GNSS Real-Time Warning Technology for Expansive Soil Landslide-A Case in Ningming Demonstration Area

被引:7
作者
Chen, Zi [1 ]
Huang, Guanwen [1 ]
Xie, Wei [1 ]
Zhang, Yongzhi [1 ]
Wang, Le [1 ]
机构
[1] Changan Univ, Sch Geol Engn & Geomatics, Xian 710054, Peoples R China
关键词
expansive soil landslide; GNSS real-time monitoring; multi-source data; early-warning model; successful warning; BEHAVIOR; CLAY;
D O I
10.3390/rs15112772
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Efficient monitoring and early warning are the preconditions of realizing expansive soil landslide hazard prevention and control. Previous early warning of expansive soil landslides was evaluated through soil sampling experiments to analyze the stability coefficient. However, the existing methods lack timeliness and ignore the inconsistent deformation characteristics of different parts of the landslide mass. There are still difficulties in the dynamic numerical early warning of landslides at multiple points. Considering that the degradation of expansive soil landslides' strength is directly reflected by surface displacement, for the Ningming expansive soil demonstration area and based on the GNSS shallow real-time displacement monitoring sequence, a landslide early-warning method based on the GNSS displacement rate combined with the GNSS displacement tangent angle model was proposed, and we thus designed early-warning thresholds for different warning levels. Combined with multi-source data such as soil moisture, soil pressure, and rainfall, the feasibility of accurate early warning of expansive soil landslides based on GNSS real-time surface displacement was verified. The proposed method does not require numerical calculation of internal stress and achieved two successful early warnings of landslides in the test area, which has a certain promotional value.
引用
收藏
页数:25
相关论文
共 36 条
[1]   Anthropogenically induced subsidence in Thessaly, central Greece: new evidence from GNSS data [J].
Argyrakis, Panagiotis ;
Ganas, Athanassios ;
Valkaniotis, Sotirios ;
Tsioumas, Vasilios ;
Sagias, Nikolaos ;
Psiloglou, Basil .
NATURAL HAZARDS, 2020, 102 (01) :179-200
[2]   Analysis of typical expansive soil slope project [J].
Chen, Liang ;
Zhang, Pei ;
Lu, Sheng .
GEOTECHNICAL ENGINEERING FOR DISASTER MITIGATION AND REHABILITATION, 2008, :487-+
[3]  
[陈正汉 Chen Zhenghan], 2014, [岩土工程学报, Chinese Journal of Geotechnical Engineering], V36, P201
[4]   Integration of DInSAR Time Series and GNSS Data for Continuous Volcanic Deformation Monitoring and Eruption Early Warning Applications [J].
Corsa, Brianna ;
Barba-Sevilla, Magali ;
Tiampo, Kristy ;
Meertens, Charles .
REMOTE SENSING, 2022, 14 (03)
[5]   Back-Analysis of Slope GNSS Displacements Using Geographically Weighted Regression and Least Squares Algorithms [J].
Dai, Wujiao ;
Dai, Yue ;
Xie, Jiawei .
REMOTE SENSING, 2023, 15 (03)
[6]   Strength Characteristics and Slope Stability Analysis of Expansive Soil with Filled Fissures [J].
Dai, Zhangjun ;
Guo, Jianhua ;
Luo, Hongming ;
Li, Jian ;
Chen, Shanxiong .
APPLIED SCIENCES-BASEL, 2020, 10 (13)
[7]   Swelling and swelling pressure of a clayey soil: Experimental data, model simulations and effects on slope stability [J].
Ghalamzan, Farzaneh ;
De Rosa, Jacopo ;
Gajo, Alessandro ;
Di Maio, Caterina .
ENGINEERING GEOLOGY, 2022, 297
[8]   A Deep Learning Application for Deformation Prediction from Ground-Based InSAR [J].
Han, Jianfeng ;
Yang, Honglei ;
Liu, Youfeng ;
Lu, Zhaowei ;
Zeng, Kai ;
Jiao, Runcheng .
REMOTE SENSING, 2022, 14 (20)
[9]  
Huang G.W., 2023, ACTA GEOD CARTOGR SI, V4, P5
[10]   Application of InSAR Techniques to an Analysis of the Guanling Landslide [J].
Kang, Ya ;
Zhao, Chaoying ;
Zhang, Qin ;
Lu, Zhong ;
Li, Bin .
REMOTE SENSING, 2017, 9 (10)