Monitoring Land Subsidence in Wuhan City (China) using the SBAS-InSAR Method with Radarsat-2 Imagery Data

Abstract

Wuhan city is the biggest city in central China and has suffered subsidence problems in recent years because of its rapid urban construction. However, longtime and wide range monitoring of land subsidence is lacking. The causes of subsidence also require further study, such as natural conditions and human activities. We use small baseline subset (SBAS) interferometric synthetic aperture radar (InSAR) method and high-resolution RADARSAT-2 images acquired between 2015 and 2018 to derive subsidence. The SBAS-InSAR results are validated by 56 leveling benchmarks where two readings of elevation were recorded. Two natural factors (carbonate rock and soft soils) and three human factors (groundwater exploitation, subway excavation and urban construction) are investigated for their relationships with land subsidence. Results show that four major areas of subsidence are detected and the subsidence rate varies from −51.56 to 27.80 millimeters per year (mm/yr) with an average of −0.03 mm/yr. More than 83.81% of persistent scattered (PS) points obtain a standard deviation of less than −6 mm/yr, and the difference between SBAS-InSAR method and leveling data is less than 5 mm/yr. Thus, we conclude that SBAS-InSAR method with Radarsat-2 data is reliable for longtime monitoring of land subsidence covering a large area in Wuhan city. In addition, land subsidence is caused by a combination of natural conditions and human activities. Natural conditions provide a basis for subsidence and make subsidence possible. Human activities are driving factors and make subsidence happen. Moreover, subsidence information could be used in disaster prevention, urban planning, and hydrological modeling.

SBAS-InSAR Based Deformation Detection of Urban Land, Created from Mega-Scale Mountain Excavating and Valley Filling in the Loess Plateau: The Case Study of Yan’an City

“…This technique overcomes the low coherence of some interferograms induced by single super-master images and reduces the requirement of the quantity of SAR images with respect to PS-InSAR [29]. SBAS-InSAR is widely applied in land subsidence detection [26,27,31], and is based on the following equations [25]:…”

“…More specifically, a permanent scatterers InSAR (PS-InSAR) method proposed by Ferretti et al and a small baseline subset InSAR (SBAS-InSAR) method introduced by Berardino et al have been widely used in related fields with millimetric accuracy [23][24][25]. Zhang and Zhou analyzed Wuhan land subsidence using SBAS-InSAR, and observed four major subsidence zones affected by urban construction and industrial development [26,27]. Chaussard et al calculated land subsidence in Mexican and Indonesian cities using the SBAS-InSAR method, and found that land subsidence was directly related to the overexploitation of groundwater [2,28].…”

Remote Sensing X-Band SAR Data for Land Subsidence and Pavement Monitoring

“…The land subsidence starts slowly and spreads to adjacent areas, where it could affect agricultural, industrial, and urban activities. Land subsidence has been recognized as a serious environmental problem [ 5 , 6 , 7 ]. There are some strategies to monitor or control land subsidence, but if it progresses without the required supervision, the land could lose its functionality in the future.…”

Special Issue “Synthetic Aperture Radar (SAR) Techniques and Applications”

“…The following seven papers are specifically dedicated to applications. The first two [13,14] use SAR interferometry (InSAR) for investigating displacements related to land subsidence and highway deformation. Multi-temporal InSAR is a well-established technique currently applied to displacement monitoring thanks to the availability of reliable processing tools developed during the last two decades, as well as data archives continuously updated by operative satellite missions.…”

“…In [13], high-resolution RADARSAT-2 SAR data were processed through the Small BAseline Subset (SBAS) algorithm for deriving 3-year displacement time series over Wuhan city, which suffers from subsidence problems related to urban construction. First, the InSAR results were compared to measurements from levelling benchmarks for a quality check.…”