Multi-dimensional deformation inversion of landslides using combined sentinel-1A ascending and descending orbit data

Quan ZHOU, YaNan JIANG, Peng LÜ, Dong WANG, Rui ZENG

Prog Geophy ›› 2024, Vol. 39 ›› Issue (4) : 1427-1439.

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Prog Geophy ›› 2024, Vol. 39 ›› Issue (4) : 1427-1439. DOI: 10.6038/pg2024HH0288

Multi-dimensional deformation inversion of landslides using combined sentinel-1A ascending and descending orbit data

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Abstract

The Jinsha River,located in the upper reaches of the Yangtze River,is prone to frequent geological hazards on both sides due to its unique terrain and geological conditions. Firstly,the article employed the SBAS-InSAR technique to capture the surface deformation characteristics of landslides in the Gongjue County of the Jinsha River Basin in the Tibet Autonomous Region,spanning the period from October 2014 to October 2018, spanning from Shadong Township to Xiongsong Township. Subsequently,by integrating ascending and descending orbit DInSAR datasets,the two-dimensional deformation information was obtained in this region. Building upon this foundation,the Shadong landslide was selected as the research subject,the surface parallel flow constraint model was introduced to conduct three-dimensional deformation monitoring studies on the landslide.The results show that: (1) The study area is characterized by fragmented terrain and the development of geological hazards. Utilizing ascending and descending orbit Sentinel-1A data,nine and thirteen deformation regions were detected,respectively. Among them,the maximum deformation rate in certain areas reached 150 mm/year.(2) The two-dimensional deformation results reveal that the maximum deformation rates in the east-west and vertical directions are 147 mm/year and-70 mm/year,respectively. The spatial distribution characteristics of landslide deformation vary significantly at different locations. (3) The presentation of the three-dimensional deformation results shows the movement direction of the Shadong landslide in various locations,with the slope mainly moving in the northeast direction and accompanied by a sinking state. (4) Based on the rainfall factors in the region,the correlation between typical landslide deformation and rainfall was analyzed. The results show that Intense rainfall is critical driving factor for accelerating landslide deformation.

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Quan ZHOU , YaNan JIANG , Peng LÜ , et al . Multi-dimensional deformation inversion of landslides using combined sentinel-1A ascending and descending orbit data[J]. Progress in Geophysics. 2024, 39(4): 1427-1439 https://doi.org/10.6038/pg2024HH0288

References

Berardino P , Fornaro G , Lanari R . A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms. IEEE Transactions on Geoscience and Remote Sensing, 2002, 40(11): 2375 2383
Dong J H . Research on application of InSAR technology in high-level and long-distance landslide recognition and monitoring in Jinsha river basin[Master's thesis](in Chinese). Xi'an: Chang'an University, 2021
Ferretti A , Prati C , Rocca F . Permanent scatterers in SAR interferometry. IEEE Transactions on Geoscience and Remote Sensing, 2001, 39(1): 8-20
Hu J , Li Z W , Ding X L . Resolving three-dimensional surface displacements from InSAR measurements: A review. Earth-Science Reviews, 2014, 133 1-17
Hu X , Bürgmann R , Fielding E J . Internal kinematics of the Slumgullion landslide (USA) from high-resolution UAVSAR InSAR data. Remote Sensing of Environment, 2020a, 251 112057
Hu X , Bürgmann R , Schulz W H . Four-dimensional surface motions of the Slumgullion landslide and quantification of hydrometeorological forcing. Nature Communications, 2020b, 11(1): 2792
Li X , Guo C B , Yang Z H . Development characteristics and formation mechanism of the Xiongba giant ancient landslide in the Jinshajiang tectonic zone. Geoscience, 2021, 35(1): 47-55
Liao M S , Dong J , Li M H . Radar remote sensing for potential landslides detection and deformation monitoring. National Remote Sensing Bulletin, 2021, 25(1): 332-341
Liu C W , Jiang Y N , Liao L . Identification and analysis of the main deformation area of Heifangtai platform with SBAS-InSAR. Science of Surveying and Mapping, 2022, 47(5): 56-65
Liu X J , Zhao C Y , Zhang Q . Three-dimensional and long-term landslide displacement estimation by fusing C- and L-band SAR observations: a case study in Gongjue County, Tibet, China. Remote Sensing of Environment, 2021, 267 112745
Lu H Y , Li W L , Xu Q . Early detection of landslides in the upstream and downstream areas of the Baige landslide, the Jinsha river based on optical remote sensing and InSAR technologies. Geomatics and Information Science of Wuhan University, 2019, 44(9): 1342-1354
Osmanoǧlu B , Sunar F , Wdowinski S . Time series analysis of InSAR data: methods and trends. ISPRS Journal of Photogrammetry and Remote Sensing, 2016, 115 90-102
Samsonov S V , d'Oreye N . Multidimensional time-series analysis of ground deformation from multiple InSAR data sets applied to Virunga Volcanic Province. Geophysical Journal International, 2012, 191(3): 1095-1108
Samsonov S V , d'Oreye N . Multidimensional Small Baseline Subset (MSBAS) for two-dimensional deformation analysis: case study Mexico city. Canadian Journal of Remote Sensing, 2017, 43(4): 318-329
Sheng L , Zhang L , Du Y L . Characteristics of deformation of landslide and ground fissure in Gongjue area of Jinsha river Basin, China based on DS-InSAR technology. Journal of Earth Sciences and Environment, 2022, 44(5): 814-825
Shi X G , Hu X . Characterization of landslide displacements in an active fault zone in Northwest China. Earth Surface Processes and Landforms, 2023, 48(10): 1926-1939
Tihonov A N . Solution of incorrectly formulated problems and the regularization method. Soviet Math, 1963, 4 1035-1038
Yan Y Q , Guo C B , Zhang Y S . Study of the deformation characteristics of the Xiongba ancient landslide based on SBAS-InSAR method, Tibet, China. Acta Geologica Sinica, 2021, 95(11): 3556-3570
Yan Y Q , Guo C B , Zhong N . Deformation characteristics of Jiaju ancient landslide based on InSAR monitoring method, Sichuan, China. Earth Science, 2022, 47(12): 4681-4697
Zhang C L , Li Z H , Yu C . Landslide detection of the Jinsha river region using GACOS assisted InSAR stacking. Geomatics and Information Science of Wuhan University, 2021, 46(11): 1649-1657
Zhang X B . Modeling and application of the 2D time series deformation monitoring in urban area using high resolution SAR images [Ph. D. thesis](in Chinese). Beijing: China University of Mining & Technology, Beijing, 2018
Zhu J J , Hu J , Li Z W . Recent progress in landslide monitoring with InSAR. Acta Geodaetica et Cartographica Sinica, 2022, 51(10): 2001-2019
继红 . InSAR技术在金沙江流域高位远程滑坡识别与监测中的应用研究[硕士论文]. 西安: 长安大学, 2021
, 长宝 , 志华 . 金沙江断裂带雄巴巨型古滑坡发育特征与形成机理. 现代地质, 2021, 35(1): 47-55
明生 , , 梦华 . 雷达遥感滑坡隐患识别与形变监测. 遥感学报, 2021, 25(1): 332-341
陈伟 , 亚楠 , . 黑方台主要形变区的SBAS-InSAR识别与分析. 测绘科学, 2022, 47(5): 56-65
会燕 , 为乐 , . 光学遥感与InSAR结合的金沙江白格滑坡上下游滑坡隐患早期识别. 武汉大学学报(信息科学版), 2019, 44(9): 1342-1354
, , 玉玲 . 基于DS-InSAR技术的金沙江流域贡觉地区滑坡与地裂缝形变特征. 地球科学与环境学报, 2022, 44(5): 814-825
怡秋 , 长宝 , 永双 . 基于SBAS-InSAR技术的西藏雄巴古滑坡变形特征. 地质学报, 2021, 95(11): 3556-3570
怡秋 , 长宝 , . 基于InSAR形变监测的四川甲居古滑坡变形特征. 地球科学, 2022, 47(12): 4681-4697
红磊 , 军还 , 志忠 . InSAR技术原理及实践. 北京: 科学出版社, 2021
成龙 , 振洪 , . 利用GACOS辅助下InSAR Stacking对金沙江流域进行滑坡监测. 武汉大学学报(信息科学版), 2021, 46(11): 1649-1657
晓博 . 基于高分辨率SAR影像的城市二维时序形变建模与应用[博士论文]. 北京: 中国矿业大学(北京), 2018
建军 , , 志伟 . InSAR滑坡监测研究进展. 测绘学报, 2022, 51(10): 2001-2019

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