhuang village of Dongguang County reached 47 mm. And from that the main reason leading to these obvious subsidence was over-exploitation of ground-water. At last, it analyzed the settlement of the High-Speed Railway (HR) which was north from the Machang town of QingCounty and south to the Lian town of Dongguang County in Cangzhou.The relative deformation of the HR between the two sections which was Lierzhuang village of Cang County and Chenxin village of Nanpi County arrived at 30 mm. Moreover, this paper discussed the application of Sentinel-1 A/B SAR images in monitoring urban land subsidence and the results provided important basic data for the relevant departments.
Conference paper (PDF, 2034 KB)


Citation: Zhou, H., Wang, Y., and Yan, S.: STUDY ON LAND SUBSIDENCE INCANGZHOU AREA BASEDON SENTINEL-1A/B DATA, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W7, 675-682, https://doi.org/10.5194/isprs-archives-XLII-2-W7-675-2017, 2017.

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