Deformation Analysis of Guobu Slope based on SBAS-InSAR


  • Conghua Li
  • Long Li
  • Chonghui Zhang



SBAS-InSAR, Laxiwa hydropower station, Guobu slope, Displacement monitoring, Deformation analysis.


The Laxiwa hydropower station reservoir in the upper reaches of the Yellow River basin is located in a canyon zone. Due to its complex terrain and difficult transportation, traditional monitoring methods are difficult to implement in this area, especially during the critical deformation stage when personnel may face danger or encounter difficulty reaching the site. To achieve long-term continuous dynamic monitoring of the upstream active slope of the Laxiwa hydropower station, namely the Guobu slope, SBAS-InSAR technology has been adopted as a replacement for traditional measurement methods to monitor landslide movements. Based on the deformation information of the monitoring targets, safety analysis, and disaster warnings are conducted to ensure the safe operation of the power station and the safety of downstream communities and residents' lives and property.


Download data is not yet available.
<br data-mce-bogus="1"> <br data-mce-bogus="1">


Alessandro Cesare Mondini, Fausto Guzzetti, Kang-Tsung Chang, et al. Landslide failures detection and mapping using Synthetic Aperture Radar: Past, present and future[J/OL]. Earth-Science Reviews, 2021, 216: 103574. DOI:10.1016/j.earscirev.2021.103574.

Tingchen Wu, Xiao Xie, Haoyu Wu, et al. A Quantitative Analysis Method of Regional Rainfall-Induced Landslide Deformation Response Variation Based on a Time-Domain Correlation Model[J/OL]. Land, 2022, 11(5): 703. DOI:10.3390/land11050703.

Xiaojie Liu. Research on key technologies for early identification, monitoring and forecasting of wide-area landslides with spaceborne radar remote sensing[D/OL]. Universidad de Alicante, 2022[2023-03-14].

Jianming Kuang, Linlin Ge, Alex Hay-Man Ng, et al. Detection and Deformation Characterization of the 2020 Aniangzhai Landslide Using Time-Series Insar and Optical Datasets[C/OL]//2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS. Brussels, Belgium: IEEE, 2021: 6595-6598[2022-12-08]. DOI:10.1109/IGARSS47720.2021.9554326.

Yan Yan, Yong Wang. Determining Suitable Spaceborne SAR Observations and Ground Control Points for Surface Deformation Study in Rugged Terrain With InSAR Technique[J/OL]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021, 14: 11324-11334. DOI:10.1109/JSTARS.2021.3123326.

Bingli Hu, Lijun Su, Bo Zhao, et al. New Insight into the Sliding Mechanism and Post-Stability of the 2017 Xinmo Landslide in Sichuan, China[J/OL]. Bulletin of Engineering Geology and the Environment, 2022, 81(10): 430. DOI:10.1007/s10064-022-02917-3.

Bayer B, Simoni A, Schmidt D, et al. Using advanced InSAR techniques to monitor landslide deformations induced by tunneling in the Northern Apennines, Italy[J/OL]. Engineering Geology, 2017, 226: 20-32. DOI:10.1016/j.enggeo.2017.03.026.

Houjun Jiang, Guangcai Feng, Teng Wang, et al. Toward full exploitation of coherent and incoherent information in Sentinel-1 TOPS data for retrieving surface displacement: Application to the 2016 Kumamoto (Japan) earthquake: FULL EXPLOITATION OF SENTINEL-1 TOPS DATA[J/OL]. Geophysical Research Letters, 2017[2023-02-20]. DOI:10.1002/2016GL072253.

Guzalay Sataer, Mohamed Sultan, Mustafa Kemal Emil, et al. Remote Sensing Application for Landslide Detection, Monitoring along Eastern Lake Michigan (Miami Park, MI)[J/OL]. Remote Sensing, 2022, 14(14): 3474. DOI:10.3390/rs14143474.

Xiaojun Su, Yi Zhang, Xingmin Meng, et al. Updating Inventory, Deformation, and Development Characteristics of Landslides in Hunza Valley, NW Karakoram, Pakistan by SBAS-InSAR[J/OL]. Remote Sensing, 2022, 14(19): 4907. DOI:10.3390/rs14194907.

Lingjing Li, Xin Yao, Baoping Wen, et al. The long-term failure processes of a large reactivated landslide in the Xiluodu reservoir area based on InSAR technology[J/OL]. Frontiers in Earth Science, 2023, 10: 1055890. DOI:10.3389/feart.2022.1055890.

P. Berardino, G. Fornaro, R. Lanari, et al. A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms[J/OL]. IEEE Transactions on Geoscience and Remote Sensing, 2002, 40(11): 2375-2383. DOI:10.1109/TGRS.2002.803792.

Jiaming Yao, Xin Yao, Xinghong Liu. Landslide Detection and Mapping Based on SBAS-InSAR and PS-InSAR: A Case Study in Gongjue County, Tibet, China[J/OL]. Remote Sensing, 2022, 14(19): 4728. DOI:10.3390/rs14194728.

Ming Chang, Wenjing Sun, Hengzhi Xu, et al. Identification and deformation analysis of potential landslides after the Jiuzhaigou earthquake by SBAS-InSAR[J/OL]. Environmental Science and Pollution Research, 2023[2023-02-18]. DOI:10.1007/s11356-022-25055-5.

Zhang P, Guo Z, Guo S, et al. Land Subsidence Monitoring Method in Regions of Variable Radar Reflection Characteristics by Integrating PS-InSAR and SBAS-InSAR Techniques[J]. Remote Sensing, 2022, 14(14): 3265.




How to Cite

Li, C., Li, L., & Zhang, C. (2023). Deformation Analysis of Guobu Slope based on SBAS-InSAR. Academic Journal of Science and Technology, 5(3), 126–131.