Exploration of slope-type geological hazard susceptibility evaluation based on dynamic correction of SBAS-InSAR technology: A case study of Kang County in Gansu Province

The assessment of geological disaster susceptibility is crucial for early warning, prevention, and mitigation of disasters. Current methods for evaluating geological disasters rely primarily on static factors that cause disasters and historical data at disaster sites or dynamic factors that are introduced into the evaluation model; however, relatively few studies have focused on the use of dynamic data corrections on the basis of susceptibility evaluation. Interferometric synthetic aperture radar (InSAR) technology can effectively capture surface deformation features. Therefore, this study introduces a correction framework based on small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) data to improve the accuracy of geohazard susceptibility assessment results. This correction framework corrects the susceptibility results of the Random Forest (RF) model, which is based on 12 static factors and historical hazard data, using surface deformation data measured by the SBAS-InSAR technique. Compared with the assessments based on static factors via the RF model, the revised results indicated a reduction in the low susceptibility area by 282.30 km2 and increases in the medium, high, and extremely high susceptibility areas by 90.00 km2, 138.98 km2, and 53.34 km2, respectively. The revised evaluation also revealed a lower density of disaster sites in the low- to high-susceptibility zones than before the revision but a higher density in the extremely high-susceptibility zones. This suggests a greater concentration of disaster sites in areas of higher susceptibility, aligning the zoning results more closely with the actual distribution of the sites. Thus, the proposed method has important reference value for improving the accuracy of regional geological disaster susceptibility evaluation. • Introduction of dynamic indicators to modify susceptibility results. • Effective solution to the problem of poor timeliness of static factors and historical disaster point data. • The results of the study provide a feasible reference method for evaluating the susceptibility of similar areas to geological disaster.

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Publication Details

Journal
Ecological Informatics
Published
2024-12-07
DOI
https://doi.org/10.1016/j.ecoinf.2024.102945
Citations
4
Primary Topic
Landslides and related hazards
Type
article
Field-Weighted Citation Impact
2.84
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article

Exploration of slope-type geological hazard susceptibility evaluation based on dynamic correction of SBAS-InSAR technology: A case study of Kang County in Gansu Province

Shucheng Tan, Peng‐Wei Wang, Yuquan Zhou, Yalan Yu et al.
4 citations
Ecological Informatics
Landslides and related hazards
2.84
article

Exploration of slope-type geological hazard susceptibility evaluation based on dynamic correction of SBAS-InSAR technology: A case study of Kang County in Gansu Province

Shucheng Tan, Peng‐Wei Wang, Yuquan Zhou, Yalan Yu, Lifeng Liu, Rongwei Li, Chaodong Gou
article en
4 citations

Abstract

The assessment of geological disaster susceptibility is crucial for early warning, prevention, and mitigation of disasters. Current methods for evaluating geological disasters rely primarily on static factors that cause disasters and historical data at disaster sites or dynamic factors that are introduced into the evaluation model; however, relatively few studies have focused on the use of dynamic data corrections on the basis of susceptibility evaluation. Interferometric synthetic aperture radar (InSAR) technology can effectively capture surface deformation features. Therefore, this study introduces a correction framework based on small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) data to improve the accuracy of geohazard susceptibility assessment results. This correction framework corrects the susceptibility results of the Random Forest (RF) model, which is based on 12 static factors and historical hazard data, using surface deformation data measured by the SBAS-InSAR technique. Compared with the assessments based on static factors via the RF model, the revised results indicated a reduction in the low susceptibility area by 282.30 km2 and increases in the medium, high, and extremely high susceptibility areas by 90.00 km2, 138.98 km2, and 53.34 km2, respectively. The revised evaluation also revealed a lower density of disaster sites in the low- to high-susceptibility zones than before the revision but a higher density in the extremely high-susceptibility zones. This suggests a greater concentration of disaster sites in areas of higher susceptibility, aligning the zoning results more closely with the actual distribution of the sites. Thus, the proposed method has important reference value for improving the accuracy of regional geological disaster susceptibility evaluation. • Introduction of dynamic indicators to modify susceptibility results. • Effective solution to the problem of poor timeliness of static factors and historical disaster point data. • The results of the study provide a feasible reference method for evaluating the susceptibility of similar areas to geological disaster.

Ecological InformaticsVol. 85
Yunnan University (CN)
Climate action
Openalex Percentile: Top 9%
Landslides and related hazards
2.84
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