Proceedings of the 2024 5th International Conference on Civil, Architecture and Disaster Prevention and Control (CADPC 2024)

Numerical Modeling and Analysis of Open-pit Mine Landslide Based on Oblique Photogrammetry and GDEM-GAVA

Authors
Xinming Liu1, Jing Wan2, *, Xianghua Shuai3, 4, Jiande Wang2, Hongnan Qin5, Yu Zhou1
1Institute of Mechanics, Chinese Academy of Sciences, Beijing, 100190, China
2Guangdong Academy of Safety Science and Technology, Guangzhou, 510060, China
3Shenzhen Academy of Disaster Prevention and Reduction, Shenzhen, Guangdong, 518003, China
4China Earthquake Networks Center, Beijing, 100045, China
5Cathay Safety Technology Co., Ltd., Beijing, 100012, China
*Corresponding author.
Corresponding Author
Jing Wan
Available Online 13 June 2024.
DOI
10.2991/978-94-6463-435-8_36How to use a DOI?
Keywords
open-pit mine; numerical simulation; oblique photography; point cloud model; landslide
Abstract

Open-pit mine landslides are dynamic disasters characterized by high nonlinearity and uncertainty. This paper presents a simulation of slope instability in an open-pit mine located in Guangdong Province, China, using the GDEM-GAVA method. Through an analysis of the source area, landslide mass, and the entire study area model, this research provides insights into the main development process of landslide disasters in open-pit mining areas, the characteristics of landslide mass movement paths, and the accumulation features in the severely affected areas. The findings reveal that the overall planar shape of the landslide mass in the open-pit mining area is elliptical, with the development process of the entire landslide accumulation area displaying two distinct zones: the upper step accumulation zone and the middle-lower step accumulation zone. The depth of the sliding body ranges from approximately 1 to 10 meters. The affected area spans about 420 meters in length, 100 meters in width, and 190 meters in height, with a maximum accumulation thickness of approximately 10 meters. The impacted area covers an approximate area of 40,000 square meters. These results can serve as a reference for subsequent safety production measures related to open-pit mine landslides caused by natural disasters.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2024 5th International Conference on Civil, Architecture and Disaster Prevention and Control (CADPC 2024)
Series
Atlantis Highlights in Engineering
Publication Date
13 June 2024
ISBN
10.2991/978-94-6463-435-8_36
ISSN
2589-4943
DOI
10.2991/978-94-6463-435-8_36How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Xinming Liu
AU  - Jing Wan
AU  - Xianghua Shuai
AU  - Jiande Wang
AU  - Hongnan Qin
AU  - Yu Zhou
PY  - 2024
DA  - 2024/06/13
TI  - Numerical Modeling and Analysis of Open-pit Mine Landslide Based on Oblique Photogrammetry and GDEM-GAVA
BT  - Proceedings of the 2024 5th International Conference on Civil, Architecture and Disaster Prevention and Control (CADPC 2024)
PB  - Atlantis Press
SP  - 322
EP  - 332
SN  - 2589-4943
UR  - https://doi.org/10.2991/978-94-6463-435-8_36
DO  - 10.2991/978-94-6463-435-8_36
ID  - Liu2024
ER  -