Wuhan Surface Subsidence Analysis in 2015–2016 Based on Sentinel-1A Data by SBAS-InSAR

Abstract

Abstract:The Terrain Observation with Progressive Scans (TOPS) acquisition mode of Sentinel-1A provides a wide coverage per acquisition and features a repeat cycle of 12 days, making this acquisition mode attractive for surface subsidence monitoring. A few studies have analyzed wide-coverage surface subsidence of Wuhan based on Sentinel-1A data. In this study, we investigated wide-area surface subsidence characteristics in Wuhan using 15 Sentinel-1A TOPS Synthetic Aperture Radar (SAR) images acquired from 11 April 2015 to 29 April 2016 with the Small Baseline Subset Interferometric SAR (SBAS InSAR) technique. The Sentinel-1A SBAS InSAR results were validated by 110 leveling points at an accuracy of 6 mm/year. Based on the verified SBAS InSAR results, prominent uneven subsidence patterns were identified in Wuhan. Specifically, annual average subsidence rates ranged from −82 mm/year to 18 mm/year in Wuhan, and maximum subsidence rate was detected in Houhu areas. Surface subsidence time series presented nonlinear subsidence with pronounced seasonal variations. Comparative analysis of surface subsidence and influencing factors (i.e., urban construction, precipitation, industrial development, carbonate karstification and water level changes in Yangtze River) indicated a relatively high spatial correlation between locations of subsidence bowl and those of engineering construction and industrial areas. Seasonal variations in subsidence were correlated with water level changes and precipitation. Surface subsidence in Wuhan was mainly attributed to anthropogenic activities, compressibility of soil layer, carbonate karstification, and groundwater overexploitation. Finally, the spatial-temporal characteristics of wide-area surface subsidence and the relationship between surface subsidence and influencing factors in Wuhan were determined.

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].…”

Measuring Surface Subsidence in Wuhan, China With Sentinel-1 Data Using Psinsar

“…it is often caused by consolidation and compression of underground unconsolidated strata . Surface subsidence is also one of the major disasters that can cause serious damage to infrastructures, tunnels, roads, bridges, and buildings, which made a huge impact to the safety of the cities Zhou et al, 2017). With its long history of subsidence, way back to the 1930s (Fan, 2006), Wuhan still continuously suffers from this hazards due to the fast urban development and subway constructions (Goethals, 2011).Compared to single-point-measurement methods such as ground leveling (Baldi et al, 2009;Poland et al, 2006) or Global Navigation Satellite System (GNSS) (Carminati et al, 2002;Psimoulis et al, 2007), Differential Interferometric Synthetic Aperture Radar (D-InSAR) has been developed to measure relatively slow surface motion between two SAR image acquisitions (Avallone et al, 1999) and it has been used widely for subsidence monitoring (Cigna et al, 2012;Solari et al, 2016).…”

Monitoring and Analyzing the Surface Subsidence in Langfang by Time-Series Interferometric Radar Technique

“…In recent decades, the emergence of synthetic aperture radar (SAR) technique provides an effective method for effectively monitoring the urban overall surface subsidence. Differential Interferometric Synthetic Aperture Radar (DInSAR) overcomes the shortcomings of traditional monitoring methods such as low spatial resolution and high cost (Zhou et al, 2017), and has been successfully applied to seismic deformation detection (Li et al, 2011), landslides (Calò et al, 2014), and urban surface subsidence analysis (Guo et al, 2016). However, DInSAR is susceptible to atmospheric delay, which is difficult to obtain high precision deformation information.…”