Japan Geoscience Union Meeting 2022

Presentation information

[J] Poster

S (Solid Earth Sciences ) » S-TT Technology & Techniques

[S-TT39] Synthetic Aperture Radar and its application

Thu. Jun 2, 2022 11:00 AM - 1:00 PM Online Poster Zoom Room (27) (Ch.27)

convener:Takahiro Abe(Graduate School of Bioresources, Mie University ), convener:Yohei Kinoshita(University of Tsukuba), Yuji Himematsu(National Research Institute for Earth Science and Disaster Resilience), convener:Haemi Park(Japan Aerospace Exploration Agency), Chairperson:Takahiro Abe(Graduate School of Bioresources, Mie University), Yohei Kinoshita(University of Tsukuba), Yuji Himematsu(National Research Institute for Earth Science and Disaster Resilience), Haemi Park(Japan Aerospace Exploration Agency)

11:00 AM - 1:00 PM

[STT39-P08] Slow-Moving Landslide Monitoring at Jichang Based on Sential-1 Time Series Analysi

*YIXUAN LIU1, Yohei Kinoshita1 (1.University of Tsukuba)

Keywords:MT-InSAR, Sentinel-1A, Landslide

With the development of social economy and the increase of population, the potential risk of natural disasters is also increasing. For the people who living near the mountain area, the disaster prevention of the slop has always been the focus of attention. As one of the most destructive natural disasters, landslides are a major research target for geological hazard prevention. The use of efficient and convenient earth observation technology at a certain regional spatial scale is one of the important elements in landslide geological hazard prevention and control.

In Jichang county located in Shuicheng County, Guizhou Province, a sudden landslide occurred on 23 July 2019, impacting the slope settlement, involving a total of 77 people and 27 houses, 21 of which were buried. The area around the Jichang landslide is still inhabited to date after the landslide occurred. According to news reports of the landslide, there is still a high probability of landslides occurring in and around the Jichang landslide. Therefore, this study aims to evaluate the stability of the slope and its surroundings by analyzing a stack of SAR data covering the area of interest in the year following the landslide to detect ground displacements. In this study, the PSInSAR method, one of SAR time series analysis methods, was used to analyze the stability around the town of Jichang county, where a landslide had occurred.

Differential interferometric synthetic aperture radar (DInSAR) has the potential to accurately observe ground deformation along the line of dight (LOS) direction up to a few millimeters. However, there are also several problems such as atmospheric disturbances, temporal decorrelation, geometrical decorrelation, and ambiguity of whole cycles. In order to eliminate these problems associated with DInSAR processing, the technique of time series analysis has been greatly developed in recent years. The persistent scatterer InSAR (PSInSAR) is one of the representative SAR time series analysis which has great application in the study of deformation at small scales and high accuracy (an order of mm/year). In this study, the ISCE+StaMPS process was used to analyze Sentinel-1 SAR data covering the study area. The most important feature of StaMPS is that it exploits the spatial correlation between SAR data from different time phases. This allows StaMPS to detect more PS points compared to other techniques. The more PS points there are, the easier it is to perform phase unwrapping. Here, SAR data were acquired from 1 August 2019 to 30 October 2020. The Sentinel-1A TOPS mode data consist of series of bursts with mutual overlaps, which provides a wide swath with resolution of 5×20. The Shuttle Radar Topography Mission (SRTM) data product released in 2015 by the U.S. Geological Survey (USGS) with a spatial resolution of 30m was used to remove the topographic phase. The reduction in vegetation and the exposure of rock and soil caused by the landslide have led to the selection of a higher density of PS points in the area of the Jichang landslide, which facilitates the detection of ground deformation.

The attached figure shows the annual surface deformation rates derived by the PS technique along the LOS direction between 1 August 2019 and 30 October 2020. According to the result, the PS points with deformation are mainly located in the middle and lower parts of the landslide, while the PS points in the upper part of the landslide are more stable. The results of the deformation in the LOS direction show a maximum deformation of 48 mm in May 2020. At the time of the presentation, we will include additional data sources and results to investigate the stability of the landslide and the causes of the maximum displacement occurred in May 2020.