Abstract: Advanced techniques of multi-temporal InSAR (MT-InSAR) represent a valuable tool in ground subsidence studies allowing remote investigation of the behavior of mass movements in long time intervals by using large datasets of SAR images covering the same area and acquired at different epochs. Beijing is susceptible to subsidence, producing undesirable environmental impacts and affecting dense population. Excessive groundwater withdrawal is thought to be the primary cause of land subsidence, and rapid urbanization and economic development, mass construction of skyscrapers, highways and underground engineering facilities (e.g., subway) are also contributing factors. In this paper, a spatial–temporal analysis of the land subsidence in Beijing was performed using one of the MT-InSAR techniques, referred to as Small Baseline Subset (SBAS). This technique allows monitoring the temporal evolution of a deformation phenomenon, via the generation of mean deformation velocity maps and displacement time series from a data set of acquired SAR images. 52 C-band ENVISAT ASAR images acquired from June 2003 to August 2010 were used to produce a linear deformation rate map and to derive time series of ground deformation. The results show that there are three large subsidence funnels within this study area, which separately located in Balizhuang-Dajiaoting in Chaoyang district, Wangjing-Laiguangying Chaoyang district, Gaoliying Shunyi district. The maximum settlement center is Wangsiying-Tongzhou along the Beijing express; the subsidence velocity exceeds 110 mm/y in the LOS direction. In particular, we compared the achieved results with leveling measurements that are assumed as reference. The estimated long-term subsidence results obtained by SBAS approach agree well with the development of the over-exploitation of ground water, indicating that SBAS techniques is adequate for the retrieval of land subsidence in Beijing from multi-temporal SAR data.
Keywords: small baseline subset (SBAS); time-series analysis; Beijing; ground subsidence
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Hu, B.; Wang, H.-S.; Sun, Y.-L.; Hou, J.-G.; Liang, J. Long-Term Land Subsidence Monitoring of Beijing (China) Using the Small Baseline Subset (SBAS) Technique. Remote Sens. 2014, 6, 3648-3661.
Hu B, Wang H-S, Sun Y-L, Hou J-G, Liang J. Long-Term Land Subsidence Monitoring of Beijing (China) Using the Small Baseline Subset (SBAS) Technique. Remote Sensing. 2014; 6(5):3648-3661.
Hu, Bo; Wang, Han-Sheng; Sun, Yong-Ling; Hou, Jian-Guo; Liang, Jun. 2014. "Long-Term Land Subsidence Monitoring of Beijing (China) Using the Small Baseline Subset (SBAS) Technique." Remote Sens. 6, no. 5: 3648-3661.