The Monitoring and Analysis of Land Subsidence in Kunming (China) Supported by Time Series InSAR

Abstract

As urban construction has been leaping forward recently, large-scale land subsidence has been caused in Kunming due to the special hydrogeological conditions of the city; the subsidence scope has stretched out, and the subsidence rate has been rising year by year. As a consequence, Kunming’s sustainable development has seriously hindered. The PS-InSAR (Persistent Scatterer Interferometric Synthetic Aperture Radar) and the SBAS-InSAR (Small Baseline Subsets Interferometric Synthetic Aperture Radar) technologies were adopted to process the descending Sentinel-1A data stacks from July 2018 to November 2020 to monitor the land subsidence of Kunming, so as to ensure the sustainable development of the city. Moreover, the causes were analyzed. As revealed by the results, (1) the overall subsidence trend of Kunming was large in the south (Dian lakeside), whereas it was relatively small in the north. The significant subsidence areas showed major distributions in Xishan, Guandu and Jining district. The maximal average subsidence rates of PS-InSAR and SBAS-InSAR were −78 mm/a and −88 mm/a, respectively. (2) The ground Subsidence field of Kunming was analyzed, and the correlation coefficient R2 of the two methods was reported as 0.997. In comparison with the leveling data of the identical period, the root mean square error (RMSE) is 6.5 mm/a and 8.5 mm/a, respectively. (3) Based on the urban subway construction data, geological structure, groundwater extraction data and precipitation, the causes of subsidence were examined. As revealed by the results, under considerable urban subways construction, special geological structures and excessive groundwater extraction, the consolidation and compression of the ground surface could cause the regional large-area subsidence. Accordingly, the monthly average precipitation in Kunming in the identical period was collected for time series analysis, thereby indicating that the land subsidence showed obvious seasonal variations with the precipitation. The results of this study can provide data support and facilitate the decision-making for land subsidence assessment, forecasting and construction planning in Kunming.

Urban Ground Subsidence Monitoring and Prediction Using Time-Series InSAR and Machine Learning Approaches: A Case Study of Tianjin, China

“…Compared to existing literature (Xiao et al 2022;Zhou et al 2024), our study not only reveals the association between rainfall and subsidence but also highlights variations in subsidence responses among different monitoring points. These differences may relate to the geological conditions, soil types, and groundwater ow characteristics speci c to each monitoring location.…”

“…In our study area, both Line 1 and Line 6 were constructed during the investigation period. Due to the large-scale excavation along subway routes, subsidence is commonly observed near stations, with major hubs experiencing more pronounced effects due to signi cant geological losses during excavation (Osmanoğlu et al 2011;Xiao et al 2022).…”

Dual Impacts of Urbanization and Precipitation on Subsidence in Chongqing Revealed by SBAS-InSAR

“…Moreover, ground subsidence along the subway lines is commonly distributed near the stations due to the large scale of excavation, and ground subsidence tends to be more severe at the hub stations due to the large stratigraphic losses, and the majority of subway tunnels are commonly built within soft clay strata characterized by elevated water content, substantial compressibility, and limited permeability. This choice is because the soil can be easily compacted during engineering construction and the clay can selfconsolidate under pressure, so uneven subsidence is often detected, especially near the stations (Osmanoğlu et al 2011;Xiao et al 2022). The Luxi station did not show signi cant subsidence until June 2021 and started to settle signi cantly after June because the construction of Line 4, where the Luxi station was located, was completed and entered the trial operation phase in January 2022, and under dynamic loads such as recurring vehicular and subsequent oscillations, together with piling, the stresses in the surrounding soil were redistributed, which caused subsidence and deformation of the foundation and intensi es the process of ground subsidence (Xu et al 2020).…”

An Interferogram Re-Flattening Method for InSAR Based on Local Residual Fringe Removal and Adaptively Adjusted Windows

“…Then, the influence of inaccurate orbit information will be partly removed. To obtain the correct interferometric phase of terrain or terrain deformation, many studies have adopted the step of refinement and re-flattening, and it has been proven to be effective for many InSAR data, such as Sentinel-1 InSAR data [31][32][33], ALOS/PALSAR-1 InSAR data [34], and Radarsat-2 [35]. In addition, some scholars have proposed other methods for baseline correction and re-flattening.…”

“…Although there is a lack of quantitative analyses, the idea of local flattening adopted by the above studies is indeed effective from the visual effect of the re-flattened interferograms. However, the regret is that the local window is set to be a smaller one at the steep terrain in [38], and the estimated frequency of flat-earth interferometric fringes within the small window will be inaccurate [33]. In addition, a flat-earth phase removal algorithm improved with frequency information of the interferogram was proposed in [39], and the original interferogram is divided into several blocks during the processing.…”