4.7 Article

Regional Land Subsidence Analysis in Eastern Beijing Plain by InSAR Time Series and Wavelet Transforms

期刊

REMOTE SENSING
卷 10, 期 3, 页码 -

出版社

MDPI
DOI: 10.3390/rs10030365

关键词

land subsidence; InSAR; hydraulic head; continuous wavelet transform

资金

  1. National Natural Science Foundation of China [41171335/D010702, 41401492/D010702]
  2. Natural Science Foundation of Tianjin City [16JCZDJC40400]

向作者/读者索取更多资源

Land subsidence is the disaster phenomenon of environmental geology with regionally surface altitude lowering caused by the natural or man-made factors. Beijing, the capital city of China, has suffered from land subsidence since the 1950s, and extreme groundwater extraction has led to subsidence rates of more than 100 mm/year. In this study, we employ two SAR datasets acquired by Envisat and TerraSAR-X satellites to investigate the surface deformation in Beijing Plain from 2003 to 2013 based on the multi-temporal InSAR technique. Furthermore, we also use observation wells to provide in situ hydraulic head levels to perform the evolution of land subsidence and spatial-temporal changes of groundwater level. Then, we analyze the accumulated displacement and hydraulic head level time series using continuous wavelet transform to separate periodic signal components. Finally, cross wavelet transform (XWT) and wavelet transform coherence (WTC) are implemented to analyze the relationship between the accumulated displacement and hydraulic head level time series. The results show that the subsidence centers in the northern Beijing Plain is spatially consistent with the groundwater drop funnels. According to the analysis of well based results located in different areas, the long-term groundwater exploitation in the northern subsidence area has led to the continuous decline of the water level, resulting in the inelastic and permanent compaction, while for the monitoring wells located outside the subsidence area, the subsidence time series show obvious elastic deformation characteristics (seasonal characteristics) as the groundwater level changes. Moreover, according to the wavelet transformation, the land subsidence time series at monitoring well site lags several months behind the groundwater level change.

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