Work

Deformation Monitoring for Mountain Excavation and City Construction Area in Yan’an New District by Improved MT-InSAR Method

Year: 2025

Type: article

Abstract: The increasing demand for land in the cities of Loess Plateau, China has intensified the conflict between people and land. Therefore, large-scale Mountain Excavation and City Creation (MECC) projects have emerged in many densely populated cities, where Yan'an New District in China was one of the largest MECC projects. Interferometric Synthetic Aperture Radar (InSAR) technology can be used to monitor historical uneven deformation in MECC areas. However, it is difficult to acquire high-precision and high-density deformation field by the traditional InSAR technique due to the serious DEM errors, incoherence errors caused by human engineering activities and longtime baselines, and phase unwrapping errors. Therefore, an improved MT-InSAR method is proposed to estimate the ground height changes, correct the phase unwrapping errors and densify the deformation monitoring points. Moreover, bias adjustment and deformation time series fusion are used to improve the accuracy and temporal resolution of the deformation time series. The results show that the ground height changes in Yan'an New district are between -100 m and 100 m. The improved method can improve the point density by 1.4 times compared with the DS-InSAR method. The fusion results improve the temporal resolution twice and increase the accuracy about 20% compared with the individual track monitoring results. Finally, 60% of high fill areas in Yan'an New district are predicted to be stable within 5 years. In the next 30 years, Yan'an New District will also undergo deformation of more than 450mm. This research extends the InSAR technique in terms of height changes estimation. The application of this method can be beneficial to the prevention and controlling of geological hazards corresponding to the MECC projects.

Source: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

DOI: 10.1109/jstars.2025.3588158