Toggle Main Menu Toggle Search

Open Access padlockePrints

Landslide Detection of the Jinsha River Region Using GACOS Assisted InSAR Stacking利用GACOS辅助下InSAR Stacking对金沙江流域进行滑坡监测

Lookup NU author(s): Chen YuORCiD, Dr Chuang Song, Dr Ruya Xiao

Downloads

Full text for this publication is not currently held within this repository. Alternative links are provided below where available.


Abstract

© 2021, Editorial Board of Geomatics and Information Science of Wuhan University. All right reserved.Objectives: The Sichuan⁃Tibet Railway crosses the Jinsha River specifically the section from Xiongsong Town to Shadong Town, Gongjue County, Tibet Autonomous Region, in which exist strong topography variations and many potential geohazards, and hence it urgent to detect the potential geohazards in this region to ensure the railway safety. Methods: In this paper, 61 Sentinel⁃1 ascending, 53 Sentinel⁃1 descending and 7 advanced land observing satellite 2 (ALOS⁃2) ascending images are used to derive the annual mean deformation rates in the satellite radar line of sight (LOS) with two advanced InSAR( interferometric synthetic aperture radar) approaches, namely generic atmospheric correction online service for InSAR(GACOS)assisted InSAR Stacking and LiCSBAS. The three LOS annual mean deformation rate maps are then used to determine 2D surface movements (one along the slope and the other perpendicular to the slope) in the study region. Results: The comparison between GACOS assisted InSAR Stacking and LiCSBAS results show that they agree with each other with correlation coefficients over 0.92 for the LOS deformation rates and over 0.85 for the 2D deformation rates, suggesting the reliability of GACOS assisted InSAR Stacking. The maximum annual deformation rate of 163 mm/a can be observed in the slope direction and seven landslides (A, B, C, D, E, F, G) can be clearly identified, which in turn lays the foundation for future real⁃time monitoring. Based on the detailed analysis of the seven regions by using InSAR and optical interpretation results, it is found that the seven landslides had relatively obvious deformation. Landslides A, B, C and D are active landslides, which might cause the result of river blocking due to overall instability. At present, landslides E, F and G are still in the stage of slow deformation. Conclusions: This study also find that GACOS assisted InSAR Stacking can effectively remove long⁃band and topographic related atmospheric delay error with the help of GACOS, which has the advantages of being simple, effective, fast, and easy to popularize and apply. GACOS assisted InSAR Stacking technology can be used to quickly identify potential landslide hazards.


Publication metadata

Author(s): Zhang C, Li Z, Yu C, Song C, Xiao R, Peng J

Publication type: Article

Publication status: Published

Journal: Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University

Year: 2021

Volume: 46

Issue: 11

Pages: 1649-1657

Online publication date: 05/11/2021

Acceptance date: 02/04/2020

ISSN (print): 1671-8860

Publisher: Editorial Board of Medical Journal of Wuhan University

URL: https://doi.org/10.13203/j.whugis20200675

DOI: 10.13203/j.whugis20200675


Altmetrics

Altmetrics provided by Altmetric


Share