43 citations as recorded by crossref.

1. Vulnerability patterns of road network to extreme floods based on accessibility measures T. Papilloud & M. Keiler https://doi.org/10.1016/j.trd.2021.103045
2. Preface: Landslide–transport network interactions F. Taylor et al. https://doi.org/10.5194/nhess-20-2585-2020
3. Vulnerability analysis in complex networks under a flood risk reduction point of view L. Santos et al. https://doi.org/10.3389/fphy.2023.1064122
4. Identifying Local Hotspots of Compounded Physical and Social Impacts from Hurricane Helene-Induced Flood and Landslides A. Shrestha & C. Fan https://doi.org/10.1016/j.ijdrr.2026.106268
5. A novel landslide susceptibility optimization framework to assess landslide occurrence probability at the regional scale for environmental management X. Sun et al. https://doi.org/10.1016/j.jenvman.2022.116108
6. Spatial agents for geological surface modelling E. de Kemp https://doi.org/10.5194/gmd-14-6661-2021
7. Quantitative Risk Assessment of Road Networks Subject to Natural Hazards: A State-of-the-Art Review A. Roy et al. https://doi.org/10.1061/JSDCCC.SCENG-1812
8. Landslide Risks to Bridges in Valleys in North Carolina S. Lin et al. https://doi.org/10.3390/geohazards5010015
9. Coupling RBF neural network with ensemble learning techniques for landslide susceptibility mapping B. Pham et al. https://doi.org/10.1016/j.catena.2020.104805
10. Landslide susceptibility mapping using hybrid random forest with GeoDetector and RFE for factor optimization X. Zhou et al. https://doi.org/10.1016/j.gsf.2021.101211
11. Data use and data needs in critical infrastructure risk analysis A. Larsson & C. Große https://doi.org/10.1080/13669877.2023.2181858
12. Brief communication: Visualizing uncertainties in landslide susceptibility modelling using bivariate mapping M. Schlögl et al. https://doi.org/10.5194/nhess-25-1425-2025
13. Recent advances in vulnerability assessment for the built environment exposed to torrential hazards: Challenges and the way forward S. Fuchs et al. https://doi.org/10.1016/j.jhydrol.2019.05.067
14. Towards a holistic assessment of landslide susceptibility models: insights from the Central Eastern Alps M. Schlögl et al. https://doi.org/10.1007/s12665-024-12041-y
15. National and regional-scale landslide indicators and indexes: Applications in Italy M. Donnini et al. https://doi.org/10.1515/geo-2022-0375
16. Landslides along the Lago Maggiore western coast (northern Italy): intense rainfall as trigger or concomitant cause? M. Ciampittiello et al. https://doi.org/10.1007/s11069-021-04626-8
17. Total probabilistic measure for the potential risk of regional roads exposed to landslides Q. Liu et al. https://doi.org/10.1016/j.ress.2022.108822
18. Modelling landslides in the Lesser Himalaya region using geospatial and numerical simulation techniques M. Islam & S. Chattoraj https://doi.org/10.1007/s12517-023-11541-8
19. Physical vulnerability to dynamic flooding: Vulnerability curves and vulnerability indices M. Papathoma-Köhle et al. https://doi.org/10.1016/j.jhydrol.2022.127501
20. Developing a probability-based technique to improve the measurement of landslide vulnerability on regional roads Q. Liu et al. https://doi.org/10.1016/j.ress.2023.109918
21. Short communication: A model to predict flood loss in mountain areas S. Fuchs et al. https://doi.org/10.1016/j.envsoft.2019.03.026
22. Identification and evaluation of flood-avoidance routes in Tucson, Arizona A. Coles https://doi.org/10.1016/j.ijdrr.2020.101597
23. Natural hazard impacts on transport infrastructure in Russia E. Petrova https://doi.org/10.5194/nhess-20-1969-2020
24. Enhanced landslide susceptibility zonation using GIS-Based ensemble techniques A. Sharma et al. https://doi.org/10.1007/s12665-024-12032-z
25. Estimation of traffic flow changes using networks in networks approaches J. Hackl & B. Adey https://doi.org/10.1007/s41109-019-0139-y
26. Enhancing Seismic Landslide Susceptibility Analysis for Sustainable Disaster Risk Management through Machine Learning H. He et al. https://doi.org/10.3390/su16093828
27. The (f)utility to account for pre-failure topography in data-driven landslide susceptibility modelling S. Steger et al. https://doi.org/10.1016/j.geomorph.2020.107041
28. Resilience of road networks to natural hazards: A systematic literature review Y. Zeleke et al. https://doi.org/10.1016/j.treng.2026.100420
29. Multi-hazard risk assessment of rail infrastructure in India under local vulnerabilities towards adaptive pathways for disaster resilient infrastructure planning D. Joshi et al. https://doi.org/10.1016/j.pdisas.2023.100308
30. Landslide risk assessment of Guangdong expressway network using random forest and complex network topological analysis Y. Niu et al. https://doi.org/10.1016/j.ige.2026.06.002
31. Analysis of historical data for a better understanding of post‐construction landslides at an artificial waterway A. Wohlers & B. Damm https://doi.org/10.1002/esp.5028
32. Incorporating spatial heterogeneity into landslide susceptibility assessment: a GWRF–SHAP new method R. Gu et al. https://doi.org/10.1080/17538947.2026.2639808
33. Landslide Susceptibility Mapping in a Mountainous Area Using Machine Learning Algorithms H. Shahabi et al. https://doi.org/10.3390/rs15123112
34. Application of a Novel Hybrid Machine Learning Algorithm in Shallow Landslide Susceptibility Mapping in a Mountainous Area B. Ghasemian et al. https://doi.org/10.3389/fenvs.2022.897254
35. Sample size effects on landslide susceptibility models: A comparative study of heuristic, statistical, machine learning, deep learning and ensemble learning models with SHAP analysis S. Yang et al. https://doi.org/10.1016/j.cageo.2024.105723
36. Rockfall Vulnerability of a Rural Road Network—A Methodological Approach in the Harz Mountains, Germany A. Wohlers & B. Damm https://doi.org/10.3390/geosciences12040170
37. Multi-hazard risk assessment for roads: probabilistic versus deterministic approaches S. Oberndorfer et al. https://doi.org/10.5194/nhess-20-3135-2020
38. Quantifying climate risks to infrastructure systems: A comparative review of developments across infrastructure sectors J. Verschuur et al. https://doi.org/10.1371/journal.pclm.0000331
39. Decoupling urban and non-urban landslides for susceptibility mapping in transitional landscapes: a case study from Southwestern Constantine, Algeria Z. Matougui et al. https://doi.org/10.5194/nhess-25-4629-2025
40. Development of multiclass alternating decision trees based models for landslide susceptibility mapping B. Pham et al. https://doi.org/10.1016/j.pce.2022.103235
41. Rainfall-induced transportation embankment failure: A review X. Linrong et al. https://doi.org/10.1515/geo-2022-0558
42. A machine learning approach in spatial predicting of landslides and flash flood susceptible zones for a road network H. Ha et al. https://doi.org/10.1007/s40808-022-01384-9
43. Mountains of hope: contributing to the sustainable development goals through integrated landslide disaster risk management I. Alcántara-Ayala https://doi.org/10.1007/s11629-025-9536-0