1242 citations as recorded by crossref.

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21. The cost of rapid and haphazard urbanization: lessons learned from the Freetown landslide disaster Y. Cui et al. 10.1007/s10346-019-01167-x
22. Mapping Landslide Susceptibility Using Machine Learning Algorithms and GIS: A Case Study in Shexian County, Anhui Province, China Z. Wang et al. 10.3390/sym12121954
23. Aspects of different growth responses of coniferous and broadleaved tree species in landslide research K. Šilhán 10.1016/j.dendro.2025.126368
24. Impact of rock block characteristics on rockfall hazard and its implications for rockfall protection strategies along Himalayan highways: a case study A. Singh et al. 10.1007/s10064-021-02288-1
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28. Performance of logistic regression and support vector machine conjunction with the GIS and RS in the landslide susceptibility assessment: Case study in Nakhon Si Thammarat, southern Thailand K. Prathom & C. Sujitapan 10.1016/j.jksus.2024.103306
29. An optimized non-landslide sampling method for Landslide susceptibility evaluation using machine learning models S. Xu et al. 10.1007/s11069-024-07021-1
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32. Infrared thermography reveals weathering hotspots at the Požáry field laboratory M. Loche et al. 10.1038/s41598-024-65527-x
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35. Landslide Characterization Applying Sentinel-1 Images and InSAR Technique: The Muyubao Landslide in the Three Gorges Reservoir Area, China C. Zhou et al. 10.3390/rs12203385
36. Investigation of the dynamic process of the Xinmo landslide using the discrete element method Z. Liu et al. 10.1016/j.compgeo.2020.103561
37. Evaluation of linear, nonlinear and ensemble machine learning models for landslide susceptibility assessment in southwest China B. Wang et al. 10.1080/10106049.2022.2152493
38. GIS-based landslide susceptibility zonation mapping using the analytic hierarchy process (AHP) method in parts of Kalimpong Region of Darjeeling Himalaya S. Das et al. 10.1007/s10661-022-09851-7
39. Study on Numerical Model and Dynamic Response of Ring Net in Flexible Rockfall Barriers C. Xia et al. 10.3390/su14084406
40. Development and Assessment of GIS-Based Landslide Susceptibility Mapping Models Using ANN, Fuzzy-AHP, and MCDA in Darjeeling Himalayas, West Bengal, India A. Saha et al. 10.3390/land11101711
41. Study on Optimal Pile Length in Load Section of Double-Row Buried Pile under Overtopping Failure Mode X. Li et al. 10.3390/app14010438
42. Triggering mechanics and early warning for snowmelt-rainfall-induced loess landslide K. Wulamu et al. 10.1038/s41598-024-78309-2
43. Characteristics of failure area and failure mechanism of a landslide in Yingjiang County, Yunnan, China G. Shi et al. 10.1007/s10346-020-01544-x
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46. Assessing Landslide Drivers in Social–Ecological–Technological Systems: The Case of Metropolitan Region of São Paulo, Brazil M. Hirye et al. 10.3390/rs15123048
47. Evaluating map quality and model performance through iterative statistics-based landslide susceptibility in eastern KY M. Crawford et al. 10.1007/s11069-025-07255-7
48. Dynahead-YOLO-Otsu: an efficient DCNN-based landslide semantic segmentation method using remote sensing images Z. Han et al. 10.1080/19475705.2024.2398103
49. Simulation of cyclic slow-to-fast landslides based on the coupled creep and frictional slip model C. Xia et al. 10.1016/j.compgeo.2024.106083
50. Exploring performance and robustness of shallow landslide susceptibility modeling at regional scale using different training and testing sets M. Conforti et al. 10.1007/s12665-023-10844-z
51. Landslide susceptibility evaluation based on landslide classification and ANN-NFR modelling in the Three Gorges Reservoir area, China J. Wang et al. 10.1016/j.ecolind.2024.111920
52. Comparison between mechanical and hydrological reinforcement effects of cultivated plants on shallow slope stability M. Bordoni et al. 10.1016/j.scitotenv.2023.168999
53. Quantifying annual occurrence probability of rainfall-induced landslide at a specific slope X. Liu & Y. Wang 10.1016/j.compgeo.2022.104877
54. 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
55. Rainfall-triggered landslides from the January 2023 1-in-200 year storm at Maungakiekie/One Tree Hill, Auckland, New Zealand G. Abazu et al. 10.1080/00288306.2025.2479699
56. Exploring the rainfall data from satellites to monitor rainfall induced landslides – A case study M. Kumar Thakur et al. 10.1016/j.asr.2020.05.015
57. Divergent patterns of landslide activity and triggering factors at a local scale of a single mountain massif (Island Beskid Mts., Western Carpathians, Poland) M. Wistuba et al. 10.1016/j.enggeo.2024.107531
58. A comparative geological, tectonic and geomorphological assessment of the Charlotte, Regent and Madina landslides, Western area, Sierra Leone Y. Lahai et al. 10.1186/s40677-021-00187-x
59. Mechanism of subsidence-buckling and instability of slopes in thick-layered rigid rock under mining J. Deng et al. 10.1007/s11629-023-7952-6
60. Community adaptive capacity in facing landslide disaster P. Wijayanti et al. 10.1088/1755-1315/1314/1/012107
61. Mapping of landslide potential in Pyeongchang-gun, South Korea, using machine learning meta-based optimization algorithms M. Fadhillah et al. 10.1016/j.ejrs.2022.03.008
62. Understanding selective triggering of landslide movement in response to rainfall, Gisborne, New Zealand A. Pola et al. 10.1080/00288306.2025.2517901
63. A comparative study of regional rainfall-induced landslide early warning models based on RF、CNN and MLP algorithms Y. Liu et al. 10.3389/feart.2024.1419421
64. Determination of Rainfall Thresholds for Landslide Prediction Using an Algorithm-Based Approach: Case Study in the Darjeeling Himalayas, India T. Teja et al. 10.3390/geosciences9070302
65. Casual-Nuevo Alausí Landslide (Ecuador, March 2023): A Case Study on the Influence of the Anthropogenic Factors L. Pilatasig et al. 10.3390/geohazards6020028
66. Application of artificial intelligence in three aspects of landslide risk assessment: A comprehensive review R. He et al. 10.1016/j.rockmb.2024.100144
67. Spatial Vulnerability Investigation by Morphotectonic Analysis of the Mandakini River Basin near Kedarnath, Uttarakhand, India using SRTM DEM in a GIS Platform and GPS Data S. Sahu & N. Bhattacharjee 10.17491/jgsi/2024/173913
68. The Spatiotemporal Evolution of Geo-Disaster Resilience in China and the Impact Mechanism of Environmental Governance H. Zhu et al. 10.3390/atmos16030247
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70. Comparing characteristics of rainfall- and earthquake-triggered landslides in the Upper Minjiang catchment, China S. Bai et al. 10.1016/j.enggeo.2020.105518
71. Spatiotemporal distribution patterns of deadly geohazard events in China, 2013–2019 Y. Huang et al. 10.1016/j.nhres.2022.10.003
72. Evaluation of the impact of climate change on rainfall for potential landslide triggering in Japan H. Tsunetaka et al. 10.1002/esp.6050
73. Leveraging local knowledge for landslide disaster risk reduction in an urban informal settlement in Manado, Indonesia E. MacAfee et al. 10.1016/j.ijdrr.2024.104710
74. 4D electrical resistivity to monitor unstable slopes in mountainous tropical regions: an example from Munnar, India A. Watlet et al. 10.1007/s10346-023-02029-3
75. Rapid Deformation Identification and Adaptive Filtering with GNSS TDCP Under Different Scenarios and Its Application in Landslide Monitoring M. Wu et al. 10.3390/rs17101751
76. Multi-hazard susceptibility mapping of landslides and earthquakes in Bhagirathi Valley region of Uttarakhand Himalaya, India N. Gupta et al. 10.1080/14498596.2024.2409083
77. The impact of the aggregation formula on indicator-based method for the assessment of building susceptibility to hydro-meteorological hazards R. Agliata et al. 10.1016/j.ijdrr.2022.102850
78. IoT-based hydrological monitoring of water-induced landslides: a case study in central Norway E. Oguz et al. 10.1007/s10064-022-02721-z
79. Geomorphological landslide inventory map of the Daunia Apennines, southern Italy F. Ardizzone et al. 10.5194/essd-15-753-2023
80. Differences in factors determining landslide hazards among three types of landslides in Japan Y. Shinohara & Y. Watanabe 10.1007/s11069-023-06075-x
81. Failure characteristics and mechanism of a landslide in weathered phyllite at Anqian iron mine, Liaoning, China S. Sun et al. 10.1007/s10064-022-02939-x
82. Deformation dynamics and hazard of slow-moving landslides: The 2023 Joshimath event, Uttarakhand Himalaya P. Dalal et al. 10.1016/j.enggeo.2025.108201
83. Characteristics and causes of natural and human-induced landslides in a tropical mountainous region: the rift flank west of Lake Kivu (Democratic Republic of the Congo) J. Maki Mateso et al. 10.5194/nhess-23-643-2023
84. Preface: Landslide–transport network interactions F. Taylor et al. 10.5194/nhess-20-2585-2020
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86. Historical damaging geo-hydrological events affecting the Catanzaro municipality (Calabria, Southern Italy), 1830–2023 M. Conforti et al. 10.1080/17445647.2025.2498977
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88. Performance and topographic preferences of dynamic and steady models for shallow landslide prediction in a small catchment W. Liang & T. Uchida 10.1007/s10346-021-01771-w
89. Multi-model combination in key steps for landslide susceptibility modeling and uncertainty analysis: a case study in Baoji City, China L. Liu & J. Deng 10.1080/19475705.2024.2344804
90. Slope deformation, reservoir variation and meteorological data at the Khoko landslide, Enguri hydroelectric basin (Georgia), during 2016–2019 A. Tibaldi et al. 10.5194/essd-13-3321-2021
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94. Future changes in precipitation-caused landslide frequency in British Columbia S. Sobie 10.1007/s10584-020-02788-1
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96. When image correlation is needed: Unravelling the complex dynamics of a slow-moving landslide in the tropics with dense radar and optical time series A. Dille et al. 10.1016/j.rse.2021.112402
97. A revised landslide inventory of the Campania region (Italy) F. Fusco et al. 10.1038/s41597-023-02155-6
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100. Acid rain: an unsuspected factor predisposing Panzhihua airport landslide, China K. Li et al. 10.1007/s11356-021-13308-8
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116. Low-Power, Flexible Sensor Arrays with Solderless Board-to-Board Connectors for Monitoring Soil Deformation and Temperature S. Wielandt et al. 10.3390/s22072814
117. Geospatial assessment and integrated multi-model approach for landslide susceptibility mapping in Meghalaya, India N. Badavath & S. Sahoo 10.1016/j.asr.2024.11.052
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122. Multi-event assessment of typhoon-triggered landslide susceptibility in the Philippines J. Jones et al. 10.5194/nhess-23-1095-2023
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134. Synthetic libraries of urban landslide simulations to identify slope failure hotspots and drivers across spatial scales and landscapes E. Bozzolan et al. 10.1007/s10346-024-02327-4
135. Integrated Landslide Hazard Assessment Using Machine Learning, Rainfall Threshold, and RAMMS Based Rockfall Simulation in NH-05, Himachal Pradesh, India M. Singh et al. 10.1007/s12524-025-02173-4
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137. Efficient intensity measures for vulnerability assessment of reinforced concrete buildings under flow-type and slow to moderately moving landslides M. Kulariya & S. Saha 10.1016/j.istruc.2024.107267
138. Landslide Hazard and Rainfall Threshold Assessment: Incorporating Shallow and Deep-Seated Failure Mechanisms with Physics-Based Models R. Marin et al. 10.3390/geosciences14100280
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140. Landslide Hazard and Exposure Modelling in Data‐Poor Regions: The Example of the Rohingya Refugee Camps in Bangladesh R. Emberson et al. 10.1029/2020EF001666
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148. Dynamic response evaluation of landslide to ambient noise using the HVSR method, the case of golay landslide in North Khorasan Province, Iran M. Hosseinzadeh et al. 10.1007/s10064-025-04311-1
149. An Improved Unascertained Measure-Set Pair Analysis Model Based on Fuzzy AHP and Entropy for Landslide Susceptibility Zonation Mapping X. Yang et al. 10.3390/su15076205
150. Using a Tank Model to Determine Hydro-Meteorological Thresholds for Large-Scale Landslides in Taiwan G. Lin et al. 10.3390/w12010253
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152. The Impact of Bamboo on Rainfall-Triggered Landslide Distribution at the Regional Scale: A Case Study from SE China Z. Guo et al. 10.3390/f15122223
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391. Enhanced analysis of landslide susceptibility mapping in the proximity of main roads in the province of Skikda, Algeria: using NAS for efficient performance and faster processing N. Mebirouk et al. 10.1007/s40808-024-02129-6
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906. Rainfall affected stability analysis of Maddingley Brown Coal eastern batter using Plaxis 3D L. Zhao & G. You 10.1007/s12517-020-06038-7
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920. Updating Inventory, Deformation, and Development Characteristics of Landslides in Hunza Valley, NW Karakoram, Pakistan by SBAS-InSAR X. Su et al. 10.3390/rs14194907
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968. Revealing the relation between spatial patterns of rainfall return levels and landslide density S. Mtibaa & H. Tsunetaka 10.5194/esurf-11-461-2023
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978. Effects of Land Cover Changes and Rainfall Variation on the Landslide Size–Frequency Distribution in a Mountainous Region of Western Japan T. Kimura 10.3390/geosciences14030059
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982. An Index for Snowmelt-Induced Landslide Prediction for Zavoj Lake, Serbia R. Marković et al. 10.3390/atmos15030256
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998. Study on the Progress in Climate-Change-Oriented Human Settlement Research Q. Yao et al. 10.3390/su15075733
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1016. Landslide Risk Assessment Using a Combined Approach Based on InSAR and Random Forest W. Liu et al. 10.3390/rs14092131
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1018. Geotechnical assessment of cut slopes in the landslide-prone Himalayas: rock mass characterization and simulation approach T. Siddique et al. 10.1007/s11069-020-04175-6
1019. Assessing probability of failure of urban landslides through rapid characterization of soil properties and vegetation distribution S. Fiolleau et al. 10.1016/j.geomorph.2022.108560
1020. Distribution and temporal-spatial characteristics of geohazards in a rainstorm-prone area of SE China considering the land use Z. Guo et al. 10.1016/j.bgtech.2025.100184
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1123. Sendai voluntary commitments: landslide stakeholders and the all-of-society approach enhanced by UNDRR Y. Matsuoka & E. Gonzales Rocha 10.1007/s10346-020-01519-y
1124. Identification of potential failure zones in large progressive landslides: a method to optimize the cost of landslide early warning S. Kumar et al. 10.1007/s11069-024-06685-z
1125. Detailed inventory and initial analysis of landslides triggered by extreme rainfall in the northern Huaiji County, Guangdong Province, China, from June 6 to 9, 2020 C. Xie et al. 10.1186/s40677-025-00311-1
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1128. A New Integrated Approach for Landslide Data Balancing and Spatial Prediction Based on Generative Adversarial Networks (GAN) H. Al-Najjar et al. 10.3390/rs13194011
1129. Landslide Risk Modeling using Data Mining in Hyrcanian Forests N. Nazariani & A. Fallah 10.61186/jwmr.14.27.123
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1132. Future climate change implications in Bhutan from a downscaled and bias‐adjusted CMIP6 multimodel ensemble F. Lehner et al. 10.1002/joc.8623
1133. Displacement Prediction of the Muyubao Landslide Based on a GPS Time-Series Analysis and Temporal Convolutional Network Model D. Huang et al. 10.3390/rs14112656
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1137. Calibration and Performance Evaluation of Cost-Effective Capacitive Moisture Sensor in Slope Model Experiments M. Hidayat et al. 10.3390/s24248156
1138. Thermo-hydro-poro-mechanical responses of a reservoir-induced landslide tracked by high-resolution fiber optic sensing nerves X. Ye et al. 10.1016/j.jrmge.2023.04.004
1139. Application of novel distributed fibre-optic sensing for slope deformation monitoring: a comprehensive review A. Acharya & T. Kogure 10.1007/s13762-022-04697-5
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1141. Assessment of landslide susceptibility zonation using frequency ratio and statistical index: a case study of Al-Fawar basin, Tartous, Syria H. Abdo 10.1007/s13762-021-03322-1
1142. Exploring disaster ontologies from Chinese and Western perspectives: commonalities and nuances S. Goodall et al. 10.1108/DPM-03-2021-0108
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1144. Landslide risk assessment considering socionatural factors: methodology and application to Cubatão municipality, São Paulo, Brazil P. Hader et al. 10.1007/s11069-021-04991-4
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1153. Comparative Analysis of Machine Learning, Statistical, and MCDA Methods for Rainfall-Induced Landslide Susceptibility Mapping in the Eco-Sensitive Koyna River Basin of India A. Patil et al. 10.1007/s40098-024-00957-y
1154. Spatial joint hazard assessment of landslide susceptibility and intensity within a single framework: Environmental insights from the Wenchuan earthquake Z. Tang et al. 10.1016/j.scitotenv.2025.178545
1155. Research on SSA-LSTM-Based Slope Monitoring and Early Warning Model S. Yang et al. 10.3390/su141610246
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1157. Editorial: Big Earth Data for Disaster Risk Reduction F. Chen et al. 10.3389/feart.2021.727547
1158. Research on Landslide Detection in SAR Images Based on Multi-channel Change Detection Fusion Z. Li et al. 10.1088/1742-6596/2562/1/012003
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1160. 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
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1163. Prioritization of Subwatershed Using Remote Sensing and Geographic Information System in Gandaki Province, Nepal D. Poudel et al. 10.1002/wwp2.12260
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1174. Démarche d'analyse et de diagnostic du risque de glissement de terrain : de l'identification à une mesure proactive A. Gruzelle & S. Lebaut 10.4000/physio-geo.14697
1175. Three decades of landslide activity in western Nepal: new insights into trends and climate drivers A. Muñoz-Torrero Manchado et al. 10.1007/s10346-021-01632-6
1176. Improved rainfall infiltration model for probabilistic slope stability assessment considering transition layers and spatial variability S. Jiang et al. 10.1016/j.enggeo.2025.108096
1177. Improving the forecast performance of landslide susceptibility mapping by using ensemble gradient boosting algorithms H. Ha et al. 10.1007/s10668-024-04694-3
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1179. The Alasu rock avalanche in the Tianshan Mountains, China: fragmentation, landforms, and kinematics Q. Lin et al. 10.1007/s10346-023-02167-8
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1183. Identifying Potential Landslides on Giant Niexia Slope (China) Based on Integrated Multi-Remote Sensing Technologies X. Dong et al. 10.3390/rs14246328
1184. Post‐landslide soil and vegetation recovery in a dry, montane system is slow and patchy B. Buma & Ł. Pawlik 10.1002/ecs2.3346
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1186. SHAP-PDP hybrid interpretation of decision-making mechanism of machine learning-based landslide susceptibility mapping: A case study at Wushan District, China D. Sun et al. 10.1016/j.ejrs.2024.06.005
1187. Impact of precipitation on Beishan landslide deformation from 1986 to 2023 M. Liu et al. 10.3389/feart.2023.1304969
1188. Spatial Prediction of Landslide Susceptibility using Various Machine Learning Based Binary Classification Methods N. Anh et al. 10.17491/jgsi/2024/174002
1189. Displacement residuals reveal landslide regime shifts L. Nava et al. 10.1007/s10346-024-02353-2
1190. Guidelines for Studying Diverse Types of Compound Weather and Climate Events E. Bevacqua et al. 10.1029/2021EF002340
1191. Consideration of spatial heterogeneity in landslide susceptibility mapping using geographical random forest model R. Quevedo et al. 10.1080/10106049.2021.1996637
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