Landslide susceptibility under two decades of land use change (2000–2020)

To address the insufficient consideration of dynamic driving factors in landslide susceptibility mapping (LSM), this study investigates the contribution of land use and land cover change (LUCC) to the spatial distribution of landslides in Sichuan Province, China, a region highly prone to geological hazards. An XGBoost model was used to integrate multi-source spatial data within a unified 30 m grid to produce a province-wide susceptibility map. SHAP-based attribution analysis was employed to quantitatively assess the relative importance of predisposing factors. The results indicate that dynamic LUCC exerts a stronger explanatory influence on landslide susceptibility than several static geological and environmental factors. High susceptibility is concentrated in low-elevation are as (<1500 m) with annual precipitation exceeding 1100 mm, where cropland expansion and urbanization intensify slope instability. These findings underscore the importance of incorporating dynamic land use information into landslide risk assessment and support more targeted spatial planning and disaster mitigation strategies.

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Publication Details

Journal
Journal of Maps
Published
2026-02-24
DOI
https://doi.org/10.1080/17445647.2026.2633880
Primary Topic
Landslides and related hazards
Type
article
Field-Weighted Citation Impact
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article

Landslide susceptibility under two decades of land use change (2000–2020)

Joseph L. Awange, Danesh Shokri, Ting On Chan, Yeran Sun et al.
Journal of Maps
Landslides and related hazards
article

Landslide susceptibility under two decades of land use change (2000–2020)

Joseph L. Awange, Danesh Shokri, Ting On Chan, Yeran Sun, Christian Larouche, Yuli Wang, Xie, Jing, J., Yibo Ling, Alex Hay-Man Ng
article en

Abstract

To address the insufficient consideration of dynamic driving factors in landslide susceptibility mapping (LSM), this study investigates the contribution of land use and land cover change (LUCC) to the spatial distribution of landslides in Sichuan Province, China, a region highly prone to geological hazards. An XGBoost model was used to integrate multi-source spatial data within a unified 30 m grid to produce a province-wide susceptibility map. SHAP-based attribution analysis was employed to quantitatively assess the relative importance of predisposing factors. The results indicate that dynamic LUCC exerts a stronger explanatory influence on landslide susceptibility than several static geological and environmental factors. High susceptibility is concentrated in low-elevation are as (<1500 m) with annual precipitation exceeding 1100 mm, where cropland expansion and urbanization intensify slope instability. These findings underscore the importance of incorporating dynamic land use information into landslide risk assessment and support more targeted spatial planning and disaster mitigation strategies.

Journal of MapsVol. 22(1)
Guangdong University of Technology (CN), Hong Kong Polytechnic University (HK), Sun Yat-sen University (CN), 3v Geomatics (Canada) (CA), Institute of Remote Sensing and Digital Earth (CN), Aerospace Information Research Institute (CN), Centre de Géomatique du Québec (CA)
Sustainable cities and communities
Openalex Percentile: Top 49%
Landslides and related hazards
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