An Improved Method for Automatic Identification and Assessment of Potential Geohazards Based on MT-InSAR Measurements

Shuran Luo,Haiyan Wang,Kailiang Deng,Yinggang Zhao,Kaifeng Li,Zhiqiang Xiong,Guangcai Feng,Yuexin Wang

doi:10.3390/rs13173490

Abstract

Multi-temporal Interferometric Synthetic Aperture Radar (MT-InSAR) has been widely used for ground motion identification and monitoring over large-scale areas, due to its large spatial coverage and high accuracy. However, automatically locating and assessing the state of the ground motion from the massive Interferometric Synthetic Aperture Radar (InSAR) measurements is not easy. Utilizing the spatial-temporal characteristics of surface deformation on the basis of the Small Baseline Subsets InSAR (SBAS-InSAR) measurements, this study develops an improved method to locate potential unstable or dangerous regions, using the spatial velocity gradation and the temporal evolution trend of surface displacements in large-scale areas. This method is applied to identify the potential geohazard areas in a mountainous region in northwest China (Lajia Town in Qinghai province) using 73 and 71 Sentinel-1 images from the ascending and descending orbits, respectively, and an urban area (Dongguan City in Guangdong province) in south China using 32 Sentinel-1 images from the ascending orbit. In the mountainous area, 23 regions with potential landslide hazards have been identified, most of which have high to very high instability levels. In addition, the instability is the highest at the center and decreases gradually outward. In the urban area, 221 potential hazards have been identified. The moderate to high instability level areas account for the largest proportion, and they are concentrated in the farmland irrigation areas, and construction areas. The experiment results show that the improved method can quickly identify and evaluate geohazards on a large scale. It can be used for disaster prevention and mitigation.

Highlights

Interferometric Synthetic Aperture Radar (InSAR) has become an important technique for large-scale ground deformation monitoring, as it has wide spatial coverage and high monitoring accuracy [1]
The automatic extraction method was employed to investigate the potential hazards based on the MT-InSAR results, where σ A of the ascending results was 3.6 mm/yr and σD of the descending results was 5.0 mm/yr
We introduced an improved method for automatic identification and assessment of potential geohazards, which can show the spatial and temporal information of the deformation, and quantitatively evaluate the instability of the deformed area

Summary

Introduction

InSAR has become an important technique for large-scale ground deformation monitoring, as it has wide spatial coverage and high monitoring accuracy [1]. The accuracy and efficiency of InSAR data processing have been greatly improved by the MT-InSAR technologies [3], such as Persistent Scatterer InSAR (PS-InSAR) [4,5], SBAS-InSAR [6,7] and SqueeSAR [8], which have overcome some limitations (temporal decorrelation, atmospheric delay, and ramp phases) inherent in Differential Interferometry SAR (DInSAR) [9,10], and have been extensively exploited to geological disaster monitoring, including urban subsidence [11,12], landslides [13,14], Remote Sens. Many efforts have been made to investigate and manage geohazards, including the case study of a single geohazard, landslide identification in mountainous areas [19,20,21]

Results

Discussion

Conclusion