Discussion on Refined Identification, Verification, Prevention and Control Models for Geo-hazards Risk

XUE Qiang; DONG Ying; ZHANG Maosheng; LI Lin; GAO Bo; MENG Xiaojie; GUO Xiaopeng

doi:10.12401/j.nwg.2024092

Northwestern Geology > 2025 > 58(2): 66-79. > DOI: 10.12401/j.nwg.2024092

XUE Qiang，DONG Ying，ZHANG Maosheng，et al. Discussion on Refined Identification, Verification, Prevention and Control Models for Geo-hazards Risk[J]. Northwestern Geology，2025，58（2）：66−79. doi: 10.12401/j.nwg.2024092

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Discussion on Refined Identification, Verification, Prevention and Control Models for Geo-hazards Risk

1.
Key Laboratory for Geo-hazards in Loess Area, Observation and Research Station of Geo-hazards in Loess Plateau, MNR, Xi’an Center of China Geological Survey/Northwest China Center for Geoscience Innovation, Xi’an 710119, Shaanxi, China
2.
School of Human Settlements and Civil Engineering, Xi’an Jiaotong University, Xi’an 712000, Shaanxi, China

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Received Date: March 04, 2024
Revised Date: September 22, 2024
Accepted Date: October 08, 2024
Available Online: October 22, 2024

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Abstract

Abstract

Accurate identification of geo-hazards is the key to achieving a shift from post disaster assistance to pre disaster prevention, and precise prevention and control of geo-hazards is the key to achieving a shift from reducing disaster losses to mitigating disaster risks. This paper takes the loess landslide and collapse disasters in Yulin area as an example. A set of geo-hazards fine identification and risk prevention technology method system has been established through surface deformation identification, identification of high and steep landslide-prone slopes, verification of dangerous slope sections, field verification, and implementation of risk prevention and control measures. The results show that: ① A total of 493380 high and steep landslide-prone slopes were identified based on DEM data in Yulin area, and 635 surface deformation sections were identified using InSAR technology. On this basis, A total of 31988 dangerous slope sections (landslide-prone slopes or surface deformation sections with threatening objects) were identified and verified based on optical remote sensing data and elements at risk information. The number of dangerous slope sections accounts for 6.48% of the number of landslide-prone slopes and surface deformation sections. The accuracy of identification has been improved, and "Precise to Slope" of potential geo-hazards identification has been achieved. ② We conducted field verification on dangerous slope sections identified by remote sensing, dangerous and disaster situations reported on-site by the masses, and registered geo-hazards by entering villages and households, and named the potential geo-hazards with "village group + household head name". Risk classification of potential geo-hazards based on slope structure, deformation signs, threat objects, etc. A total of 37523 potential geo-hazards were verified in the field in Yulin area. The risk base of potential geo-hazards has been accurately determined, and "Precise to Household" of potential geo-hazards verification has been achieved. ③ We have developed potential geo-hazards early warning response plans and risk prevention and control measures for different risk levels. The graded prevention and control pattern of potential geo-hazards in cities, counties, towns, and villages has been formed, and "Precise Control" of potential geo-hazards risk has been achieved. The timely and successful application of potential geo-hazards risk identification, verification, and prevention and control models has effectively controlled the geo-hazards risk in Yulin area, and provided a demonstration for potential geo-hazards identification and verification.
- geo-hazards,
- early identification,
- remote sensing interpretation,
- field verification,
- risk prevention and control,
- Yulin area

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References (26)

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