Distributed Scatterer InSAR Reveals Surface Motion of the Ancient Chaoshan Residence Cluster in the Lianjiang Plain, China

Abstract

The Lianjiang Plain in China and ancient villages distributed within the plain are under the potential threat of surface motion change, but no effective monitoring strategy currently exists. Distributed Scatterer InSAR (DSInSAR) provides a new high-resolution method for the precise detection of surface motion change. In contrast to the first-generation of time-series InSAR methodology, the distributed scatterer-based method focuses both on pointwise targets with high phase stability and distributed targets with moderate coherence, the latter of which is more suitable for the comprehensive environment of the Lianjiang Plain. In this paper, we present the first study of surface motion change detection in the Lianjiang Plain, China. Two data stacks, including 54 and 29 images from Sentinel-1A adjacent orbits, are used to retrieve time-series surface motion changes for the Lianjiang Plain from 2015 to 2018. The consistency of measurement has been cross-validated between adjacent orbit results with a statistically significant determination coefficient of 0.92. The temporal evolution of representative measuring points indicates three subzones with varied surface patterns: Eastern Puning (Zone A) in a slight elastic rebound phase with a moderate deformation rate (0–40 mm/yr), Chaonan (Zone B) in a substantial subsidence phase with a strong deformation rate (−140–0 mm/yr), and Chaoyang (Zone C) in a homogeneous and stable situation (−10–10 mm/yr). The spatial distribution of these zones suggests a combined change dynamic and a strong concordance of factors impacting surface motion change. Human activities, especially groundwater exploitation, dominate the subsidence pattern, and natural conditions act as a supplementary inducement by providing a hazard-prone environment. The qualitative and quantitative analysis of spatial and temporal details in this study provides a basis for systematic surface motion monitoring, cultural heritage protection and groundwater resources management.

Understanding the Spatiotemporal Characteristics of Land Subsidence and Rebound in the Lianjiang Plain Using Time-Series InSAR with Dual-Track Sentinel-1 Data

“…However, there are subtle differences when it comes to the magnitude of the deformation rate. The maximum subsidence detected in this study was located in Chaonan (T1), which is similar to the findings of Du et al [37] and Liu et al [13]. However, the peak subsidence estimated from this work (−124.4 mm/year) was slightly lower than in those studies (157.2 mm/year and −140 mm/year).…”

“…In general, the consistency in both spatial pattern and magnitude of the subsidence and uplift between this work and previous ones can be found. A regional subsidence bowl (T1) of centimeter order has been found at all sites in previous studies [13,37,53]. The two large uplift areas at Puning (S1) and Chaonan (S2) also coincide with previously detected uplifting bowls [39,40].…”

“…These studies have demonstrated the feasibility of the TS-InSAR method for determining surface displacement in the LJP. In addition, these studies have revealed the influence of structural geology, land use, and faults on land subsidence [13,37]. Subsequent land subsidence was also observed by Zhang et al [38].…”

“…To date, few deformation studies have been conducted in the LJP using point-based surveying methods, including leveling surveys and Global Positioning System (GPS), because of their high cost and time-consuming nature [13]. Therefore, there is a need for accessible and effective methods to monitor the distribution and status of land deformation in the LJP.…”

Quantifying earth surface changes with multi-sensor SAR imagery

“…For rural areas, Distributed Scatterer InSAR (DSInSAR) has been developed (Touzi et al, 1999;Berardino et al, 2002;Hooper, 2008;Ferretti et al, 2011;Liu et al, 2019) and the corresponding data processing is displayed in Fig. 2.3.…”