71 citations as recorded by crossref.

1. Linkages and reactions of geomorphic processes in Kerala Flood, 2018 S. Chothodi et al. 10.1007/s11069-024-06469-5
2. Developing landslide hazard scenario using the historical events for the Kashmir Himalaya B. Shah et al. 10.1007/s11069-022-05542-1
3. Assessment of exposed elements in a changing built environment by using an integrated model of debris flow initiation and runout (Kalimpong region, Himalaya) S. Bera et al. 10.1007/s10064-021-02352-w
4. Challenges of modeling rainfall triggered landslides in a data-sparse region: A case study from the Western Ghats, India C. Vishnu et al. 10.1016/j.geogeo.2022.100060
5. A national landslide inventory for Denmark G. Luetzenburg et al. 10.5194/essd-14-3157-2022
6. Investigating the effects of landslides inventory completeness on susceptibility mapping and frequency-area distributions: Case of Taounate province, Northern Morocco R. Sahrane et al. 10.1016/j.catena.2022.106737
7. Predicting debris flow pathways using volume-based thresholds for effective risk assessment A. Rajaneesh et al. 10.1038/s44304-024-00055-2
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9. Improvement of Region-Merging Image Segmentation Accuracy Using Multiple Merging Criteria H. Wang et al. 10.3390/rs13142782
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11. Vulnerability evaluation utilizing AHP and an ensemble model in a few landslide-prone areas of the Western Ghats, India S. Anchima et al. 10.1007/s10668-023-04149-1
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13. Effects of Digital Elevation Models on Spatial Characterisation of Landslides in the Kalka-Shimla Region of the Indian Himalayas A. Sharma & H. Sandhu 10.1007/s12524-024-01938-7
14. Space–Time Landslide Susceptibility Modeling Based on Data-Driven Methods Z. Fang et al. 10.1007/s11004-023-10105-6
15. A Pilot Assessment of the Fatal Landslide on 29 August 2022 in Kudayathoor, Idukki, Kerala K. Amal George et al. 10.1007/s12594-023-2277-1
16. Migrating rivers, consequent paleochannels: The unlikely partners and hotspots of flooding K. Sajinkumar et al. 10.1016/j.scitotenv.2021.150842
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18. RER2023: the landslide inventory dataset of the May 2023 Emilia-Romagna meteorological event M. Berti et al. 10.5194/essd-17-1055-2025
19. Flood vulnerability of a few areas in the foothills of the Western Ghats: a comparison of AHP and F-AHP models C. Senan et al. 10.1007/s00477-022-02267-2
20. An Ensemble Modeling of Frequency Ratio (FR) with Evidence Belief Function (EBF) for GIS-Based Landslide Susceptibility Mapping: A Case Study of the Coastal Cliff of Safi, Morocco R. Habiballah et al. 10.1007/s12524-023-01765-2
21. Application of data‐driven techniques for landslide susceptibility prediction along an earthquake‐affected road section in Kashmir Himalaya S. Gardezi et al. 10.1002/gj.4630
22. A rapid run-out assessment methodology for the 2024 Wayanad debris flow V. Krishnapriya et al. 10.1038/s44304-024-00044-5
23. Unsupervised machine learning with different sampling strategies and topographic factors for distinguishing between landslide source and runout areas to improve landslide inventory production J. Lai et al. 10.1080/19475705.2024.2406302
24. Japanese literature organization and spatiotemporal database system creation for natural disaster analysis B. Lyu et al. 10.1186/s40494-024-01132-5
25. Mass movement susceptibility assessment of alpine infrastructure in the Salzkammergut area, Austria L. Abad et al. 10.1016/j.ijdrr.2022.103009
26. Novel ensemble of deep learning neural network and support vector machine for landslide susceptibility mapping in Tehri region, Garhwal Himalaya S. Saha et al. 10.1080/10106049.2022.2120638
27. Spatio-temporal landslide forecasting using process-based and data-driven approaches: A case study from Western Ghats, India M. Abraham et al. 10.1016/j.catena.2023.106948
28. Assessment of a Dynamic Physically Based Slope Stability Model to Evaluate Timing and Distribution of Rainfall-Induced Shallow Landslides J. Thomas et al. 10.3390/ijgi12030105
29. Spatial distribution characteristics of climate-induced landslides in the Eastern Himalayas D. Uwizeyimana et al. 10.1007/s11629-024-8869-4
30. A Non-Stationary Framework for Landslide Hazard Assessment Under the Extreme Rainfall Condition S. Dilama Shamsudeen et al. 10.1007/s41748-024-00445-6
31. Can citizen scientists provide a reliable geo-hydrological hazard inventory? An analysis of biases, sensitivity and precision for the Rwenzori Mountains, Uganda J. Sekajugo et al. 10.1088/1748-9326/ac5bb5
32. Landslide susceptibility modelling in Nyahode and Buzi sub-catchments of Zimbabwe F. Muchaka et al. 10.2166/wpt.2022.069
33. Mass movement susceptibility prediction and infrastructural risk assessment (IRA) using GIS-based Meta classification algorithms S. Ali et al. 10.1016/j.asoc.2023.110591
34. Predicting the geographical distribution of Impatiens parasitica (Balsaminaceae), an epiphytic species endemic to the Southern Western Ghats, India R. Ashok et al. 10.54207/bsmps1000-2023-V2134U
35. Social sensing of flood impacts in India: A case study of Kerala 2018 J. Young et al. 10.1016/j.ijdrr.2022.102908
36. Exploration of Landslide Geomorphology and Inventory Construction in Minhe County, Qinghai, China, Based on Google Earth Remote Sensing Imagery Q. Wang et al. 10.1111/tgis.13281
37. Terrain visibility impact on the preparation of landslide inventories: a practical example in Darjeeling district (India) T. Bornaetxea et al. 10.5194/nhess-22-2929-2022
38. Integrating FR, MFR and IV Models for Landslide Susceptibility Zonation Mapping in Joshimath Watershed, Uttarakhand, India I. Khan et al. 10.1007/s40996-024-01708-y
39. Creation of a Landslide Inventory for the 2018 Storm Event of Kodagu in the Western Ghats for Landslide Susceptibility Mapping Using Machine Learning G. Arpitha et al. 10.1007/s12524-024-01953-8
40. Factors Affecting Landslide Susceptibility Mapping: Assessing the Influence of Different Machine Learning Approaches, Sampling Strategies and Data Splitting M. Abraham et al. 10.3390/land10090989
41. Landslide susceptibility modeling based on GIS and ensemble techniques H. Yan & W. Chen 10.1007/s12517-022-09974-8
42. Selection of contributing factors for predicting landslide susceptibility using machine learning and deep learning models C. Chen & L. Fan 10.1007/s00477-023-02556-4
43. LSL-SS-Net: level set loss-guided semantic segmentation networks for landslide extraction Y. Yang et al. 10.1080/15481603.2024.2416727
44. Proposing an easy-to-use tool for estimating landslide dimensions using a data-driven approach M. Abraham et al. 10.1080/27669645.2022.2127549
45. Performance evaluation of machine learning and statistical techniques for modelling landslide susceptibility with limited field data A. Achu et al. 10.1007/s12145-022-00910-8
46. A ground instabilities inventory between Tetouan and Jebha (Morocco): mapping, description and analysis H. Tribak et al. 10.1007/s10064-023-03161-z
47. Estimation of Shallow Landslide Susceptibility Incorporating the Impacts of Vegetation on Slope Stability H. Jiang et al. 10.1007/s13753-023-00507-9
48. Effect of spatial resolution and data splitting on landslide susceptibility mapping using different machine learning algorithms M. Abraham et al. 10.1080/19475705.2021.2011791
49. Evaluation of pore-pressure variation and slope stability on terraced cultivation using physics-based landslide susceptibility model A. Ajith et al. 10.1016/j.geomorph.2024.109081
50. The impact of irrigated agriculture on landslide activity: A spatio-temporal analysis in Heifangtai, China L. Hao et al. 10.1016/j.catena.2025.108844
51. Extreme precipitation induced concurrent events trigger prolonged disruptions in regional road networks R. Dave et al. 10.1088/1748-9326/ac2d67
52. Analyzing the posterior predictive capability and usability of landslide susceptibility maps: a case of Kerala, India T. Pareek et al. 10.1007/s10346-024-02389-4
53. Landslide Susceptibility Assessment Using Recurrent Neural Network (RNN)—A Case of Chabahar and Konarak in Iran V. Isazade et al. 10.1007/s40098-025-01220-8
54. Optimization of SVR and CatBoost models using metaheuristic algorithms to assess landslide susceptibility R. Ajin et al. 10.1038/s41598-024-72663-x
55. Landslide inventory and susceptibility models considering the landslide typology using deep learning: Himalayas, India S. Bera et al. 10.1007/s11069-021-04731-8
56. The tale of three landslides in the Western Ghats, India: lessons to be learnt R. Ajin et al. 10.1186/s40677-022-00218-1
57. Analysis of landslide explicative factors and susceptibility mapping in an andean context: The case of Azuay province (Ecuador) S. Cobos-Mora et al. 10.1016/j.heliyon.2023.e20170
58. Assessing the Improvement of a Sparse Rain Gauge Network in a Landslide Hotspot in Kerala, India—A Multi-Criteria Approach C. Vishnu et al. 10.21663/EEG-D-23-00029
59. Machine learning as a tool to classify extra-terrestrial landslides: A dossier from Valles Marineris, Mars A. Rajaneesh et al. 10.1016/j.icarus.2022.114886
60. Event-based rainfall-induced landslide inventories and rainfall thresholds for Malawi P. Niyokwiringirwa et al. 10.1007/s10346-023-02203-7
61. Debris flow in the Nenmara, Kerala, India: insights from geophysical testing, subsurface investigation and numerical analysis R. Kesavaram & S. Chandrasekaran 10.1007/s10064-025-04093-6
62. TRIGRS-FOSM: probabilistic slope stability tool for rainfall-induced landslide susceptibility assessment A. Ajith & R. Pillai 10.1007/s11069-024-06933-2
63. Landslide Susceptibility Assessment of a Part of the Western Ghats (India) Employing the AHP and F-AHP Models and Comparison with Existing Susceptibility Maps S. Bhagya et al. 10.3390/land12020468
64. Addressing the Effect of Intra-Seasonal Variations in Developing Rainfall Thresholds for Landslides: An Antecedent Rainfall-Based Approach C. Vishnu et al. 10.3390/geohazards5030033
65. Insights from Optimized Non-Landslide Sampling and SHAP Explainability for Landslide Susceptibility Prediction M. Li & H. Tian 10.3390/app15031163
66. Landslide hazard mapping of Wayanad District of Kerala, India, incorporating copula-based estimation of joint probability of rainfall S. Dilama Shamsudeen & A. Sankaran 10.5194/piahs-387-79-2024
67. A GIS tool for infinite slope stability analysis (GIS-TISSA) R. Escobar-Wolf et al. 10.1016/j.gsf.2020.09.008
68. Landslide susceptibility investigation for Idukki district of Kerala using regression analysis and machine learning S. Jones et al. 10.1007/s12517-021-07156-6
69. Unraveling the drivers of intensified landslide regimes in Western Ghats, India A. Yunus et al. 10.1016/j.scitotenv.2021.145357
70. Uncertainties in landslide susceptibility prediction modeling: A review on the incompleteness of landslide inventory and its influence rules F. Huang et al. 10.1016/j.gsf.2024.101886
71. Effect of scale and mapping unit on landslide susceptibility mapping of Mandakini River Basin, Uttarakhand, India S. Gupta & D. Shukla 10.1007/s12665-022-10487-6