Country-scale assessment of urban areas, population, and households exposed to land subsidence using Sentinel-1 InSAR, and GPS time series

Abstract

The increased need for water resources in urban sprawls and intense droughts has forced more aggressive groundwater extraction resulting in numerous urban areas undergoing land subsidence. In most cases, only some large metropolitan areas have been well-characterized for subsidence. However, there is no existing country-wide assessment of urban areas, population, and households exposed to this process. This research showcases a methodology to systematically evaluate urban localities with land subsidence higher than − 2.8 cm/year throughout Mexico. We used Interferometric Synthetic Aperture Radar (InSAR) tools with a dataset of 4611 scenes from European Space Agency’s Sentinel-1 A/B SAR sensors acquired from descending orbits from September 2018 through October 2019. This dataset was processed at a supercomputer using InSAR Scientific Computing Environment and the Miami InSAR Time Series software in Python software. The quality and calibration of the resulting velocity maps are assessed through a large-scale comparison with observations from 100 continuous GPS sites throughout Mexico. Our results show that an urban area of 3797 km2, 6.9 million households, and 17% of the total population in Mexico is exposed to subsidence velocities of faster than − 2.8 cm/year, in more than 853 urban localities within 29 land subsidence regions. We also confirm previous global potential estimations of subsidence occurrence in low relief areas over unconsolidated deposits and where groundwater aquifers are under stress. The presented research demonstrates the capabilities for surveying urban areas exposed to land subsidence at a country-scale level by combining Sentinel-1 velocities with spatial national census data.

Spatio-Temporal Characteristics of Land Subsidence and Driving Factors Analysis in Shenzhen

“…From the final subsidence results, it is evident that Shenzhen indeed experiences significant land subsidence, with spatial distribution being quite dispersed and the causes The STD of the entire subsidence rate map is 3.9. Reliable subsidence regions were extracted based on ±1.5 times (5.85) the STD, in Figure 6, as within 1.5 times the STD is typically considered stable, while areas beyond this threshold are likely genuine subsidence regions [38,39]. It was observed that significant land subsidence is distributed in the coastal reclamation area on the western side of Bao'an District and in the reservoir area of Qinglinjing.…”

Development of a Proof-of-Concept A-DInSAR-Based Monitoring Service for Land Subsidence

“…Recently, other examples of nationwide A-DInSAR data have been processed to monitor the ground deformations in Greece [22] and Japan [23]. Nationwide and country scale A-DInSAR data are used for several purposes such as strategic water facilities monitoring in Hungary [24], landslide mapping and risk management in Italy [25], railway monitoring in the Netherlands [26], and assessment of areas, population, and households exposed to land subsidence in Mexico [27].…”