Abstract
In recent years, many cities in the Chinese loess plateau (especially in Shanxi province) have encountered ground subsidence problems due to the construction of underground projects and the exploitation of underground resources. With the completion of the world’s largest geotechnical project, called “mountain excavation and city construction,” in a collapsible loess area, the Yan’an city also appeared to have uneven ground subsidence. To obtain the spatial distribution characteristics and the time-series evolution trend of the subsidence, we selected Yan’an New District (YAND) as the specific study area and presented an improved time-series InSAR (TS-InSAR) method for experimental research. Based on 89 Sentinel-1A images collected between December 2017 to December 2020, we conducted comprehensive research and analysis on the spatial and temporal evolution of surface subsidence in YAND. The monitoring results showed that the YAND is relatively stable in general, with deformation rates mainly in the range of −10 to 10 mm/yr. However, three significant subsidence funnels existed in the fill area, with a maximum subsidence rate of 100 mm/yr. From 2017 to 2020, the subsidence funnels enlarged, and their subsidence rates accelerated. Further analysis proved that the main factors induced the severe ground subsidence in the study area, including the compressibility and collapsibility of loess, rapid urban construction, geological environment change, traffic circulation load, and dynamic change of groundwater. The experimental results indicated that the improved TS-InSAR method is adaptive to monitoring uneven subsidence of deep loess area. Moreover, related data and information would provide reference to the large-scale ground deformation monitoring and in similar loess areas.
Highlights
Yan’an city of Shaanxi province is located between loess gullies, which greatly restricts the development of the local tourism
Synthetic aperture radar interferometry based on two-view or multi-view synthetic aperture radar image data has been widely used in regional ground subsidence detection, early identification and monitoring of landslides and other geological hazards [3], and has gradually played an indispensable and important role [4] because of its features of all-day, all-weather, wide coverage and high accuracy of deformation monitoring [5]
The selection of highly coherent interference pairs is performed based on the Python language, and the deformation rates are calculated by inversion of the interferometric network using least squares (WLS) solutions in Mintpy software
Summary
Yan’an city of Shaanxi province is located between loess gullies, which greatly restricts the development of the local tourism. The proposed small baseline subsets InSAR (SBAS-InSAR) approach [6,7,8,9] has greatly avoided the decoherence phenomenon caused by long temporal and spatial baselines and reduced the influence of topography on the differential and atmospheric effects. Such a method greatly improves the monitoring accuracy of the InSAR technique and provides an effective means to detect the spatial distribution and spatial and temporal evolution of regional ground subsidence. The traditional SBAS-InSAR approach has a disadvantage in adaptability in the natural surface and vegetation areas [10]
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