33 citations as recorded by crossref.

1. Utilizing Remote Sensing and Random Forests to Identify Optimal Land Use Scenarios and Address the Increase in Landslide Susceptibility A. Putra et al.
2. A quantitative framework to assess the debris flow hazard at a catchment scale under climate change Z. Guo et al.
3. VIGIRISKS platform, a web-tool for single and multi-hazard risk assessment C. Negulescu et al.
4. Landslide Susceptibility Mapping Using Machine Learning: A Danish Case Study A. Ageenko et al.
5. Predicting landslide susceptibility based on decision tree machine learning models under climate and land use changes Q. Pham et al.
6. Measurement and inversion strategies for 3‐D resistivity surveys with vector arrays M. Loke et al.
7. Prolonged influence of urbanization on landslide susceptibility T. Rohan et al.
8. Dynamics of population exposure to landslides under climate change scenarios P. Ghosh et al.
9. Influence of Carbonate-Flysch Contact and Groundwater Dynamics on the Occurrence of Geohazards in Istria, Croatia S. Dugonjić Jovančević et al.
10. Landslide susceptibility in Xiji county: a coupled modeling approach with dynamic factors Q. Ling et al.
11. Implications of future land-use/cover pattern change on landslide susceptibility at a national level: A scenario-based analysis in Romania M. Jurchescu et al.
12. SCoMHA: a framework to analyse process-level sediment connectivity in multi-hazard events M. Ishmam et al.
13. Assessing the impact of climate change on landslide recurrence intervals in Nakhon Si Thammarat Province, Thailand, using CMIP6 climate models T. Chaithong
14. A probabilistic model for natural gas pipeline failure under climate-induced Natech hazards: Toward AI-based safety management G. Qin et al.
15. Current understanding and uncertainties associated with climate change and the impact on slope stability: A systematic literature review F. Tetteh et al.
16. Energy and structural evolution process of high-altitude and long-runout landslides induced by a strong earthquake Y. Ge et al.
17. Climate change increases the number of landslides at the juncture of the Alpine, Pannonian and Mediterranean regions M. Jemec Auflič et al.
18. How will the projected climate change influence rainfall-induced landslides in Europe? A review of modelling approaches S. Gariano & G. Rianna
19. Artificial Intelligence: A new era for spatial modelling and interpreting climate-induced hazard assessment A. Dikshit et al.
20. Physically based model for assessing rainfall-induced deep-seated landslides using a hydrological-geotechnical model S. Phakdimek et al.
21. Displacement prediction of slow-moving landslides using InSAR and ensemble regression models based on slope units S. Cobos-Mora et al.
22. Impacts of future climate and land cover changes on landslide susceptibility: regional scale modelling in the Val d’Aran region (Pyrenees, Spain) M. Hürlimann et al.
23. Exploring performance and robustness of shallow landslide susceptibility modeling at regional scale using different training and testing sets M. Conforti et al.
24. Improving the spatial prediction of machine learning-based landslide susceptibility models by integrating the particle swarm optimization algorithm R. Ajin et al.
25. The Role of Citrus Groves in Rainfall-Triggered Landslide Hazards in Uwajima, Japan N. Lusiana & Y. Shinohara
26. Determining the impact of anthropogenic activities and climate change on landslide susceptibility for the Himalayan region A. Tyagi et al.
27. Land Use/ Land Cover Changes and Climate Change as Conditioning Factors for Landslide: A Review R. Verma et al.
28. A novel hybrid model integrating high resolution remote sensing and stacking ensemble techniques for landslide susceptibility mapping: Application to event-based landslide inventory Z. Guo et al.
29. Prediction of the future landslide susceptibility scenario based on LULC and climate projections A. Tyagi et al.
30. Shallow landslide susceptibility assessment under future climate and land cover changes: A case study from southwest China Z. Guo et al.
31. Spatial understanding of historical and future landslide variation in Africa L. Nahayo et al.
32. Integrating dynamic factors for predicting future landslide susceptibility S. Lamichhane et al.
33. Spatiotemporal changes of landslide susceptibility in response to rainfall and its future prediction — A case study of Sichuan Province, China H. Zheng & M. Ding