Landslide susceptibility assessment and zonation using negative sampling strategy: A case study of Bazhong area, Sichuan Province

GONG Xueqiang; XI Chuanjie; HU Xiewen; HU Yayun; ZHOU Yonghao; ZHANG Yu

doi:10.16031/j.cnki.issn.1003-8035.202309028

2025 Vol. 36, No. 1

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GONG Xueqiang, XI Chuanjie, HU Xiewen, HU Yayun, ZHOU Yonghao, ZHANG Yu. Landslide susceptibility assessment and zonation using negative sampling strategy: A case study of Bazhong area, Sichuan Province[J]. The Chinese Journal of Geological Hazard and Control, 2025, 36(1): 146-155. doi: 10.16031/j.cnki.issn.1003-8035.202309028

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GONG Xueqiang, XI Chuanjie, HU Xiewen, HU Yayun, ZHOU Yonghao, ZHANG Yu. Landslide susceptibility assessment and zonation using negative sampling strategy: A case study of Bazhong area, Sichuan Province[J]. The Chinese Journal of Geological Hazard and Control, 2025, 36(1): 146-155. doi: 10.16031/j.cnki.issn.1003-8035.202309028

Landslide susceptibility assessment and zonation using negative sampling strategy: A case study of Bazhong area, Sichuan Province

1.
Faculty of Geosciences and Environment Engineering, Southwest Jiaotong University, Chengdu, Sichuan　610031, China
2.
State-Province Joint Engineering Laboratory of Spatial Information Technology for High-Speed Railway Safety, Chengdu, Sichuan　610031, China
3.
Zhejiang Engineering Survey and Design Institute Group Co. Ltd, Ningbo, Zhejiang　315012, China

More Information

Corresponding author: HU Xiewen, huxiewen@163.com

Received Date: 21 September 2023

Revised Date: 07 November 2023

Accepted Date: 06 January 2025

Publish Date: 25 February 2025

Abstract

Abstract

Landslide susceptibility assessment is a crucial component of landslide risk management, effectively guiding disaster prevention and mitigation efforts. However, the accuracy of landslide susceptibility assessments is constrained by various factors, and current research on optimizing negative sample sampling strategies based on slope units remains relatively limited. This study, focuses on Bazhong City as the research area, incorporates eleven conditioning factors including elevation, relief, and annual average rainfall to develop a geographically weighted regression - random forest (GWR-RF) coupling model. This model optimize the negative sampling strategy by comparing it against traditional random sampling across the entire area. The results indicate the following: (1) Random sampling from the entire area leads to significant disparities in susceptibility assessments, accompanied by a relatively diminished accuracy, rendering it unsuitable for slope unit-based assessments. (2) The coupled GWR-RF model demonstrates spatial variations in landslide susceptibility, predominantly distributing in the Enyang, Bazhou, Pingchang Counties, and the central - southern region of Nanjiang County. The proposed GWR-RF coupled model improves the accuracy of landslide susceptibility assessments by optimizing the negative sample sampling strategy, providing a scientific basis for landslide disaster prevention and mitigation in the Bazhong region.
- susceptibility assessment /
- geographically weighted regression /
- random forest /
- landslide

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References

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