High-level collapse risk identification based on oblique photography and InSAR technology
Collapse risk identification is the basis of collapse disaster prevention. High level collapse is characterized by sudden, hidden and large height difference, which brings great challenges to information collection, disaster identification and risk assessment. In order to solve this engineering prob...
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| Format: | Article |
| Language: | zho |
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Editorial Office of Hydrogeology & Engineering Geology
2023-09-01
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| Series: | Shuiwen dizhi gongcheng dizhi |
| Subjects: | |
| Online Access: | https://www.swdzgcdz.com/en/article/doi/10.16030/j.cnki.issn.1000-3665.202208068 |
| _version_ | 1797659776034799616 |
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| author | Pengwei WANG Yuke AN |
| author_facet | Pengwei WANG Yuke AN |
| author_sort | Pengwei WANG |
| collection | DOAJ |
| description | Collapse risk identification is the basis of collapse disaster prevention. High level collapse is characterized by sudden, hidden and large height difference, which brings great challenges to information collection, disaster identification and risk assessment. In order to solve this engineering problem, this paper takes the Jiulongxia high slope in the Bailong River basin as an example, Based on the 3D model of oblique photography, the establishment of high-level collapse identification index and its structural plane information extraction method, proposes a collapse risk assessment model combining stereographic projection qualitative analysis and InSAR quantitative analysis, and forms a whole process model of high level collapse identification and risk assessment combining collapse identification, stability analysis and deformation monitoring. The results show that there are 22 collapse dangerous rocks in the study area (including 7 high risk rocks, accounting for 32%, 11 medium risk rocks, accounting for 50%, and 4 low risk rocks, accounting for 18%), with a distribution height of 37 m – 640 m. High risk dangerous rocks are mainly concentrated in the prominent mountain mouth in the south, the eastern slope and the western slope toe. These analysis results are consistent with the historical data of highway disaster maintenance, which verifies the feasibility of tilt photography and InSAR technology in high level collapse risk identification. The results provide a basis and reference for the application of this technology in collapse disaster prevention. |
| first_indexed | 2024-03-11T18:20:03Z |
| format | Article |
| id | doaj.art-5916821fdf0540629f222d285c65c801 |
| institution | Directory Open Access Journal |
| issn | 1000-3665 |
| language | zho |
| last_indexed | 2024-03-11T18:20:03Z |
| publishDate | 2023-09-01 |
| publisher | Editorial Office of Hydrogeology & Engineering Geology |
| record_format | Article |
| series | Shuiwen dizhi gongcheng dizhi |
| spelling | doaj.art-5916821fdf0540629f222d285c65c8012023-10-16T01:16:38ZzhoEditorial Office of Hydrogeology & Engineering GeologyShuiwen dizhi gongcheng dizhi1000-36652023-09-0150516918010.16030/j.cnki.issn.1000-3665.202208068202208068High-level collapse risk identification based on oblique photography and InSAR technologyPengwei WANG0Yuke AN1Gansu Province Transportation Planning, Survey & Design Institute Co.Ltd., Lanzhou, Gansu 730030, ChinaGansu Province Transportation Planning, Survey & Design Institute Co.Ltd., Lanzhou, Gansu 730030, ChinaCollapse risk identification is the basis of collapse disaster prevention. High level collapse is characterized by sudden, hidden and large height difference, which brings great challenges to information collection, disaster identification and risk assessment. In order to solve this engineering problem, this paper takes the Jiulongxia high slope in the Bailong River basin as an example, Based on the 3D model of oblique photography, the establishment of high-level collapse identification index and its structural plane information extraction method, proposes a collapse risk assessment model combining stereographic projection qualitative analysis and InSAR quantitative analysis, and forms a whole process model of high level collapse identification and risk assessment combining collapse identification, stability analysis and deformation monitoring. The results show that there are 22 collapse dangerous rocks in the study area (including 7 high risk rocks, accounting for 32%, 11 medium risk rocks, accounting for 50%, and 4 low risk rocks, accounting for 18%), with a distribution height of 37 m – 640 m. High risk dangerous rocks are mainly concentrated in the prominent mountain mouth in the south, the eastern slope and the western slope toe. These analysis results are consistent with the historical data of highway disaster maintenance, which verifies the feasibility of tilt photography and InSAR technology in high level collapse risk identification. The results provide a basis and reference for the application of this technology in collapse disaster prevention.https://www.swdzgcdz.com/en/article/doi/10.16030/j.cnki.issn.1000-3665.202208068high level slopecollapsetilt photographyinsarrisk identification |
| spellingShingle | Pengwei WANG Yuke AN High-level collapse risk identification based on oblique photography and InSAR technology Shuiwen dizhi gongcheng dizhi high level slope collapse tilt photography insar risk identification |
| title | High-level collapse risk identification based on oblique photography and InSAR technology |
| title_full | High-level collapse risk identification based on oblique photography and InSAR technology |
| title_fullStr | High-level collapse risk identification based on oblique photography and InSAR technology |
| title_full_unstemmed | High-level collapse risk identification based on oblique photography and InSAR technology |
| title_short | High-level collapse risk identification based on oblique photography and InSAR technology |
| title_sort | high level collapse risk identification based on oblique photography and insar technology |
| topic | high level slope collapse tilt photography insar risk identification |
| url | https://www.swdzgcdz.com/en/article/doi/10.16030/j.cnki.issn.1000-3665.202208068 |
| work_keys_str_mv | AT pengweiwang highlevelcollapseriskidentificationbasedonobliquephotographyandinsartechnology AT yukean highlevelcollapseriskidentificationbasedonobliquephotographyandinsartechnology |