Abstract

Detecting the slow motions of high and distant landslides in remote mountain areas has always been a problem. This paper takes the Woda landslide along the Jinsha River as an example to monitor landslide movement. Although some parts of the landslide body have been found to have moved in recent years, the timing and magnitude of motion have not been systematically monitored or interpreted. Here, we apply the SBAS time series strategy using 65-scene Sentinel-1A/B satellite InSAR images and study the spatial distribution and temporal behaviour of landslide movements between July 4, 2018, and August 29, 2020. Our research results show that the cumulative deformation on the left side of the landslide body with concentrated deformation was approximately 200 mm during the 2-year observation period. By calculating the relationship between the InSAR time series and the precipitation around the landslide, it is found that the landslide deformation is closely related to rainfall. GNSS technology is also deployed on the landslide mass and effectively complements InSAR technology. Simultaneously, based on the results of field surveys and hydrological data analysing the landslide's spatial deformation characteristics and deformation factors, the landslide deformation can also be inferred to be related to precipitation. The method used in this paper can be used for early recognition and early warning of high and remote landslides.

Highlights

  • Based on a synthesis of previous studies and the Kumamoto seismic data, this paper uses a combination of multiple interferometric synthetic aperture radar (InSAR) techniques and multisource data inversion methods to analyse the 3D deformation field of the Kumamoto earthquake

  • Based on the results of field surveys and hydrological data analysing the landslide's spatial deformation characteristics and deformation factors, the landslide deformation can be inferred to be related to precipitation

  • 1 Introduction Based on a synthesis of previous studies and the Kumamoto seismic data, this paper uses a combination of multiple interferometric synthetic aperture radar (InSAR) techniques and multisource data inversion methods to analyse the 3D deformation field of the Kumamoto earthquake

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Summary

Introduction

Based on a synthesis of previous studies and the Kumamoto seismic data, this paper uses a combination of multiple interferometric synthetic aperture radar (InSAR) techniques and multisource data inversion methods to analyse the 3D deformation field of the Kumamoto earthquake. With the continuous advancement of China's economic development, large-scale engineering projects such as urbanization, railways, and nuclear and hydroelectric power plants continue to increase in number, and the economic threat from geological disasters is increasing (Chen et al, 2011). The occurrence of two landslide dams blocking the river has increased the need for people to identify potential catastrophic landslide disasters in mountainous areas, analyse the factors that possibly induce them, and further assess related risks.

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