1024 citations as recorded by crossref.

1. Distinctive controls on the distribution of river-damming and non-damming landslides induced by the 2008 Wenchuan earthquake R. Tang et al. 10.1007/s10064-018-1381-8
2. Fiber bundle model applied to slope stability assessment: co-detection multi-threshold analysis for early warning J. Faillettaz 10.3389/fphy.2023.1244503
3. Hydrometeorological disasters in urban areas of Costa Rica, Central America A. Quesada-Román et al. 10.1080/17477891.2020.1791034
4. Invited perspectives: Landslide populations – can they be predicted? F. Guzzetti 10.5194/nhess-21-1467-2021
5. Centrifuge and numerical modeling of h-type anti-slide pile reinforced soil-rock mixture slope H. Zhang et al. 10.1007/s11629-022-7446-y
6. Deadly Myanmar mine disaster caused by poor planning, say data sleuths A. Silver 10.1038/d41586-021-01740-2
7. The influence of the physical environment on self-recovery after disasters in Nepal and the Philippines S. Sargeant et al. 10.1016/j.ijdrr.2020.101673
8. A Deep-Learning-Based Algorithm for Landslide Detection over Wide Areas Using InSAR Images Considering Topographic Features N. Li et al. 10.3390/s24144583
9. Rainfall Induced Landslide Studies in Indian Himalayan Region: A Critical Review A. Dikshit et al. 10.3390/app10072466
10. The role of non-government stakeholders in implementing the Sendai Framework: A view from the voluntary commitments online platform Y. Matsuoka & E. Gonzales Rocha 10.1016/j.pdisas.2021.100142
11. Scenarios of Human Responses to Unprecedented Social‐Environmental Extreme Events M. Rusca et al. 10.1029/2020EF001911
12. Pre- and post-failure spatiotemporal evolution of loess landslides: a case study of the Jiangou landslide in Ledu, China Y. Zhu et al. 10.1007/s10346-021-01714-5
13. Mapping Landslides on EO Data: Performance of Deep Learning Models vs. Traditional Machine Learning Models N. Prakash et al. 10.3390/rs12030346
14. Spatial and Temporal Analysis of Global Landslide Reporting Using a Decade of the Global Landslide Catalog C. Dandridge et al. 10.3390/su15043323
15. Sonlu Elemanlar Yöntemi ile Depreme Bağlı Heyelan Tehlike Modelleme F. SUNBUL & A. SUNBUL 10.20854/bujse.829417
16. Experimental Study on the Relationship between the Velocity of Surface Movements and Tilting Rate in Pre-Failure Stage of Rainfall-Induced Landslides J. Xie et al. 10.3390/s21185988
17. Shared Blocks-Based Ensemble Deep Learning for Shallow Landslide Susceptibility Mapping T. Kavzoglu et al. 10.3390/rs13234776
18. The cost of rapid and haphazard urbanization: lessons learned from the Freetown landslide disaster Y. Cui et al. 10.1007/s10346-019-01167-x
19. 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
20. 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
21. Estimating Rainfall Thresholds for Landslide Occurrence in the Bhutan Himalayas A. Dikshit et al. 10.3390/w11081616
22. 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
23. Evaluación de la cinemática del deslizamiento de Cuenca en los Andes de Perú central mediante técnicas fotogramétricas y geodésicas W. Quiroz et al. 10.4995/raet.2024.21785
24. 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
25. Towards a web service for rapid landslide mapping based on Copernicus data F. Albrecht et al. 10.1088/1755-1315/509/1/012002
26. GIS-based for prediction and prevention of environmental geological disaster susceptibility: From a perspective of sustainable development X. Wang et al. 10.1016/j.ecoenv.2021.112881
27. Infrared thermography reveals weathering hotspots at the Požáry field laboratory M. Loche et al. 10.1038/s41598-024-65527-x
28. Framework for rainfall-triggered landslide-prone critical infrastructure zonation K. Gnyawali et al. 10.1016/j.scitotenv.2023.162242
29. Utilization of google maps for depicting landslide pattern in Indonesia S. Sukristiyanti et al. 10.1088/1755-1315/500/1/012042
30. 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
31. Investigation of the dynamic process of the Xinmo landslide using the discrete element method Z. Liu et al. 10.1016/j.compgeo.2020.103561
32. 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
33. 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
34. Study on Numerical Model and Dynamic Response of Ring Net in Flexible Rockfall Barriers C. Xia et al. 10.3390/su14084406
35. 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
36. Study on Optimal Pile Length in Load Section of Double-Row Buried Pile under Overtopping Failure Mode X. Li et al. 10.3390/app14010438
37. 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
38. Landslide detection in the Himalayas using machine learning algorithms and U-Net S. Meena et al. 10.1007/s10346-022-01861-3
39. Assessing Landslide Drivers in Social–Ecological–Technological Systems: The Case of Metropolitan Region of São Paulo, Brazil M. Hirye et al. 10.3390/rs15123048
40. Dynahead-YOLO-Otsu: an efficient DCNN-based landslide semantic segmentation method using remote sensing images Z. Han et al. 10.1080/19475705.2024.2398103
41. 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
42. 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
43. 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
44. Comparison between mechanical and hydrological reinforcement effects of cultivated plants on shallow slope stability M. Bordoni et al. 10.1016/j.scitotenv.2023.168999
45. Quantifying annual occurrence probability of rainfall-induced landslide at a specific slope X. Liu & Y. Wang 10.1016/j.compgeo.2022.104877
46. 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
47. 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
48. 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
49. 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
50. 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
51. Community adaptive capacity in facing landslide disaster P. Wijayanti et al. 10.1088/1755-1315/1314/1/012107
52. 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
53. 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
54. 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
55. Application of artificial intelligence in three aspects of landslide risk assessment: A comprehensive review R. He et al. 10.1016/j.rockmb.2024.100144
56. 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
57. Ensemble modeling of landslide susceptibility using random subspace learner and different decision tree classifiers B. Pham et al. 10.1080/10106049.2020.1737972
58. Comparing characteristics of rainfall- and earthquake-triggered landslides in the Upper Minjiang catchment, China S. Bai et al. 10.1016/j.enggeo.2020.105518
59. Spatiotemporal distribution patterns of deadly geohazard events in China, 2013–2019 Y. Huang et al. 10.1016/j.nhres.2022.10.003
60. 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
61. 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
62. 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
63. 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
64. IoT-based hydrological monitoring of water-induced landslides: a case study in central Norway E. Oguz et al. 10.1007/s10064-022-02721-z
65. Geomorphological landslide inventory map of the Daunia Apennines, southern Italy F. Ardizzone et al. 10.5194/essd-15-753-2023
66. Differences in factors determining landslide hazards among three types of landslides in Japan Y. Shinohara & Y. Watanabe 10.1007/s11069-023-06075-x
67. 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
68. 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
69. Preface: Landslide–transport network interactions F. Taylor et al. 10.5194/nhess-20-2585-2020
70. HR-GLDD: a globally distributed dataset using generalized deep learning (DL) for rapid landslide mapping on high-resolution (HR) satellite imagery S. Meena et al. 10.5194/essd-15-3283-2023
71. Old but still active: > 18 ka history of rock slope failures affecting a flysch anticline M. Břežný et al. 10.1007/s10346-020-01483-7
72. 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
73. 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
74. 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
75. Thermal Infrared Imagery Integrated with Terrestrial Laser Scanning and Particle Tracking Velocimetry for Characterization of Landslide Model Failure J. Ma et al. 10.3390/s20010219
76. Land surface temperature (LST) and soil moisture index (SMI) to identify slope stability S. Putro et al. 10.1088/1755-1315/986/1/012022
77. Future changes in precipitation-caused landslide frequency in British Columbia S. Sobie 10.1007/s10584-020-02788-1
78. 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
79. A revised landslide inventory of the Campania region (Italy) F. Fusco et al. 10.1038/s41597-023-02155-6
80. Quick and automatic detection of co-seismic landslides with multi-feature deep learning model W. Huangfu et al. 10.1007/s11430-023-1306-8
81. Acid rain: an unsuspected factor predisposing Panzhihua airport landslide, China K. Li et al. 10.1007/s11356-021-13308-8
82. Constraining landslide timing in a data-scarce context: from recent to very old processes in the tropical environment of the North Tanganyika-Kivu Rift region O. Dewitte et al. 10.1007/s10346-020-01452-0
83. A Meta-Learning Approach of Optimisation for Spatial Prediction of Landslides B. Pradhan et al. 10.3390/rs13224521
84. Building a landslide hazard indicator with machine learning and land surface models T. Stanley et al. 10.1016/j.envsoft.2020.104692
85. Physically-based catchment-scale prediction of slope failure volume and geometry B. Van den Bout et al. 10.1016/j.enggeo.2020.105942
86. Freeze-thaw induced landslides on grasslands in cold regions J. Yang et al. 10.1016/j.catena.2022.106650
87. Machine learning and landslide studies: recent advances and applications F. Tehrani et al. 10.1007/s11069-022-05423-7
88. Spatiotemporal Prediction of Landslide Displacement Using Graph Convolutional Network-Based Models: A Case Study of the Tangjiao 1# Landslide in Chongqing, China Y. Sun et al. 10.3390/app14209288
89. Landslides across the USA: occurrence, susceptibility, and data limitations B. Mirus et al. 10.1007/s10346-020-01424-4
90. Deformation characteristics of a large landslide reactivated by human activity in Wanyuan city, Sichuan Province, China B. Zhao et al. 10.1007/s10346-022-01853-3
91. Low-Power, Flexible Sensor Arrays with Solderless Board-to-Board Connectors for Monitoring Soil Deformation and Temperature S. Wielandt et al. 10.3390/s22072814
92. A prototype landslide early warning system in Rize (Turkey): analyzing recent impacts to design a safer future S. Segoni et al. 10.1007/s10346-022-01988-3
93. Time-Lapse Electrical Resistivity Tomography (TL-ERT) for Landslide Monitoring: Recent Advances and Future Directions V. Lapenna & A. Perrone 10.3390/app12031425
94. Multi-event assessment of typhoon-triggered landslide susceptibility in the Philippines J. Jones et al. 10.5194/nhess-23-1095-2023
95. Landslide detection from bitemporal satellite imagery using attention-based deep neural networks S. Amankwah et al. 10.1007/s10346-022-01915-6
96. A national landslide inventory for Denmark G. Luetzenburg et al. 10.5194/essd-14-3157-2022
97. Farmers’ adoption intentions of water-saving agriculture under the risks of frequent irrigation-induced landslides J. Wang et al. 10.1016/j.crm.2023.100484
98. Rainfall triggers more deep-seated landslides than Cascadia earthquakes in the Oregon Coast Range, USA S. LaHusen et al. 10.1126/sciadv.aba6790
99. ERT-based experimental integrated approach for soil hydrological characterization in rainfall-induced shallow landslides prone areas V. Vivaldi et al. 10.1007/s10064-024-03627-8
100. Timely prediction potential of landslide early warning systems with multispectral remote sensing: a conceptual approach tested in the Sattelkar, Austria D. Hermle et al. 10.5194/nhess-21-2753-2021
101. A multi-scale approach for deterministic analysis of landslide triggering and mass flow mechanism at Kaliasaur (Rudraprayag) A. Sajwan et al. 10.1007/s10346-023-02151-2
102. 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
103. Determination of the Probabilities of Landslide Events—A Case Study of Bhutan R. Sarkar & K. Dorji 10.3390/hydrology6020052
104. 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
105. Landslide Hazard and Rainfall Threshold Assessment: Incorporating Shallow and Deep-Seated Failure Mechanisms with Physics-Based Models R. Marin et al. 10.3390/geosciences14100280
106. The Role of Soil Type in Triggering Shallow Landslides in the Alps (Lombardy, Northern Italy) F. Luino et al. 10.3390/land11081125
107. 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
108. Reviews and Syntheses: Promoting the Advancement of Hillslope Hydrology and Stability in Taiwan from the Perspective of Critical Zone Science Y. Yang et al. 10.3390/w15061234
109. Active landslide detection using integrated remote sensing technologies for a wide region and multiple stages: A case study in southwestern China H. Lu et al. 10.1016/j.scitotenv.2024.172709
110. The influence of the selection of non-geological disasters sample spatial range on the evaluation of environmental geological disasters susceptibility: a case study of Liulin County J. Chen et al. 10.1007/s11356-023-25454-2
111. A pseudo-3D methodology for regional-scale back-analysis of earthquake-induced landslides W. Gong et al. 10.1016/j.enggeo.2023.107277
112. 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
113. Using a Tank Model to Determine Hydro-Meteorological Thresholds for Large-Scale Landslides in Taiwan G. Lin et al. 10.3390/w12010253
114. GIS-Based Landslide Susceptibility Mapping for Land Use Planning and Risk Assessment A. Roccati et al. 10.3390/land10020162
115. A python system for regional landslide susceptibility assessment by integrating machine learning models and its application Z. Guo et al. 10.1016/j.heliyon.2023.e21542
116. Insights to pre- and post-event stability analysis of rainfall-cum-anthropogenically induced recent Laxmanpuri landslide, Uttarakhand, India B. Peethambaran et al. 10.1007/s12665-021-10143-5
117. Study on the Evolution Process of Bearing Characteristics of Cantilever Anti-Slide Pile Exposed to Sodium Sulfate Solution Attack H. Jin et al. 10.1007/s40996-023-01134-6
118. Natural hazards fatalities in Brazil, 1979–2019 G. de Azevedo Couto et al. 10.1007/s11069-023-06059-x
119. Synergetic use of geospatial and machine learning techniques in modelling landslide susceptibility in parts of Shimla to Kinnaur National Highway, Himachal Pradesh R. Das et al. 10.1007/s40808-024-01993-6
120. A new method to detect changes in displacement rates of slow-moving landslides using InSAR time series A. Urgilez Vinueza et al. 10.1007/s10346-022-01913-8
121. Three-dimensional rockfall shape back analysis: methods and implications D. Bonneau et al. 10.5194/nhess-19-2745-2019
122. Indicator-based approach for the assessment of intrinsic physical vulnerability of the built environment to hydro-meteorological hazards: Review of indicators and example of parameters selection for a sample area R. Agliata et al. 10.1016/j.ijdrr.2021.102199
123. Influence of buffer distance on environmental geological hazard susceptibility assessment Z. Wang et al. 10.1007/s11356-023-31739-3
124. Spatiotemporal prediction of landslide displacement using deep learning approaches based on monitored time-series displacement data: a case in the Huanglianshu landslide N. Xi et al. 10.1080/17499518.2023.2172186
125. Revealing the Effect of Typhoons on the Stability of Residual Soil Slope by Wind Tunnel Test Z. Guo et al. 10.3390/f15050791
126. Topographic uncertainty quantification for flow-like landslide models via stochastic simulations H. Zhao & J. Kowalski 10.5194/nhess-20-1441-2020
127. Spatio-temporal cluster analysis of recent Italian landslides M. Tonini et al. 10.1080/17499518.2020.1861634
128. Landslide susceptibility mapping and risk assessment using total estimated susceptibility values along NH44 in Jammu and Kashmir, Western Himalaya R. Mir et al. 10.1007/s11069-023-06363-6
129. The Influence of Gravel Particle Diameter and Slope Angle on a Rockfall–Cushion Layer Collision S. Duan et al. 10.1007/s10706-022-02207-5
130. Near-surface soil hydrothermal response feedbacks landslide activity and mechanism X. Ye et al. 10.1016/j.enggeo.2024.107690
131. Spatial understanding of historical and future landslide variation in Africa L. Nahayo et al. 10.1007/s11069-023-06126-3
132. Landslides after wildfire: initiation, magnitude, and mobility F. Rengers et al. 10.1007/s10346-020-01506-3
133. Historical dynamics of landslide risk from population and forest-cover changes in the Kivu Rift A. Depicker et al. 10.1038/s41893-021-00757-9
134. Probabilistic Hydrological Estimation of LandSlides (PHELS): global ensemble landslide hazard modelling A. Felsberg et al. 10.5194/nhess-23-3805-2023
135. Study on characteristics and impact of Kalikhola landslide, Manipur, NE India, using UAV photogrammetry R. Pattanaik & Y. Singh 10.1007/s11069-024-06484-6
136. GIS-based landslide susceptibility modeling: A comparison between fuzzy multi-criteria and machine learning algorithms S. Ali et al. 10.1016/j.gsf.2020.09.004
137. Effects of retained dry material on the impact, overflow and landing dynamics J. Fang et al. 10.1016/j.jrmge.2023.11.024
138. Deep learning approaches for landslide information recognition: Current scenario and opportunities N. Chandra & H. Vaidya 10.1007/s12040-024-02281-8
139. A Pattern‐Based Strategy for InSAR Phase Unwrapping and Application to Two Landslides in Colorado Y. Molan & R. Lohman 10.1029/2022JB025761
140. Causes and triggers of deep-seated hillslope instability in the tropics – Insights from a 60-year record of Ikoma landslide (DR Congo) A. Dille et al. 10.1016/j.geomorph.2019.106835
141. Deep learning for geological hazards analysis: Data, models, applications, and opportunities Z. Ma & G. Mei 10.1016/j.earscirev.2021.103858
142. Potential sliding zone recognition method for the slow-moving landslide based on the Hurst exponent H. Yang et al. 10.1016/j.jrmge.2023.08.007
143. INSPIRE standards as a framework for artificial intelligence applications: a landslide example G. Roberti et al. 10.5194/nhess-20-3455-2020
144. A hybrid machine learning model for landslide-oriented risk assessment of long-distance pipelines H. Wen et al. 10.1016/j.jenvman.2023.118177
145. An explainable AI (XAI) model for landslide susceptibility modeling B. Pradhan et al. 10.1016/j.asoc.2023.110324
146. Hazard assessment for regional typhoon-triggered landslides by using physically-based model – a case study from southeastern China Z. Guo et al. 10.1080/17499518.2023.2188465
147. Soil Moisture Sensor-Based Landslide Monitoring: A Laboratory-Based Approach for Guwahati City M. Sharma & S. Laskar 10.37394/232033.2024.2.3
148. Identification and Analysis of Landslides in the Ahai Reservoir Area of the Jinsha River Basin Using a Combination of DS-InSAR, Optical Images, and Field Surveys Y. Li et al. 10.3390/rs14246274
149. Performance evaluation for four GIS-based models purposed to predict and map landslide susceptibility: A case study at a World Heritage site in Southwest China Y. Jiao et al. 10.1016/j.catena.2019.104221
150. Mechanism of Co‐Seismic Deformation of the Slow‐Moving La Sorbella Landslide in Italy Revealed by MPM Analysis M. Kohler & A. Puzrin 10.1029/2022JF006618
151. Geologic controls of slow-moving landslides near the US West Coast Y. Xu et al. 10.1007/s10346-021-01732-3
152. Unsupervised active–transfer learning for automated landslide mapping Z. Wang & A. Brenning 10.1016/j.cageo.2023.105457
153. Topographic Analysis of Landslide Distribution Using AW3D30 Data A. Nonomura et al. 10.3390/geosciences10040115
154. A massive rock and ice avalanche caused the 2021 disaster at Chamoli, Indian Himalaya D. Shugar et al. 10.1126/science.abh4455
155. Slope Unit Maker (SUMak): an efficient and parameter-free algorithm for delineating slope units to improve landslide modeling J. Woodard et al. 10.5194/nhess-24-1-2024
156. Stability analysis of open-pit gold mine slopes and optimization of mining scheme in Inner Mongolia, China S. Ren et al. 10.1007/s11629-020-6217-x
157. Multi-coal seam mining-induced collapse and deformation evolution of high steep slopes of the Shaomi collapse, Guizhou, China B. Shen et al. 10.1007/s10346-024-02381-y
158. Automatic identification of active landslides over wide areas from time-series InSAR measurements using Faster RCNN J. Cai et al. 10.1016/j.jag.2023.103516
159. Granular flow simulation in a centrifugal acceleration field M. Cabrera et al. 10.1680/jgeot.18.P.260
160. Experimental study on the stability of vegetated earthen slopes under intense rainfall X. Song & Y. Tan 10.1016/j.still.2024.106028
161. A local rainfall-triggered giant landslide occurred in a region along a high-speed railway on the Qinghai–Tibetan Plateau Q. Li et al. 10.1007/s11629-023-8408-8
162. Calibration of the microparameters of the discrete element method using a relevance vector machine and its application to rockfill materials C. Ma et al. 10.1016/j.advengsoft.2020.102833
163. Definition of 3D rainfall thresholds to increase operative landslide early warning system performances A. Rosi et al. 10.1007/s10346-020-01523-2
164. Rainfall Infiltration through Stratified Colluvial Deposits: Analytical Approach vs. Numerical Modelling P. Paronuzzi et al. 10.3390/geosciences14020053
165. An ensemble random forest tree with SVM, ANN, NBT, and LMT for landslide susceptibility mapping in the Rangit River watershed, India S. Ali et al. 10.1007/s11069-022-05360-5
166. Analysis of Changes in Landslide Susceptibility according to Land Use over 38 Years in Lixian County, China J. Liu et al. 10.3390/su131910858
167. Artificial Intelligence: A new era for spatial modelling and interpreting climate-induced hazard assessment A. Dikshit et al. 10.1016/j.gsf.2024.101815
168. Study on the stability of brown coal batter with opened cracks on Maddingley brown coal mine L. Zhao & G. You 10.1007/s42452-020-2897-7
169. The 2020 Hpakant Jade Mine Disaster, Myanmar: A multi-sensor investigation for slope failure Y. Lin et al. 10.1016/j.isprsjprs.2021.05.015
170. Impact of topography on in situ soil wetness measurements for regional landslide early warning – a case study from the Swiss Alpine Foreland A. Wicki et al. 10.5194/nhess-23-1059-2023
171. Geomorphological hazards susceptibility in high-density urban areas: A case study of Mexico City D. García-Soriano et al. 10.1016/j.jsames.2020.102667
172. Impact Analysis of a Building Collapse Caused by a Rainfall-Induced Landslide in Kerala, India V. Santhosh Kumar & S. Chandrasekaran 10.3390/buildings12091395
173. Synergistic effect of rainfall and pipe leakage erosion on the formation and development of loess caves in Weinan city, Loess Plateau, Northwest China G. Zhou et al. 10.1007/s12665-023-11130-8
174. Landslide Susceptibility Prediction Considering Regional Soil Erosion Based on Machine-Learning Models F. Huang et al. 10.3390/ijgi9060377
175. Risk Assessment of Geological Hazards in the Alpine Gorge Region and Its Influencing Factors: A Case Study of Jiulong County, China X. Zhang et al. 10.3390/su16051949
176. Disparity between evacuation intention and actual evacuation behavior during a heavy rain induced disaster event in Japan: Exploring the role of everyday awareness of disaster preparedness T. Hatori et al. 10.1016/j.ijdrr.2023.103729
177. Assessing landslide susceptibility based on hybrid Best-first decision tree with ensemble learning model H. Hong 10.1016/j.ecolind.2023.109968
178. Spatial dendrogeomorphic sampling based on the specific tree growth responses induced by the landslide mechanism K. Šilhán 10.1016/j.quageo.2020.101132
179. Developmental characteristics of rainfall-induced landslides from 1999 to 2016 in Wenzhou City of China H. Qin et al. 10.3389/feart.2022.1005199
180. Slit structures: Fundamental mechanisms of mechanical trapping of granular flows S. Goodwin & C. Choi 10.1016/j.compgeo.2019.103376
181. 30-year record of Himalaya mass-wasting reveals landscape perturbations by extreme events J. Jones et al. 10.1038/s41467-021-26964-8
182. A Comparison of Research Trends on Soil Reinforcement by Tree Roots Using Bibliometric Analysis K. Kim & S. Kim 10.14397/jals.2024.58.3.63
183. Stability analysis of complex terrain slope based on multi-source point cloud fusion W. Zan et al. 10.1007/s11629-022-7307-8
184. “Understanding livelihood insecurity due to landslides in the mid-hill of Nepal: A case study of Bahrabise Municipality” M. Shrestha et al. 10.1016/j.ijdrr.2024.104399
185. Deformation and Failure Mechanism of a Massive Ancient Anti-Dip River-Damming Landslide in the Upper Jinsha River Y. Li et al. 10.3390/su142013048
186. Insights gained into geo-hydrological disaster management 25 years after the catastrophic landslides of 1998 in southern Italy G. Esposito et al. 10.1016/j.ijdrr.2022.103440
187. Shedding effects of sediment composition and bed morphology on debris flow dynamics and entrainment mechanism: Insights from laboratory experiments P. Li et al. 10.1016/j.enggeo.2024.107495
188. Precipitation Characteristics and Future Changes Over the Southern Slope of Tibetan Plateau Simulated by a High‐Resolution Global Nonhydrostatic Model Y. Na et al. 10.1029/2020JD033630
189. Landslide inventory and susceptibility models considering the landslide typology using deep learning: Himalayas, India S. Bera et al. 10.1007/s11069-021-04731-8
190. Prediction of spatial landslide susceptibility applying the novel ensembles of CNN, GLM and random forest in the Indian Himalayan region S. Saha et al. 10.1007/s00477-022-02212-3
191. Landslide susceptibility and mobilization rates in the Mount Elgon region, Uganda J. Broeckx et al. 10.1007/s10346-018-1085-y
192. 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
193. Design of Miniaturized Sensing Unit for Underground Displacement 3-D Measurement Sensor N. Shentu et al. 10.1109/JSEN.2024.3452091
194. Preliminary investigation of emerging suburban landsliding in Gisborne, New Zealand M. Cook et al. 10.1144/qjegh2021-087
195. An interpretable model for landslide susceptibility assessment based on Optuna hyperparameter optimization and Random Forest X. Xiao et al. 10.1080/19475705.2024.2347421
196. Mobilization rates of landslides in a changing tropical environment: 60-year record over a large region of the East African Rift A. Depicker et al. 10.1016/j.geomorph.2024.109156
197. The influence of cartographic representation on landslide susceptibility models: empirical evidence from a Brazilian UNESCO world heritage site J. Araujo Junior et al. 10.1007/s11069-024-06576-3
198. Introduce a framework for landslide risk assessment using geospatial analysis: a case study from Kegalle District, Sri Lanka E. Perera et al. 10.1007/s40808-020-00811-z
199. Identify Landslide Precursors from Time Series InSAR Results M. Liu et al. 10.1007/s13753-023-00532-8
200. An hourly shallow landslide warning model developed by combining automatic landslide spatial susceptibility and temporal rainfall threshold predictions Y. Cao et al. 10.1007/s11629-022-7370-1
201. A Regional-Scale Landslide Early Warning System Based on the Sequential Evaluation Method: Development and Performance Analysis J. Park et al. 10.3390/app10175788
202. Estimating landslide sliding distance based on an improved Heim sled model Z. Zhang et al. 10.1016/j.catena.2021.105401
203. A landslide dating framework using a combination of Sentinel-1 SAR and -2 optical imagery S. Fu et al. 10.1016/j.enggeo.2023.107388
204. Spatiotemporal distribution characteristics, causes, and prevention advice of fatal geohazards in Jiangxi Province, China C. Shao et al. 10.1016/j.scitotenv.2022.155337
205. A data-driven evaluation of post-fire landslide susceptibility E. Culler et al. 10.5194/nhess-23-1631-2023
206. A Joint Seismic and Space‐Based Investigation of the 2016 Lamplugh Glacier and 2017 Wrangell Mountains (Alaska) Landslides X. Luo et al. 10.1029/2022JF006903
207. A catastrophic high-speed train crash caused by a small-scale debris flow in China S. Zhang et al. 10.1016/j.trgeo.2023.101070
208. Türkiye Cumhuriyeti’nin 100. Yılında Türkiye Adresli Yayınların Dünya Heyelan Literatürüne Katkısı C. Gökçeoğlu 10.24232/jmd.1443848
209. Two Nitsche-based mixed finite element discretizations for the seepage problem in Richards’ equation F. Gatti et al. 10.1016/j.cma.2024.117368
210. Numerical modeling of seepage and deformation of unsaturated slope subjected to post-earthquake rainfall J. Xu et al. 10.1016/j.compgeo.2022.104791
211. Refined Zoning of Landslide Susceptibility: A Case Study in Enshi County, Hubei, China Z. Wang et al. 10.3390/ijerph19159412
212. Forecasting the magnitude of potential landslides based on InSAR techniques Y. Zhang et al. 10.1016/j.rse.2020.111738
213. Correlation between Acoustic Emission Behaviour and Dynamics Model during Three-Stage Deformation Process of Soil Landslide L. Deng et al. 10.3390/s21072373
214. Integration of Spatial Probability and Size in Slope-Unit-Based Landslide Susceptibility Assessment: A Case Study L. Li & H. Lan 10.3390/ijerph17218055
215. Application of quantitative methods for the assessment of landslide susceptibility of the Aghsuchay river basin S. Tarikhazer et al. 10.26565/2410-7360-2023-58-20
216. Assessing the impact of climate change on landslides near Vejle, Denmark, using public data K. Svennevig et al. 10.5194/nhess-24-1897-2024
217. Spatiotemporal variations of fatal landslides in Turkey T. Görüm & S. Fidan 10.1007/s10346-020-01580-7
218. Integrated analysis of geophysical approaches for slope failure characterisation M. Zakaria et al. 10.1007/s12665-022-10410-z
219. The human cost of global warming: Deadly landslides and their triggers (1995–2014) U. Haque et al. 10.1016/j.scitotenv.2019.03.415
220. Effect of Uncertainty in Geotechnical and Flow Parameters on Landslide-induced Force for Building Response Analysis Under Flow-type Landslides Using Uncoupled Approach M. Kulariya et al. 10.1007/s40098-024-01074-6
221. A Physical and Numerical Investigation of Flow–Barrier Interaction for the Design of a Multiple-Barrier System C. Ng et al. 10.1061/(ASCE)GT.1943-5606.0002932
222. Flash flood and landslide susceptibility analysis for a mountainous roadway in Vietnam using spatial modeling C. Luu et al. 10.1016/j.qsa.2023.100083
223. Exploitation of optical and SAR amplitude imagery for landslide identification: a case study from Sikkim, Northeast India T. Sivasankar et al. 10.1007/s10661-021-09119-6
224. Four-Year Monitoring Study of Shallow Landslide Hazards Based on Hydrological Measurements in a Weathered Granite Soil Slope in South Korea K. Kim et al. 10.3390/w13172330
225. Exploring spatial non-stationarity in the relationships between landslide susceptibility and conditioning factors: a local modeling approach using geographically weighted regression C. Chalkias et al. 10.1007/s10064-020-01733-x
226. Electrical Resistivity Tomography (ERT) Investigation for Landslides: Case Study in the Hunan Province, China M. Sun et al. 10.3390/app14073007
227. Assessing landslide susceptibility using improved machine learning methods and considering spatial heterogeneity for the Three Gorges Reservoir Area, China J. Dong et al. 10.1007/s11069-023-06235-z
228. A comparative study of different machine learning methods coupled with GIS for landslide susceptibility assessment: a case study of N’fis basin, Marrakesh High Atlas (Morocco) H. Ait Naceur et al. 10.1007/s12517-022-10349-2
229. The added value of a regional landslide susceptibility assessment: The western branch of the East African Rift A. Depicker et al. 10.1016/j.geomorph.2019.106886
230. Application of Bayesian Hyperparameter Optimized Random Forest and XGBoost Model for Landslide Susceptibility Mapping S. Wang et al. 10.3389/feart.2021.712240
231. Implementation of hydrometeorological thresholds for regional landslide warning in Catalonia (NE Spain) R. Palau et al. 10.1007/s10346-023-02094-8
232. Temporal patterns of nonseismically triggered landslides in Shaanxi Province, China H. Qiu et al. 10.1016/j.catena.2019.104356
233. 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
234. Changes in Human Vulnerability to Flood and Landslide: Evidences from Historical Data O. Petrucci 10.3390/su16166715
235. Evaluation of Susceptibility by Mass Movements through Stochastic and Statistical Methods for a Region of Bucaramanga, Colombia J. Valencia Ortiz et al. 10.3390/rs15184567
236. Machine Learning Approaches for Mapping and Predicting Landslide-Prone Areas in São Sebastião (Southeast Brazil) E. Alcântara et al. 10.1016/j.nhres.2024.10.003
237. Space-time data-driven modeling of precipitation-induced shallow landslides in South Tyrol, Italy M. Moreno et al. 10.1016/j.scitotenv.2023.169166
238. Synoptic-scale precursors of landslides in the western Himalaya and Karakoram K. Hunt & A. Dimri 10.1016/j.scitotenv.2021.145895
239. Reconstruction of surface deformation characteristics in alpine canyons under shadow conditions Z. Gu & X. Yao 10.1007/s11629-021-7294-1
240. Properties of fault zones and their influences on rainfall-induced landslides, examples from Alborz and Zagros ranges M. Ehteshami-Moinabadi 10.1007/s12665-022-10283-2
241. Landslide mapping and analysis along the China-Pakistan Karakoram Highway based on SBAS-InSAR detection in 2017 X. Su et al. 10.1007/s11629-021-6686-6
242. Combining remote sensing techniques and field surveys for post-earthquake reconnaissance missions G. Giardina et al. 10.1007/s10518-023-01716-9
243. A material point method analysis of failure mechanism and kinematic behavior of rainfall-induced landslide S. Wang et al. 10.1007/s11069-024-06770-3
244. Landslide susceptibility mapping using physics-guided machine learning: a case study of a debris flow event in Colorado Front Range T. Pei & T. Qiu 10.1007/s11440-024-02384-y
245. Regional early warning model for rainfall induced landslide based on slope unit in Chongqing, China S. Liu et al. 10.1016/j.enggeo.2024.107464
246. Effects of solid fraction of saturated granular flows on overflow and landing mechanisms of rigid barriers C. Ng et al. 10.1680/jgeot.21.00170
247. The landslide traces inventory in the transition zone between the Qinghai-Tibet Plateau and the Loess Plateau: a case study of Jianzha County, China T. Li et al. 10.3389/feart.2024.1370992
248. Landslides forecasting using satellite rainfall estimations and machine learning in the Colombian Andean region D. Gómez et al. 10.1016/j.jsames.2023.104293
249. Analysis of an anthropogenically-induced landslide with emphasis on geological precursors M. Apon et al. 10.1016/j.rines.2024.100020
250. New global characterisation of landslide exposure R. Emberson et al. 10.5194/nhess-20-3413-2020
251. Systematic Quantification and Assessment of Digital Image Correlation Performance for Landslide Monitoring D. Hermle et al. 10.3390/geosciences13120371
252. 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
253. Dynamic Response and Failure Process of a Counter-Bedding Rock Slope under Strong Earthquake Conditions M. Guo et al. 10.3390/sym14010103
254. Entering the Era of Earth Observation-Based Landslide Warning Systems: A Novel and Exciting Framework K. Dai et al. 10.1109/MGRS.2019.2954395
255. Site scale landslide deformation and strain analysis using MT-InSAR and GNSS approach – A case study V. Kumar Maurya et al. 10.1016/j.asr.2022.05.028
256. Landslide hazard assessment based on Bayesian optimization–support vector machine in Nanping City, China W. Xie et al. 10.1007/s11069-021-04862-y
257. Rainfall-induced landslide susceptibility mapping using machine learning algorithms and comparison of their performance in Hilly area of Fujian Province, China P. Ye et al. 10.1007/s11069-022-05332-9
258. Mechanics of coseismic and postseismic acceleration of active landslides M. Kohler & A. Puzrin 10.1038/s43247-023-00797-3
259. 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
260. Mitigating GNSS multipath in landslide areas: A novel approach considering mutation points at different stages X. Liu et al. 10.1007/s10346-023-02117-4
261. Space-time landslide predictive modelling L. Lombardo et al. 10.1016/j.earscirev.2020.103318
262. Effect of basin morphometric parameters on physically-based rainfall thresholds for shallow landslides R. Marin et al. 10.1016/j.enggeo.2020.105855
263. Study on the Optimization of Pile Length of Micropiles in Soil Landslides H. Cheng et al. 10.3390/app13179980
264. Surface wave monitoring using ambient noise for detecting temporal variations in underground structures in landslide area C. Feng et al. 10.1016/j.enggeo.2024.107706
265. Comprehensive study on evaluation of Kaliasaur Landslide attributes in Garhwal Himalaya by the execution of geospatial, geotechnical and geophysical methods J. Velayudham et al. 10.1016/j.qsa.2021.100025
266. Assessing landslide susceptibility based on hybrid multilayer perceptron with ensemble learning H. Hong 10.1007/s10064-023-03409-8
267. Reactivation/Acceleration of Landslides Caused by the 2018 Baige Landslide-Dammed Lake and its Breach Floods Revealed by InSAR and Optical Images Z. Xiong et al. 10.1109/JSTARS.2023.3339234
268. Landslide topology uncovers failure movements K. Bhuyan et al. 10.1038/s41467-024-46741-7
269. Prototype of an IoT-Based Low-Cost Sensor Network for the Hydrological Monitoring of Landslide-Prone Areas P. Marino et al. 10.3390/s23042299
270. Assessing Historical Landslide Risk Management Based on Trigger Magnitude and Consequences: A Case Study from the Rokko Mountains, Kobe, Japan T. Sato & Y. Shuin 10.1007/s10706-024-02932-z
271. Landslide precipitation thresholds in Rwanda J. Uwihirwe et al. 10.1007/s10346-020-01457-9
272. Empowerment of Farmer Institutions in Improving Farmer’s Bargaining Position M. Sasmi et al. 10.1088/1755-1315/1177/1/012001
273. Deciphering seasonal effects of triggering and preparatory precipitation for improved shallow landslide prediction using generalized additive mixed models S. Steger et al. 10.5194/nhess-23-1483-2023
274. Landslide mapping from multi-sensor data through improved change detection-based Markov random field P. Lu et al. 10.1016/j.rse.2019.111235
275. Understanding fatal landslides at global scales: a summary of topographic, climatic, and anthropogenic perspectives S. Fidan et al. 10.1007/s11069-024-06487-3
276. Internet of Things Geosensor Network for Cost-Effective Landslide Early Warning Systems M. Gamperl et al. 10.3390/s21082609
277. A new strategy to map landslides with a generalized convolutional neural network N. Prakash et al. 10.1038/s41598-021-89015-8
278. Event-based rainfall-induced landslide inventories and rainfall thresholds for Malawi P. Niyokwiringirwa et al. 10.1007/s10346-023-02203-7
279. Mechanism Analysis and Process Inversion of the “7.26” Landslide in the West Open-Pit Mine of Fushun, China H. Meng et al. 10.3390/w15142652
280. LADI: Landslide displacement interpolation through a spatial-temporal Kalman filter A. Senogles et al. 10.1016/j.cageo.2023.105451
281. Effect of groundwater table fluctuation on slope instability: a comprehensive 3D simulation approach for Kotropi landslide, India S. Panda et al. 10.1007/s10346-022-01993-6
282. Deformation Monitoring and Trend Analysis of Reservoir Bank Landslides by Combining Time-Series InSAR and Hurst Index X. Zhang et al. 10.3390/rs15030619
283. Forecasting landslide deformation by integrating domain knowledge into interpretable deep learning considering spatiotemporal correlations Z. Ma & G. Mei 10.1016/j.jrmge.2024.02.034
284. Mass exchange between geophysical flows and beds: Idealised computational modelling using a Herschel-Bulkley rheology S. Goodwin et al. 10.1051/e3sconf/202341501008
285. Identification of Potential Landslides in the Gaizi Valley Section of the Karakorum Highway Coupled with TS-InSAR and Landslide Susceptibility Analysis K. Lin et al. 10.3390/rs16193653
286. Integrating empirical models and satellite radar can improve landslide detection for emergency response K. Burrows et al. 10.5194/nhess-21-2993-2021
287. Coupling effect of impoundment and irrigation on landslide movement in Maoergai Reservoir area revealed by multi-platform InSAR observations J. Du et al. 10.1016/j.jag.2024.103802
288. Characteristics of Rainfall Events Triggering Landslides in Two Climatologically Different Areas: Southern Ecuador and Southern Spain J. Palenzuela Baena et al. 10.3390/hydrology7030045
289. Detecting Long-Term Deformation of a Loess Landslide from the Phase and Amplitude of Satellite SAR Images: A Retrospective Analysis for the Closure of a Tunnel Event Y. Zhu et al. 10.3390/rs13234841
290. Application of a novel constitutive model to evaluate the shear deformation of discontinuity S. Xie et al. 10.1016/j.enggeo.2022.106693
291. Coupled transient saturated–unsaturated seepage and limit equilibrium analysis for slopes: influence of rapid water level changes A. Biniyaz et al. 10.1007/s11440-021-01359-7
292. Efficient Identification and Monitoring of Landslides by Time-Series InSAR Combining Single- and Multi-Look Phases Z. Liu et al. 10.3390/rs14041026
293. Prediction of landslide block movement based on Kalman filtering data assimilation method Y. Liu et al. 10.1007/s11629-023-7902-3
294. Preliminary insights from hydrological field monitoring for the evaluation of landslide triggering conditions over large areas L. Schilirò et al. 10.1007/s11069-023-06064-0
295. GIS-based analysis of landslides susceptibility mapping: a case study of Lushoto district, north-eastern Tanzania M. Makonyo & Z. Zahor 10.1007/s11069-023-06038-2
296. Objectives and main results of “Community Participation for Landslide Disaster Risk Reduction” thematic papers J. Klimeš et al. 10.1007/s10346-019-01246-z
297. Landslide Susceptibility Analysis: A Logistic Regression Model Case Study in Coonoor, India E. Sujatha & V. Sridhar 10.3390/hydrology8010041
298. Integrating local pore water pressure monitoring in territorial early warning systems for weather-induced landslides G. Pecoraro & M. Calvello 10.1007/s10346-020-01599-w
299. Landslide risk assessment based on susceptibility and vulnerability J. Mosaffaie et al. 10.1007/s10668-023-03093-4
300. Management of Landslides in a Rural–Urban Transition Zone Using Machine Learning Algorithms—A Case Study of a National Highway (NH-44), India, in the Rugged Himalayan Terrains M. Fayaz et al. 10.3390/land11060884
301. Influence of Calculation Parameters on the Slope Stability of the Historical Rasos Cemetery in Vilnius (Lithuania) R. Chmielewski et al. 10.3390/su16072891
302. Integrating geoinformatics and numerical modelling for landslide back-analysis and forecasting: a proactive mitigation study of the Shiv Bawri landslide A. Sajwan & G. Ramana 10.1007/s10346-024-02321-w
303. Deep learning forecast of rainfall-induced shallow landslides A. Mondini et al. 10.1038/s41467-023-38135-y
304. 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
305. A ground instabilities inventory between Tetouan and Jebha (Morocco): mapping, description and analysis H. Tribak et al. 10.1007/s10064-023-03161-z
306. Landslide Inventory in the Downstream of the Niulanjiang River with ALOS PALSAR and Sentinel-1 Datasets Z. Wang et al. 10.3390/rs14122873
307. Sustainability Nexus AID: landslides and land subsidence M. Motagh et al. 10.1007/s00550-024-00549-7
308. Landslide risk index map at the municipal scale for Costa Rica A. Quesada-Román 10.1016/j.ijdrr.2021.102144
309. Monitoring of rainfall-induced landslides at Songmao and Lushan, Taiwan, using IoT and big data-based monitoring system Y. Lau et al. 10.1007/s10346-022-01964-x
310. Spatial modelling of shallow landslide susceptibility: a study from the southern Western Ghats region of Kerala, India. A. Achu et al. 10.1080/19475683.2020.1758207
311. 降雨诱发深层老滑坡复活变形的动态作用机制 K. Song et al. 10.3799/dqkx.2022.184
312. An assessment of the spatial distribution of shallow landslides induced by Hurricane María in Puerto Rico C. Ramos-Scharrón et al. 10.1080/02723646.2020.1801121
313. Assessment of stability of a Himalayan road cut slope with varying degrees of weathering: A finite-element-model-based approach G. Komadja et al. 10.1016/j.heliyon.2020.e05297
314. Advancing predictive accuracy of shallow landslide using strategic data augmentation H. Qiu et al. 10.1016/j.jrmge.2024.09.010
315. Indicator-based approach for assigning physical vulnerability of the houses to landslide hazard in the Himalayan region of India S. Bera et al. 10.1016/j.ijdrr.2020.101891
316. Improving Spatial Landslide Prediction with 3D Slope Stability Analysis and Genetic Algorithm Optimization: Application to the Oltrepò Pavese N. Palazzolo et al. 10.3390/w13060801
317. Forecasting landslides using SIGMA model: a case study from Idukki, India M. Abraham et al. 10.1080/19475705.2021.1884610
318. The importance of input data on landslide susceptibility mapping K. Gaidzik & M. Ramírez-Herrera 10.1038/s41598-021-98830-y
319. Landslides caught on seismic networks and satellite radars A. Manconi & A. Mondini 10.5194/nhess-22-1655-2022
320. Biomechanical analysis head–neck injuries against mine falls using a simplified human model R. Garg et al. 10.1007/s12046-022-02028-5
321. Comparison of LiDAR- and UAV-derived data for landslide susceptibility mapping using Random Forest algorithm F. França Pereira et al. 10.1007/s10346-022-02001-7
322. Landslides triggered by the 2015 Mw 6.0 Sabah (Malaysia) earthquake: inventory and ESI-07 intensity assignment M. Ferrario 10.5194/nhess-22-3527-2022
323. Performance Study of Landslide Detection Using Multi-Temporal SAR Images Y. Lin et al. 10.3390/rs14102444
324. Reconstruction and Characterisation of Past and the Most Recent Slope Failure Events at the 2021 Rock-Ice Avalanche Site in Chamoli, Indian Himalaya A. Bhardwaj & L. Sam 10.3390/rs14040949
325. Is the Grain Size Distribution a Key Parameter for Explaining the Long Runout of Granular Avalanches? M. Cabrera & N. Estrada 10.1029/2021JB022589
326. Optimizing Landslide Susceptibility Model Using Artificial Neural Network (ANN) Approach in Sawla-Laska Road Corridor and Surroundings, Southwest Ethiopia T. Unkuse et al. 10.21523/gcj1.2024080101
327. A semi-conservative depth-averaged material point method for fast flow-like landslides and mudflows M. Fois et al. 10.1016/j.cnsns.2024.108202
328. Detecting slow-moving landslides in parts of Darjeeling–Sikkim Himalaya, NE India: quantitative constraints from PSInSAR and its relation to the structural discontinuities S. Singh et al. 10.1007/s10346-022-01900-z
329. Underground Displacement Measurement Method Based on Double Mutual Inductance Voltage Contour Model of Optimized Dual Kriging N. Shentu et al. 10.1109/JSEN.2023.3265031
330. Hazardous exogenous geological processes in the mountains under the pressure of human activity: 15-year observations from a natural landscape to a large ski resort A. Derkacheva et al. 10.1007/s11069-023-06309-y
331. Remote sensing and GIS-based landslide susceptibility mapping using LNRF method in part of Western Ghats of India A. Patil & S. Panhalkar 10.1016/j.qsa.2023.100095
332. Adopting the margin of stability for space–time landslide prediction – A data-driven approach for generating spatial dynamic thresholds S. Steger et al. 10.1016/j.gsf.2024.101822
333. Hong Kong’s landslip warning system—40 years of progress V. Kong et al. 10.1007/s10346-020-01379-6
334. A comprehensive appraisal on the effect of aerosol on mountain glaciers: special reference to Sikkim Himalayan region of India S. Kumari & A. Middey 10.1007/s12046-023-02097-0
335. Integrating principal component analysis with statistically-based models for analysis of causal factors and landslide susceptibility mapping: A comparative study from the loess plateau area in Shanxi (China) Y. Tang et al. 10.1016/j.jclepro.2020.124159
336. Landslide Risk Management in Areas Affected by Wildfires or Floods: A Comprehensive Framework Integrating GIS, Remote Sensing Techniques, and Regional Climate Models C. Nefros & C. Loupasakis 10.12681/bgsg.35629
337. Automatic recognition of active landslides by surface deformation and deep learning X. Wang et al. 10.1177/03091333241276523
338. Fast physically-based model for rainfall-induced landslide susceptibility assessment at regional scale V. Medina et al. 10.1016/j.catena.2021.105213
339. Landslide hazard mapping in Chefchaouen, Morocco: AHP-GIS integration L. Dahmani et al. 10.1080/00207233.2024.2412483
340. Performance assessment for three statistical models of landslide susceptibility zonation mapping: A case study for Dharamshala Region, Himachal Pradesh, India K. Sweta et al. 10.1007/s12040-022-01881-6
341. A random forest model of landslide susceptibility mapping based on hyperparameter optimization using Bayes algorithm D. Sun et al. 10.1016/j.geomorph.2020.107201
342. Advancing reservoir landslide stability assessment via TS-InSAR and airborne LiDAR observations in the Daping landslide group, Three Gorges Reservoir Area, China L. Zhang et al. 10.1007/s10346-024-02337-2
343. Potential of satellite-derived hydro-meteorological information for landslide initiation thresholds in Rwanda J. Uwihirwe et al. 10.5194/nhess-22-3641-2022
344. Prediction of landslide velocity and displacement from groundwater level changes considering the shear rate-dependent friction of sliding zone soil H. Miao & G. Wang 10.1016/j.enggeo.2023.107361
345. Landslide susceptibility mapping of Phewa Watershed, Kaski, Nepal B. Kunwar et al. 10.21595/mme.2024.24231
346. Assessing the Effects of LULC Change on Landslide Hazards in Rwanda N. Hafashimana et al. 10.14232/jengeo-2022-44169
347. A GIS-Based Approach for Shallow Landslides Risk Assessment in the Giampilieri and Briga Catchments Areas (Sicily, Italy) G. Vegliante et al. 10.3390/geohazards5010011
348. Numerical Modelling of Debris Flows for Simulation-Based Decision Support: An Indian Perspective M. Abraham et al. 10.1007/s40098-024-00988-5
349. 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
350. Machine Learning: New Potential for Local and Regional Deep-Seated Landslide Nowcasting A. van Natijne et al. 10.3390/s20051425
351. Relationships between earthquakes, hurricanes, and landslides in Costa Rica A. Quesada-Román et al. 10.1007/s10346-019-01209-4
352. Hydro-meteorological landslide triggering thresholds based on artificial neural networks using observed precipitation and ERA5-Land soil moisture P. Distefano et al. 10.1007/s10346-023-02132-5
353. GIS-based landslide susceptibility mapping using frequency ratio and index of entropy models for She County of Anhui Province, China Y. Liu et al. 10.1515/arh-2022-0122
354. Enhancing the reliability of landslide early warning systems by machine learning H. Thirugnanam et al. 10.1007/s10346-020-01453-z
355. Heavy rainfall drives slow-moving landslide in Mazhe Village, Enshi to a catastrophic collapse on 21 July 2020 C. Xue et al. 10.1007/s10346-021-01782-7
356. Enhanced dynamic landslide hazard mapping using MT-InSAR method in the Three Gorges Reservoir Area C. Zhou et al. 10.1007/s10346-021-01796-1
357. Automatic detection of active geohazards with millimeter-to-meter-scale deformation and quantitative analysis of factors influencing spatial distribution: A case study in the Hexi corridor, China B. Chen et al. 10.1016/j.jag.2024.103995
358. Combining seismic signal dynamic inversion and numerical modeling improves landslide process reconstruction Y. Yan et al. 10.5194/esurf-10-1233-2022
359. Henry’s gas solubility optimization algorithm in formulating deep neural network for landslide susceptibility assessment in mountainous areas Q. Nguyen et al. 10.1007/s12665-021-09711-6
360. Temporal Probability Assessment and Its Use in Landslide Susceptibility Mapping for Eastern Bhutan A. Dikshit et al. 10.3390/w12010267
361. Prompt Quantitative Risk Assessment for Rain-Induced Landslides J. He et al. 10.1061/JGGEFK.GTENG-10980
362. Landslide susceptibility assessment using GIS-based multicriteria decision analysis (MCDA) along a part of National Highway-1, Kashmir- Himalayas, India I. Beigh & S. Bukhari 10.1007/s12518-024-00559-6
363. Comparison of Three Mixed-Effects Models for Mass Movement Susceptibility Mapping Based on Incomplete Inventory in China Y. He & Y. Zhang 10.3390/rs14236068
364. Global connections between El Nino and landslide impacts R. Emberson et al. 10.1038/s41467-021-22398-4
365. Cyclic landslide-flood chains along a major mountain river Y. Yang et al. 10.1016/j.geomorph.2023.108835
366. Project ‘‘Mass Movements in Germany’’ and its implications for nationwide landslide susceptibility assessment J. Torizin et al. 10.1007/s10064-024-03691-0
367. Including informal housing in slope stability analysis – an application to a data-scarce location in the humid tropics E. Bozzolan et al. 10.5194/nhess-20-3161-2020
368. Landslide susceptibility assessment in the Himalayan range based along Kasauli – Parwanoo road corridor using weight of evidence, information value, and frequency ratio A. Alsabhan et al. 10.1016/j.jksus.2021.101759
369. Thermal Remote Sensing from UAVs: A Review on Methods in Coastal Cliffs Prone to Landslides M. Melis et al. 10.3390/rs12121971
370. Effects of hysteretic soil water characteristic curves on the hydromechanical behaviour Y. Yang & H. Yeh 10.1007/s12040-023-02146-6
371. Assessment of landslide susceptibility in the Himalayan state of Tripura, India, using a Multi-Model Approach D. Das et al. 10.12944/CWE.19.2.29
372. Invited perspectives: Mountain roads in Nepal at a new crossroads K. Sudmeier-Rieux et al. 10.5194/nhess-19-655-2019
373. Landslide Susceptibility Mapping Using Feature Fusion-Based CPCNN-ML in Lantau Island, Hong Kong Y. Chen et al. 10.1109/JSTARS.2021.3066378
374. Enhancing disaster risk resilience using greenspace in urbanising Quito, Ecuador C. Watson et al. 10.5194/nhess-22-1699-2022
375. Landslide Segmentation with Deep Learning: Evaluating Model Generalization in Rainfall-Induced Landslides in Brazil L. Soares et al. 10.3390/rs14092237
376. Landslide monitoring techniques in the Geological Surveys of Europe M. Auflič et al. 10.1007/s10346-022-02007-1
377. Landslide displacement forecasting using deep learning and monitoring data across selected sites L. Nava et al. 10.1007/s10346-023-02104-9
378. Regional-scale InSAR investigation and landslide early warning thresholds in Umbria, Italy F. Ponziani et al. 10.1016/j.enggeo.2023.107352
379. The influences of the spatial extent selection for non-landslide samples on statistical-based landslide susceptibility modelling: a case study of Anhui Province in China C. Wang et al. 10.1007/s11069-022-05252-8
380. Pre-collapse motion of the February 2021 Chamoli rock–ice avalanche, Indian Himalaya M. Van Wyk de Vries et al. 10.5194/nhess-22-3309-2022
381. A comparative modeling of landslides susceptibility at a meso-scale using frequency ratio and analytic hierarchy process models in geographic information system: the case of African Alpine Mountains (Rif, Morocco) N. Boukhres et al. 10.1007/s40808-022-01605-1
382. Landslide Deformation Analysis and Prediction with a VMD-SA-LSTM Combined Model C. Wen et al. 10.3390/w16202945
383. Quantification of meteorological conditions for rockfall triggers in Germany K. Nissen et al. 10.5194/nhess-22-2117-2022
384. Vulnerability index related to populations at-risk for landslides in the Brazilian Early Warning System (BEWS) M. Assis Dias et al. 10.1016/j.ijdrr.2020.101742
385. How can landslide risk maps be validated? Potential solutions with open-source databases F. Caleca et al. 10.3389/feart.2022.998885
386. Zonation of Landslide Susceptibility in Ruijin, Jiangxi, China X. Zhou et al. 10.3390/ijerph18115906
387. Rapid evaluation of earthquake-induced landslides by PGA and Arias intensity model: insights from the Luding Ms6.8 earthquake, Tibetan Plateau C. Li et al. 10.3389/feart.2023.1324773
388. Landslide Prediction Method Based on a Ground-Based Micro-Deformation Monitoring Radar L. Qi et al. 10.3390/rs12081230
389. Satellite rainfall products outperform ground observations for landslide prediction in India M. Brunetti et al. 10.5194/hess-25-3267-2021
390. A multistage hybrid model for landslide risk mapping: tested in and around Mussoorie in Uttarakhand state of India M. Mishra & T. Sarkar 10.1007/s12665-020-09180-3
391. Preface to the Special Issue “Rainfall Thresholds and Other Approaches for Landslide Prediction and Early Warning” S. Segoni et al. 10.3390/w13030323
392. Improving landslide inventories by combining satellite interferometry and landscape analysis: the case of Sierra Nevada (Southern Spain) C. Reyes-Carmona et al. 10.1007/s10346-023-02071-1
393. Seismotectonic and anthropogenic factors controlling landslide hazard in Gafsa phosphates quarries I. Mahmoudi et al. 10.1007/s10064-024-03747-1
394. SAR data and field surveys combination to update rainfall-induced shallow landslide inventory P. Miele et al. 10.1016/j.rsase.2022.100755
395. Refined Landslide Susceptibility Mapping Considering Land Use Changes and InSAR Deformation: A Case Study of Yulin City, Guangxi P. Li et al. 10.3390/rs16163016
396. Landslide failure time prediction with a new model: case studies in Fushun west open pit mine, China J. Hu et al. 10.1007/s10064-024-03902-8
397. A Modeling Platform for Landslide Stability: A Hydrological Approach M. Emadi-Tafti & B. Ataie-Ashtiani 10.3390/w11102146
398. Spatial and temporal landslide distributions using global and open landslide databases D. Gómez et al. 10.1007/s11069-023-05848-8
399. An Infrared Thermography Approach to Evaluate the Strength of a Rock Cliff M. Loche et al. 10.3390/rs13071265
400. 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
401. Inventory of shallow landslides triggered by extreme precipitation in July 2023 in Beijing, China H. Ma & F. Wang 10.1038/s41597-024-03901-0
402. Development of integrated deep learning and machine learning algorithm for the assessment of landslide hazard potential B. Aslam et al. 10.1007/s00500-021-06105-5
403. Effects of debris flow rheology on overflow and impact dynamics against dual-rigid barriers C. Ng et al. 10.1680/jgeot.21.00226
404. Rainfall-induced landslide early warning system based on corrected mesoscale numerical models: an application for the southern Andes I. Fustos-Toribio et al. 10.5194/nhess-22-2169-2022
405. Unmanned Aerial Vehicles (UAVs) in Landslide Investigation and Monitoring: A Review J. Sun et al. 10.3390/drones8010030
406. Failure mechanism and landslide fragility of reinforced concrete buildings considering uncertain flow properties M. Kulariya & S. Saha 10.1080/17499518.2024.2337377
407. Statistical-spatial modeling of the potential of landslide occurrence in Yamchi catchment F. Pourfarrashzadeh et al. 10.61186/jsaeh.11.1.4
408. Modelling antecedent soil hydrological conditions to improve the prediction of landslide susceptibility in typhoon-prone regions C. Abancó et al. 10.1007/s10346-024-02242-8
409. Data-Driven Landslide Nowcasting at the Global Scale T. Stanley et al. 10.3389/feart.2021.640043
410. Hydrological influences on landslide dynamics in the three gorges reservoir area: an SBAS-InSAR study in Yunyang county, Chongqing J. Cui et al. 10.1007/s12665-024-11770-4
411. Strategic protection of landslide vulnerable mountains for biodiversity conservation under land-cover and climate change impacts B. Li et al. 10.1073/pnas.2113416118
412. Keynote lecture. Landslide Early Warning Systems: Resources or Problems? F. Guzzetti et al. 10.1051/e3sconf/202341503010
413. Vadose Zone Thickness Limits Pore‐Fluid Pressure Rise in a Large, Slow‐Moving Earthflow C. Murphy et al. 10.1029/2021JF006415
414. Analysis of failure of high slope subjected to rainfall infiltration at Peringavu in Kerala, India V. Santhosh Kumar & S. Sennimalai Chandrasekaran 10.1016/j.engfailanal.2022.106423
415. Recent advancements of landslide hydrology R. Greco et al. 10.1002/wat2.1675
416. Insights into spatial differential characteristics of landslide susceptibility from sub-region to whole-region cased by northeast Chongqing, China R. Liu et al. 10.1080/19475705.2023.2190858
417. Contrasting Population Projections to Induce Divergent Estimates of Landslides Exposure Under Climate Change Q. Lin et al. 10.1029/2023EF003741
418. Q-Slope: Rock Slope Engineering 10 Years on N. Bar & N. Barton 10.1007/s00603-024-04064-5
419. Assessing torrentiality in catchments of the tropical Andes: A morphometric approach S. Machuca et al. 10.1016/j.jsames.2023.104775
420. A new global landslide dam database (RAGLAD) and analysis utilizing auxiliary global fluvial datasets H. Wu et al. 10.1007/s10346-021-01817-z
421. Geomorphology of landslide–flood-critical areas in hilly catchments and urban areas for EWS (Feltrino Stream and Lanciano town, Abruzzo, Central Italy) C. Carabella et al. 10.1080/17445647.2020.1819903
422. The dynamic threat from landslides following large continental earthquakes K. Arrell et al. 10.1371/journal.pone.0308444
423. Integrated deep learning with explainable artificial intelligence for enhanced landslide management S. Alqadhi et al. 10.1007/s11069-023-06260-y
424. Understanding slow-moving landslide triggering processes using low-cost passive seismic and inclinometer monitoring S. Fiolleau et al. 10.1016/j.jappgeo.2023.105090
425. Data-driven landslide forecasting: Methods, data completeness, and real-time warning T. Xiao & L. Zhang 10.1016/j.enggeo.2023.107068
426. Modeling impacts of climate change on return period of landslide triggering D. Peres & A. Cancelliere 10.1016/j.jhydrol.2018.10.036
427. Co-seismic landslide mapping using Sentinel-2 10-m fused NIR narrow, red-edge, and SWIR bands P. Lu et al. 10.1007/s10346-021-01636-2
428. Forecasting the time of failure of landslides at slope-scale: A literature review E. Intrieri et al. 10.1016/j.earscirev.2019.03.019
429. Applying deep learning and benchmark machine learning algorithms for landslide susceptibility modelling in Rorachu river basin of Sikkim Himalaya, India K. Mandal et al. 10.1016/j.gsf.2021.101203
430. Landslide Susceptibility Mapping with Integrated SBAS-InSAR Technique: A Case Study of Dongchuan District, Yunnan (China) Z. Zhu et al. 10.3390/s22155587
431. Analysis of the rainfall pattern triggering the Lemešná debris flow, Javorníky Range, the Czech Republic J. Smolíková et al. 10.1007/s11069-021-04546-7
432. Time-varying baseline error correction method for ground-based micro-deformation monitoring radar T. Lei et al. 10.23919/JSEE.2022.000091
433. InSAR-based landslide detection method with the assistance of C-index Z. Xiong et al. 10.1007/s10346-023-02120-9
434. Prediction of Landslide Susceptibility in the Karakorum under the Context of Climate Change Y. Pei et al. 10.3390/app14188562
435. A Robust SAR Speckle Tracking Workflow for Measuring and Interpreting the 3D Surface Displacement of Landslides D. Donati et al. 10.3390/rs13153048
436. Post-failure landslide change detection and analysis using optical satellite Sentinel-2 images F. Qu et al. 10.1007/s10346-020-01498-0
437. Landslide susceptibility modelling using hybrid bivariate statistical-based machine-learning method in a highland segment of Southern Western Ghats, India A. Achu et al. 10.1007/s12665-022-10464-z
438. Identifying recurrent and persistent landslides using satellite imagery and deep learning: A 30-year analysis of the Himalaya T. Chen et al. 10.1016/j.scitotenv.2024.171161
439. Development of a Landslide Early Warning System in Indonesia R. Hidayat et al. 10.3390/geosciences9100451
440. How much does the rainfall temporal resolution affect rainfall thresholds for landslide triggering? S. Gariano et al. 10.1007/s11069-019-03830-x
441. Creep-to-Runout Transition of Large Landslides Controlled by Frictional Velocity Strengthening and Weakening (Vajont 1963, Italy) H. Zhang et al. 10.1007/s00603-023-03473-2
442. Controls on the size distributions of shallow landslides D. Bellugi et al. 10.1073/pnas.2021855118
443. Simultaneous state–parameter estimation of rainfall-induced landslide displacement using data assimilation J. Wang et al. 10.5194/nhess-19-1387-2019
444. A Heuristic Method to Evaluate the Effect of Soil Tillage on Slope Stability: A Pilot Case in Central Italy E. Volpe et al. 10.3390/land11060912
445. Comparison between Deep Learning and Tree-Based Machine Learning Approaches for Landslide Susceptibility Mapping S. Saha et al. 10.3390/w13192664
446. Landslide displacement prediction based on time series and long short-term memory networks A. Jin et al. 10.1007/s10064-024-03714-w
447. Towards a predictive multi-phase model for alpine mass movements and process cascades A. Cicoira et al. 10.1016/j.enggeo.2022.106866
448. A predictive model of societal landslide risk in Italy M. Rossi et al. 10.1016/j.earscirev.2019.04.021
449. New impact equation using barrier Froude number for the design of dual rigid barriers against debris flows C. Ng et al. 10.1007/s10346-021-01631-7
450. Precipitation-induced landslide risk escalation in China’s urbanization with high-resolution soil moisture and multi-source precipitation product K. He et al. 10.1016/j.jhydrol.2024.131536
451. Standards for shallow landslide identification in Brazil: Spatial trends and inventory mapping H. Dias & C. Grohmann 10.1016/j.jsames.2024.104805
452. Formation mechanism and evolution of the Jiaju landslide in the Dadu River, China Y. Bai et al. 10.1007/s10064-024-03611-2
453. Natural Disaster Risk Inequalities in Central America A. Quesada-Román & D. Campos-Durán 10.1080/23754931.2022.2081814
454. Landslide displacement prediction based on Variational mode decomposition and MIC-GWO-LSTM model Z. Taorui et al. 10.1007/s00477-021-02145-3
455. Rock slope failure preparation paced by total crack boundary length S. Lagarde et al. 10.1038/s43247-023-00851-0
456. A deep learning approach using graph convolutional networks for slope deformation prediction based on time-series displacement data Z. Ma et al. 10.1007/s00521-021-06084-6
457. Superpixel and Supervoxel Segmentation Assessment of Landslides Using UAV-Derived Models I. Farmakis et al. 10.3390/rs14225668
458. Changes in the rainfall event characteristics above the empirical global rainfall thresholds for landslide initiation at the pan-European level N. Bezak & M. Mikoš 10.1007/s10346-020-01579-0
459. A Geotechnical Investigation of 2017 Chattogram Landslides M. Islam et al. 10.3390/geosciences11080337
460. Towards landslide space-time forecasting through machine learning: the influence of rainfall parameters and model setting N. Nocentini et al. 10.3389/feart.2023.1152130
461. A Simple Model for Estimating the Hydraulic Conductivity of Unsaturated Soil Z. Zhang & M. Zhang 10.3390/app14031254
462. Morphometric and morphostructural analysis as a modeling tool in mass movement scenarios (Bucaramanga, Colombia) J. Valencia Ortiz & A. Martínez-Graña 10.1080/19475705.2024.2391427
463. Assessing the potential of soil moisture measurements for regional landslide early warning A. Wicki et al. 10.1007/s10346-020-01400-y
464. Investigation of rainfall intensity on the slope failure process using GPU-accelerated coupled MPM D. Wang et al. 10.1016/j.compgeo.2023.105718
465. A framework for automated landslide dating utilizing SAR-Derived Parameters Time-Series, An Enhanced Transformer Model, and Dynamic Thresholding W. Wang et al. 10.1016/j.jag.2024.103795
466. Climate Resilient Cities Assessing Differential Vulnerability to Climate Hazards in Urban India L. Rangwala et al. 10.46830/wrirpt.22.00055
467. Exploring time series models for landslide prediction: a literature review K. Ebrahim et al. 10.1186/s40677-024-00288-3
468. Assessing Global Landslide Casualty Risk Under Moderate Climate Change Based on Multiple GCM Projections X. Wang et al. 10.1007/s13753-023-00514-w
469. Multicollinearity and spatial correlation analysis of landslide conditioning factors in Langat River Basin, Selangor S. Selamat et al. 10.1007/s11069-024-06903-8
470. Comprehensive monitoring of talus slope deformation and displacement back analysis of mechanical parameters based on back-propagation neural network H. Xing et al. 10.1007/s10346-020-01613-1
471. Phenomenology of Avalanche Recordings From Distributed Acoustic Sensing P. Paitz et al. 10.1029/2022JF007011
472. Landslide susceptibility prediction using frequency ratio model: a case study of Uttarakhand, Himalaya (India) P. Singh et al. 10.1007/s43538-023-00171-z
473. Spatiotemporal patterns of non-seismic fatal landslides in China from 2010 to 2022 Z. Li et al. 10.1007/s10346-024-02362-1
474. Assessment of Landslide Hazard in Jiangxi Using Geo-information Technology P. Ou et al. 10.3389/feart.2021.648342
475. Extreme rainfall-related accelerations in landslides in Danba County, Sichuan Province, as detected by InSAR X. Shi et al. 10.1016/j.jag.2022.103109
476. Landslide hazard assessment and risk reduction in the rural community of Rampac Grande, Cordillera Negra, Peru J. Klimeš et al. 10.1007/s12665-023-11307-1
477. Geoinformatic Analysis of Rainfall-Triggered Landslides in Crete (Greece) Based on Spatial Detection and Hazard Mapping A. Argyriou et al. 10.3390/su14073956
478. A decrease in rockfall probability under climate change conditions in Germany K. Nissen et al. 10.5194/nhess-23-2737-2023
479. Regional-scale landslide risk assessment in Central Asia F. Caleca et al. 10.5194/nhess-24-13-2024
480. The influence of land use and land cover change on landslide susceptibility in the Lower Mekong River Basin C. Dandridge et al. 10.1007/s11069-022-05604-4
481. Landslide susceptibility mapping using GIS-based machine learning algorithms for the Northeast Chongqing Area, China Z. Bai et al. 10.1007/s12517-021-08871-w
482. Measuring ground surface elevation changes in a slow-moving colluvial landslide using combinations of regional airborne lidar, UAV lidar and UAV photogrammetric surveys S. Johnson et al. 10.1144/qjegh2022-078
483. Approximate water vertical infiltration extremum path in unsaturated soils J. Li et al. 10.1016/j.jhydrol.2023.129989
484. Deep learning models integrating multi-sensor and -temporal remote sensing to monitor landslide traces in Vietnam K. Dang et al. 10.1016/j.ijdrr.2024.104391
485. Are the historically known landslide events really the biggest? An insight using dendrogeomorphology K. Šilhán 10.1007/s10346-024-02354-1
486. Is tree-ring anatomy the key? searching for an optimal dendrogeomorphic approach to distinguish shallow creep and true slide movements K. Šilhán 10.1016/j.catena.2023.107466
487. Landslide prediction based on low-cost and sustainable early warning systems with IoT Y. Liu et al. 10.1007/s10064-023-03137-z
488. Slow-moving landslide risk assessment combining Machine Learning and InSAR techniques A. Novellino et al. 10.1016/j.catena.2021.105317
489. A new method for defining the local factor of safety based on displacement isosurfaces to assess slope stability T. Yang et al. 10.1016/j.enggeo.2022.106587
490. After 2000 Stože Landslide: Part II - Development of landslide disaster risk reduction policy in Slovenia M. Mikoš 10.15292/acta.hydro.2021.04
491. Estimating rainfall threshold and temporal probability for landslide occurrences in Darjeeling Himalayas A. Dikshit et al. 10.1007/s12303-020-0001-3
492. A review of landslide acceptable risk and tolerable risk K. Sim et al. 10.1186/s40677-022-00205-6
493. Integrated Geophysical Imaging and Remote Sensing for Enhancing Geological Interpretation of Landslides with Uncertainty Estimation—A Case Study from Cisiec, Poland M. Wróbel et al. 10.3390/rs15010238
494. Landslide Hazard Assessment of Kashmir 10.47485/2766-2624.1048
495. The geo-observer network: A proof of concept on participatory sensing of disasters in a remote setting L. Jacobs et al. 10.1016/j.scitotenv.2019.03.177
496. Analysis of Geotechnical-Assisted 2-D Electrical Resistivity Tomography Monitoring of Slope Instability in Residual Soil of Weathered Granitic Basement O. Olabode et al. 10.3389/feart.2020.580230
497. Accurate IoT Based Slope Instability Sensing System for Landslide Detection N. Kumar M. & M. Ramesh 10.1109/JSEN.2022.3189903
498. Fatal landslides in Colombia (from historical times to 2020) and their socio-economic impacts H. Garcia-Delgado et al. 10.1007/s10346-022-01870-2
499. Landslide susceptibility modeling using different artificial intelligence methods: a case study at Muong Lay district, Vietnam T. Phong et al. 10.1080/10106049.2019.1665715
500. 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
501. Exploring the multiple land degradation pathways across the planet R. Prăvălie 10.1016/j.earscirev.2021.103689
502. A Scientometric Analysis of Predicting Methods for Identifying the Environmental Risks Caused by Landslides Y. Zou & C. Zheng 10.3390/app12094333
503. Changing significance of landslide Hazard and risk after the 2015 Mw 7.8 Gorkha, Nepal Earthquake N. Rosser et al. 10.1016/j.pdisas.2021.100159
504. Different sampling strategies for predicting landslide susceptibilities are deemed less consequential with deep learning J. Dou et al. 10.1016/j.scitotenv.2020.137320
505. Optimization of SVR and CatBoost models using metaheuristic algorithms to assess landslide susceptibility R. Ajin et al. 10.1038/s41598-024-72663-x
506. The Post-Failure Spatiotemporal Deformation of Certain Translational Landslides May Follow the Pre-Failure Pattern L. Wang et al. 10.3390/rs14102333
507. Machine learning for landslides prevention: a survey Z. Ma et al. 10.1007/s00521-020-05529-8
508. Towards a Transferable Antecedent Rainfall—Susceptibility Threshold Approach for Landsliding E. Monsieurs et al. 10.3390/w11112202
509. Landslide Susceptibility Mapping Considering Landslide Local-Global Features Based on CNN and Transformer Z. Zhao et al. 10.1109/JSTARS.2024.3379350
510. A framework for identifying the onset of landslide acceleration based on the exponential moving average (EMA) J. Wang et al. 10.1007/s11629-023-7905-0
511. Living with landslides: Land use on unstable hillslopes in a rural tropical mountainous environment in DR Congo J. Maki Mateso et al. 10.1016/j.scitotenv.2024.171624
512. Assessing landslide susceptibility using geospatial technology in Bonga town, southwestern Ethiopia M. Melese & S. Gashure 10.1080/19376812.2023.2172054
513. Brief communication: Introducing rainfall thresholds for landslide triggering based on artificial neural networks P. Distefano et al. 10.5194/nhess-22-1151-2022
514. Low-Power and Wireless Communication Research on Underground Displacement Three-Dimensional Monitoring System N. Shentu et al. 10.3390/s24051592
515. An approach based on socio-politically optimized neural computing network for predicting shallow landslide susceptibility at tropical areas V. Nhu et al. 10.1007/s12665-021-09525-6
516. Global landslide susceptibility prediction based on the automated machine learning (AutoML) framework G. Tang et al. 10.1080/10106049.2023.2236576
517. A novel method using explainable artificial intelligence (XAI)-based Shapley Additive Explanations for spatial landslide prediction using Time-Series SAR dataset H. Al-Najjar et al. 10.1016/j.gr.2022.08.004
518. Application of modified Segment Tracing Algorithm (mSTA) Method to Identify Landslide Susceptibility Zones Around Mt. Sinabung, Indonesia . Zahratunnisa et al. 10.1088/1755-1315/1245/1/012012
519. Implications of landslide inventory in susceptibility modeling along a Himalayan highway corridor, India V. Pandey et al. 10.1080/02723646.2021.1872857
520. Landslide Susceptibility Mapping in Brazil: A Review H. Dias et al. 10.3390/geosciences11100425
521. Landslide Susceptibility Assessment Model Construction Using Typical Machine Learning for the Three Gorges Reservoir Area in China J. Cheng et al. 10.3390/rs14092257
522. Investigating Gravitational Slope Deformations with COSMO-SkyMed-Based Differential Interferometry: A Case Study of San Marco dei Cavoti M. Khalili et al. 10.3390/app13106291
523. Machine learning ensemble modelling as a tool to improve landslide susceptibility mapping reliability M. Di Napoli et al. 10.1007/s10346-020-01392-9
524. Enhancing Landslide Vulnerability Mapping Through Automated Fuzzy Logic Algorithm-Based Methodology A. Bruzón et al. 10.1007/s10706-023-02714-z
525. Evaluation of neural network models for landslide susceptibility assessment Y. Yi et al. 10.1080/17538947.2022.2062467
526. Effect of time and space partitioning strategies of samples on regional landslide susceptibility modelling K. Khanna et al. 10.1007/s10346-021-01627-3
527. Assessing framework of rainfall-induced landslide hazard considering spatiotemporal asymmetry in extreme precipitation indices under climate change C. Yan & D. Gong 10.1007/s00704-024-05106-2
528. Frequency analysis of extreme rainfall over the Japanese archipelago by leveraging gauge-adjusted radar and satellite estimates S. Mtibaa 10.1016/j.jhydrol.2024.131425
529. Analysis of human exposure to landslides with a GIS multiscale approach S. Modugno et al. 10.1007/s11069-021-05186-7
530. Comparative analysis of machine learning and multi-criteria decision making techniques for landslide susceptibility mapping of Muzaffarabad district U. Khalil et al. 10.3389/fenvs.2022.1028373
531. Study of the spatial distribution and the temporal trend of landslide disasters that occurred in the Nepal Himalayas from 2011 to 2020 R. KC et al. 10.1007/s12665-023-11347-7
532. The Spatial and Temporal Influence of Cloud Cover on Satellite-Based Emergency Mapping of Earthquake Disasters T. Robinson et al. 10.1038/s41598-019-49008-0
533. Research on the Landslide Prediction Based on the Dual Mutual-Inductance Deep Displacement 3D Measuring Sensor N. Shentu et al. 10.3390/app13010213
534. An integrated quantitative and qualitative approach for landslide susceptibility mapping in West Sikkim district, Indian Himalaya P. Biswakarma et al. 10.1080/19475705.2023.2273781
535. Inventory of Landslides in the Northern Half of the Taihang Mountain Range, China X. Zhang et al. 10.3390/geosciences14030074
536. Emergency Disposal Solution for Control of a Giant Landslide and Dammed Lake in Yangtze River, China G. Chen et al. 10.3390/w11091939
537. HazMapper: a global open-source natural hazard mapping application in Google Earth Engine C. Scheip & K. Wegmann 10.5194/nhess-21-1495-2021
538. Landslide Susceptibility Mapping Using Machine Learning: A Case Study of Oregon B. Wu et al. 10.1088/1755-1315/1334/1/012032
539. Assessing the spatiotemporal impact of climate change on event rainfall characteristics influencing landslide occurrences based on multiple GCM projections in China Q. Lin et al. 10.1007/s10584-020-02750-1
540. FLIDND-MCN: Fake label images detection of natural disasters with multi model convolutional neural network S. Alqhtani 10.3233/JIFS-213308
541. Time series analysis and long short-term memory neural network to predict landslide displacement B. Yang et al. 10.1007/s10346-018-01127-x
542. Shear Creep Properties and Creep Model of Gravel Sliding Zone: A Case Study of the Zhoujia Landslide in China S. Chen et al. 10.3389/feart.2022.838183
543. “Satark”: Landslide Prediction System over Western Ghats of India J. Kulkarni et al. 10.3390/land11050689
544. Deep Learning for Exploring Landslides with Remote Sensing and Geo-Environmental Data: Frameworks, Progress, Challenges, and Opportunities Q. Zhang & T. Wang 10.3390/rs16081344
545. Landslide assessment through integrated geoelectrical and seismic methods: A case study in Thungsong site, southern Thailand C. Sujitapan et al. 10.1016/j.heliyon.2024.e24660
546. Comparing methods for determining landslide early warning thresholds: potential use of non-triggering rainfall for locations with scarce landslide data availability D. Peres & A. Cancelliere 10.1007/s10346-021-01704-7
547. Visualization analysis of rainfall-induced landslides hazards based on remote sensing and geographic information system-an overview Z. Yang et al. 10.1080/17538947.2023.2229797
548. Uncertainties of landslide susceptibility prediction: influences of different study area scales and mapping unit scales F. Huang et al. 10.1007/s40789-024-00678-w
549. Landslide impacting factors and susceptibility assessment in part of the Purvanchal Himalayas using data mining approaches K. Khusulio & R. Kumar 10.1007/s12517-023-11719-0
550. Spatial autocorrelation modeling to assess geohazard susceptibility assessment in the mountainous Shennongjia area of China F. Zou et al. 10.1007/s12517-022-11032-2
551. Development of a framework for the prediction of slope stability using machine learning paradigms K. Rajan et al. 10.1007/s11069-024-06819-3
552. Rainfall-induced landslide (RFIL) disaster in Dima Hasao, Assam, Northeast India S. Das et al. 10.1007/s10346-022-01962-z
553. Catastrophic landslide triggered by extreme rainfall in Chongqing, China: July 13, 2020, Niuerwan landslide C. Zhou et al. 10.1007/s10346-022-01911-w
554. Insights into landslide susceptibility in different karst erosion landforms based on interpretable machine learning D. Sun et al. 10.1002/esp.5748
555. Characterization of the Fels Landslide (Alaska) Using Combined Terrestrial, Aerial, and Satellite Remote Sensing Data D. Donati et al. 10.3390/rs16010117
556. 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
557. Influence of spatial heterogeneity on landslide susceptibility in the transboundary area of the Himalayas H. Sun et al. 10.1016/j.geomorph.2023.108723
558. Failure mechanism and stability analysis of the landslide: a case study for open pit iron mine in Xichang, Sichuan, China C. Wang et al. 10.1007/s11069-022-05693-1
559. Seasonal Landslide Activity Lags Annual Precipitation Pattern in the Pacific Northwest L. Luna & O. Korup 10.1029/2022GL098506
560. An Optimization of Statistical Index Method Based on Gaussian Process Regression and GeoDetector, for Higher Accurate Landslide Susceptibility Modeling C. Cheng et al. 10.3390/app122010196
561. Insight into the dynamics of a long-runout mass movement using single-grain feldspar luminescence in the Pokhara Valley, Nepal A. de Boer et al. 10.5194/gchron-6-53-2024
562. Optimization of Turbulence Model Parameters Using the Global Search Method Combined with Machine Learning K. Barkalov et al. 10.3390/math10152708
563. Method to estimate the initial landslide failure surface and volumes using grid points and spline curves in MATLAB G. Prajapati & M. Jaboyedoff 10.1007/s10346-022-01940-5
564. Hazard assessment and mitigation of non-seismically fatal landslides in China F. Zhang et al. 10.1007/s11069-020-04491-x
565. Landslide susceptibility mapping along the China Pakistan Economic Corridor (CPEC) route using multi-criteria decision-making method A. Maqsoom et al. 10.1007/s40808-021-01226-0
566. Community perceptions of landslide risk and susceptibility: a multi-country study M. Bukhari et al. 10.1007/s10346-023-02027-5
567. Physical Model-Based Landslide Susceptibility Mapping of Himalayan Highways Considering the Coupled Effect of Rainfall and Earthquake S. Kumar & A. Sengupta 10.1061/NHREFO.NHENG-1997
568. A new method to compile global multi-hazard event sets J. Claassen et al. 10.1038/s41598-023-40400-5
569. Mitigation measures of debris flow and landslide risk carried out in two mountain areas of North-Eastern Italy R. Genevois et al. 10.1007/s11629-021-7212-6
570. Can global rainfall estimates (satellite and reanalysis) aid landslide hindcasting? U. Ozturk et al. 10.1007/s10346-021-01689-3
571. Shallow Landslide Susceptibility Mapping by Random Forest Base Classifier and Its Ensembles in a Semi-Arid Region of Iran V. Nhu et al. 10.3390/f11040421
572. Assessment of Landslide Risks Through a Multi-Disciplinary Approach: A Case Study of Al Hoceima, Northern Morocco M. El Khattabi et al. 10.20965/jdr.2023.p0424
573. Vulnerability of buildings to landslides: The state of the art and future needs H. Luo et al. 10.1016/j.earscirev.2023.104329
574. Potential of Documentary Evidence to Study Fatalities of Hydrological and Meteorological Events in the Czech Republic R. Brázdil et al. 10.3390/w11102014
575. Spatial distribution, temporal trends and impact of landslides on São Miguel Island from 1900 to 2020 based on an analysis of the Azores historical natural hazards database R. Silva et al. 10.1007/s11069-023-06296-0
576. Characterization of landslide displacements in an active fault zone in Northwest China X. Shi & X. Hu 10.1002/esp.5594
577. Incorporation of Satellite Precipitation Uncertainty in a Landslide Hazard Nowcasting System S. Hartke et al. 10.1175/JHM-D-19-0295.1
578. Critical assessment of landslide failure forecasting methods with case histories: a comparative study of INV, MINV, SLO, and VOA S. Sharifi et al. 10.1007/s10346-024-02237-5
579. Frekans Oranı Yöntemi Kullanılarak Arsuz Çayı Havzası Heyelan Duyarlılık Analizi S. Demirbilek & H. Turoğlu 10.46453/jader.1496249
580. Application of Empirical Approaches for Fast Landslide Hazard Management: The Case Study of Theilly (Italy) S. Segoni et al. 10.3390/w14213485
581. Stability analysis of reference station and compensation for monitoring stations in GNSS landslide monitoring D. Wang et al. 10.1186/s43020-023-00119-0
582. Landslide susceptibility mapping of Al Taif urban area, Saudi Arabia, using remote sensing data and microtremor measurements: integrated approach K. Abdelrahman et al. 10.3389/feart.2023.1270061
583. Generating landslide density heatmaps for rapid detection using open-access satellite radar data in Google Earth Engine A. Handwerger et al. 10.5194/nhess-22-753-2022
584. Application and interpretability of ensemble learning for landslide susceptibility mapping along the Three Gorges Reservoir area, China B. Liu et al. 10.1007/s11069-023-06374-3
585. Inventory and Spatial Distribution of Ancient Landslides in Hualong County, China Y. Huang et al. 10.3390/land12010136
586. Landslide Mapping From PlanetScope Images Using Improved Region-Based Level Set Evolution P. Lu et al. 10.1109/LGRS.2021.3122964
587. Airborne combined photogrammetry—infrared thermography applied to landslide remote monitoring V. Vivaldi et al. 10.1007/s10346-022-01970-z
588. Landslide susceptibility assessment of Kashmir Himalaya, India S. Zaz & S. Romshoo 10.1007/s12517-022-09699-8
589. 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
590. Disaster risk reduction and the limits of truisms: Improving the knowledge and practice interface D. Nohrstedt et al. 10.1016/j.ijdrr.2021.102661
591. Experimental investigation on anti-sliding performance of grouted micro-pipe pile groups X. Liu et al. 10.1007/s11069-022-05351-6
592. Displacement mechanisms of slow-moving landslides in response to changes in porewater pressure and dynamic stress J. Carey et al. 10.5194/esurf-7-707-2019
593. On the collision problem of simulant debris flow particles against concrete barriers of various strengths L. Luo & K. Senetakis 10.1007/s10064-024-03807-6
594. A review of recent studies on landslide hazard in Latin America A. Valdés Carrera et al. 10.1080/02723646.2021.1978372
595. Global detection of rainfall-triggered landslide clusters S. Benz & P. Blum 10.5194/nhess-19-1433-2019
596. Geospatial technologies for landslide monitoring: a case study of Sighetu Marmației, Romania T. Kalmar et al. 10.1007/s12665-024-11473-w
597. Pre-disaster adaptation strategies for houses in landslide-prone residential area, case study of Giripurno Village, Borobudur Sub-District, Central Java, Indonesia S. Purwitaningsih & J. Asano 10.1016/j.ijdrr.2023.104211
598. Probabilistic framework for quantifying human flight failure rate to landslides S. Wang et al. 10.1016/j.enggeo.2024.107723
599. Improving generalization performance of landslide susceptibility model considering spatial heterogeneity by using the geomorphic label-based LightGBM D. Sun et al. 10.1007/s10064-024-03859-8
600. Study of qualitative stability analysis and rainfall thresholds for possible landslide occurrence: a case study of Sikkim Himalaya K. Dutta et al. 10.1080/16583655.2021.1984701
601. Twelve‐Year Dynamics and Rainfall Thresholds for Alternating Creep and Rapid Movement of the Hooskanaden Landslide From Integrating InSAR, Pixel Offset Tracking, and Borehole and Hydrological Measurements Y. Xu et al. 10.1029/2020JF005640
602. Predicting Landslides Susceptible Zones in the Lesser Himalayas by Ensemble of Per Pixel and Object-Based Models U. Sur et al. 10.3390/rs14081953
603. Three-dimensional and long-term landslide displacement estimation by fusing C- and L-band SAR observations: A case study in Gongjue County, Tibet, China X. Liu et al. 10.1016/j.rse.2021.112745
604. Automated determination of landslide locations after large trigger events: advantages and disadvantages compared to manual mapping D. Milledge et al. 10.5194/nhess-22-481-2022
605. Application of Machine Learning on Google Earth Engine to Produce Landslide Susceptibility Mapping (Case Study: Pacitan) H. Ilmy et al. 10.1088/1755-1315/731/1/012028
606. Rainfall-Induced Landslides from Initialization to Post-Failure Flows: Stochastic Analysis with Machine Learning H. Xu et al. 10.3390/math10234426
607. Deformation evolution of landslides induced by coal mining in mountainous areas: case study of the Madaling landslide, Guizhou, China Q. Lai et al. 10.1007/s10346-023-02069-9
608. Human Vulnerability to Landslides W. Pollock & J. Wartman 10.1029/2020GH000287
609. Risk assessment of chemical release accident triggered by landslide using Bayesian network N. Moriguchi et al. 10.1016/j.scitotenv.2023.164321
610. Growth of Debris Flows by Soil Bed Erosion: Effects of Frictional and Hydrodynamic Shear Stresses P. Song et al. 10.1051/e3sconf/202341502021
611. Evaluation of a Tilt-Based Monitoring System for Rainfall-Induced Landslides: Development and Physical Modelling A. Paswan & A. Shrivastava 10.3390/w15101862
612. Sudden Slide Mechanism of a Rock Block in Road Cutting Slope with Soft and Hard Interlayered Bedding Structure Based on Energy Balance Theory F. Zhou et al. 10.1007/s12205-022-0749-2
613. Landslide susceptibility mapping using hybrid random forest with GeoDetector and RFE for factor optimization X. Zhou et al. 10.1016/j.gsf.2021.101211
614. Class A prediction of debris flow impact forces on dual rigid and flexible barriers: MPM modelling S. Cuomo et al. 10.1016/j.compgeo.2024.106556
615. Historical Landslide Fatalities in British Columbia, Canada: Trends and Implications for Risk Management A. Strouth & S. McDougall 10.3389/feart.2021.606854
616. Using principal component analysis to incorporate multi-layer soil moisture information in hydrometeorological thresholds for landslide prediction: an investigation based on ERA5-Land reanalysis data N. Palazzolo et al. 10.5194/nhess-23-279-2023
617. Temporal Variations in Landslide Distributions Following Extreme Events: Implications for Landslide Susceptibility Modeling J. Jones et al. 10.1029/2021JF006067
618. A Landslide Susceptibility Assessment Method Based on GIS Technology and an AHP-Weighted Information Content Method: A Case Study of Southern Anhui, China H. He et al. 10.3390/ijgi8060266
619. Spatial and temporal patterns and the socioeconomic impacts of landslides in the tropical and mountainous Colombian Andes E. Aristizábal & O. Sánchez 10.1111/disa.12391
620. Livelihood, irrigation, and landslide: Unfolding the human-water-land nexus using an integrative framework J. Wang et al. 10.1016/j.landusepol.2024.107190
621. Refined and dynamic susceptibility assessment of landslides using InSAR and machine learning models Y. Wei et al. 10.1016/j.gsf.2024.101890
622. A national rockfall dataset as a tool for analysing the spatial and temporal rockfall occurrence in Germany S. Rupp & B. Damm 10.1002/esp.4827
623. Field and Numerical Investigation of Taihu Resort Cut Slope Failure in Suzhou, China A. Raouf et al. 10.3390/app14072683
624. Failure and disaster-causing mechanism of a typhoon-induced large landslide in Yongjia, Zhejiang, China Y. Zhuang et al. 10.1007/s10346-023-02099-3
625. Geographical landslide early warning systems F. Guzzetti et al. 10.1016/j.earscirev.2019.102973
626. Resettlement preferences from landslide prone areas in Cameroon: Willingness to move, reasons to stay M. Baert et al. 10.1016/j.landusepol.2019.04.036
627. Improved phase gradient stacking for landslide detection D. Zhang et al. 10.1007/s10346-024-02263-3
628. Characteristics of landslide path dependency revealed through multiple resolution landslide inventories in the Nepal Himalaya S. Roberts et al. 10.1016/j.geomorph.2021.107868
629. Geological education scenario in India and role of open educational resources in the light of COVID-19 pandemic O. Verma et al. 10.15446/esrj.v26n3.96209
630. Landslide Susceptibility Assessment Tools v1.0.0b – Project Manager Suite: a new modular toolkit for landslide susceptibility assessment J. Torizin et al. 10.5194/gmd-15-2791-2022
631. Estimates of three-dimensional rupture surface geometry of deep-seated landslides using landslide inventories and high-resolution topographic data M. Bunn et al. 10.1016/j.geomorph.2020.107332
632. Automatic calculation of rainfall thresholds for landslide occurrence in Chukha Dzongkhag, Bhutan S. Gariano et al. 10.1007/s10064-018-1415-2
633. Rainfall-Induced or Lake-Water-Level-Controlled Landslide? An Example from the Steep Slopes of Lake Balaton, Hungary F. Nagy-Göde & Á. Török 10.3390/w14071169
634. Effects of flow-bed interactions on barrier impact W. De Silva et al. 10.1051/e3sconf/202341501005
635. The State of Remote Sensing Capabilities of Cascading Hazards Over High Mountain Asia D. Kirschbaum et al. 10.3389/feart.2019.00197
636. IoT-Driven Microseismic Sensing System and Monitoring Platform for Landslide Detection P. Indukala et al. 10.1109/ACCESS.2024.3427386
637. High resolution landslide susceptibility mapping using ensemble machine learning and geospatial big data N. Sharma et al. 10.1016/j.catena.2023.107653
638. Ground subsidence in Dar village (Darma valley), Pithoragarh district, Kumaun Himalaya, India: A Himalayan disaster in waiting B. Ram et al. 10.1007/s12040-023-02244-5
639. Negative Poisson’s ratio and peripheral strain of an NPR anchor cable Z. Tao et al. 10.1007/s11629-022-7426-2
640. Landslide Mapping Using Multilevel-Feature-Enhancement Change Detection Network L. Wang et al. 10.1109/JSTARS.2023.3245062
641. An investigation of the combined effect of rainfall and road cut on landsliding S. Pradhan et al. 10.1016/j.enggeo.2022.106787
642. Landslide Fatality Occurrence: A Systematic Review of Research Published between January 2010 and March 2022 O. Petrucci 10.3390/su14159346
643. Landslide mapping with remote sensing: challenges and opportunities C. Zhong et al. 10.1080/01431161.2019.1672904
644. Timing landslide and flash flood events from SAR satellite: a regionally applicable methodology illustrated in African cloud-covered tropical environments A. Deijns et al. 10.5194/nhess-22-3679-2022
645. Modified “Rockfall Hazard Rating System for Pakistan (RHRSP)”: An Application for Hazard and Risk Assessment along the Karakoram Highway, Northwest Pakistan J. Tanoli et al. 10.3390/app12083778
646. Widespread Initiation, Reactivation, and Acceleration of Landslides in the Northern California Coast Ranges due to Extreme Rainfall A. Handwerger et al. 10.1029/2019JF005035
647. Changes in the factors contributing to the reduction of landslide fatalities between 1945 and 2019 in Japan Y. Shinohara & T. Kume 10.1016/j.scitotenv.2022.154392
648. A GIS-based factor clustering and landslide susceptibility analysis using AHP for Gish River Basin, India T. Basu & S. Pal 10.1007/s10668-019-00406-4
649. Distribution law and susceptibility of geohazards across a gradient belt of the Western Sichuan Plateau T. Li et al. 10.1007/s11629-023-8290-4
650. Assessing the impact of governance policies on landslide risk in Brazilian municipalities V. Gonçalves Sales 10.1016/j.ijdrr.2023.104058
651. Monitoring Slope Movement and Soil Hydrologic Behavior Using IoT and AI Technologies: A Systematic Review M. Alam et al. 10.3390/hydrology11080111
652. High-Resolution Soil-Moisture Maps Over Landslide Regions in Northern California Grassland Derived From SAR Backscattering Coefficients T. Liao et al. 10.1109/JSTARS.2021.3069010
653. Rainfall Threshold Estimation and Landslide Forecasting for Kalimpong, India Using SIGMA Model M. Abraham et al. 10.3390/w12041195
654. Future changes of socioeconomic exposure to potential landslide hazards over mainland China D. Li et al. 10.1016/j.wace.2024.100731
655. Co-seismic landslide detection after M 7.4 earthquake on June 23, 2020, in Oaxaca, Mexico, based on rapid mapping method using high and medium resolution synthetic aperture radar (SAR) images N. Hernandez et al. 10.1007/s10346-021-01735-0
656. Spatial Landslide Risk Assessment at Phuentsholing, Bhutan A. Dikshit et al. 10.3390/geosciences10040131
657. Prediction of rainfall-induced landslide using machine learning models along highway Bandipora to Gurez road, India A. Nanda et al. 10.1007/s11069-024-06405-7
658. Forecasting Landslides Using Mobility Functions: A Case Study from Idukki District, India M. Abraham et al. 10.1007/s40098-020-00490-8
659. Introducing a novel multi-layer perceptron network based on stochastic gradient descent optimized by a meta-heuristic algorithm for landslide susceptibility mapping H. Hong et al. 10.1016/j.scitotenv.2020.140549
660. Heterogeneous transfer learning considering feature representation and environmental consistency for landslide spatial prediction Z. Zhao et al. 10.1080/15481603.2024.2349343
661. 滑坡运动路径复杂度研究：综述与展望 L. Li & H. Lan 10.3799/dqkx.2021.224
662. UAV, GNSS, and GIS for the Rapid Assessment of Multi-Occurrence Landslides K. Nikolakopoulos et al. 10.3390/geosciences14060160
663. A multi‐sensor evaluation of precipitation uncertainty for landslide‐triggering storm events E. Culler et al. 10.1002/hyp.14260
664. Dynamics of pore water pressure at the soil–bedrock interface recorded during a rainfall-induced shallow landslide in a steep natural forested headwater catchment, Taiwan W. Liang 10.1016/j.jhydrol.2020.125003
665. Review article: Natural hazard risk assessments at the global scale P. Ward et al. 10.5194/nhess-20-1069-2020
666. An ensemble approach of bi-variate statistical models with soft-computing techniques for GIS-based landslide susceptibility zonation in the Kalimpong region of Darjeeling Himalaya, India S. Das et al. 10.1007/s10668-024-04592-8
667. A comparative study of regional landslide susceptibility mapping with multiple machine learning models Y. Wang et al. 10.1002/gj.4902
668. Landslide Susceptibility mapping using random forest and extreme gradient boosting: A case study of Fengjie, Chongqing W. Zhang et al. 10.1002/gj.4683
669. Dry Spells and Extreme Precipitation are The Main Trigger of Landslides in Central Europe R. Tichavský et al. 10.1038/s41598-019-51148-2
670. Landslide susceptibility prediction based on landform predisposing indexes − An example from the Beiluo River Basin F. Liu et al. 10.1016/j.asr.2024.08.003
671. Landslide monitoring using seismic ambient noise correlation: challenges and applications M. Le Breton et al. 10.1016/j.earscirev.2021.103518
672. Landslides associated with recent road constructions in the Río Lucma catchment, eastern Cordillera Blanca, Peru A. EMMER et al. 10.1590/0001-3765202220211352
673. Failure mechanism and kinetic feature of a high locality landslide at Qingliu Village, Li County, China, 2020 L. Li et al. 10.1007/s10346-024-02236-6
674. A global perspective on a bioengineering approach to landslide mitigation using bamboo diversity S. Maddalwar et al. 10.1016/j.bamboo.2024.100093
675. Slope deformation monitoring and early identification of disasters in debris flow source area of Baini River, Dongchuan District, China X. Zhang et al. 10.3389/feart.2022.1000736
676. Land use and land cover as a conditioning factor in landslide susceptibility: a literature review R. Pacheco Quevedo et al. 10.1007/s10346-022-02020-4
677. Spatial Non-Stationarity-Based Landslide Susceptibility Assessment Using PCAMGWR Model Y. Li et al. 10.3390/w14060881
678. Deep learning and benchmark machine learning based landslide susceptibility investigation, Garhwal Himalaya (India) S. Saha et al. 10.1016/j.qsa.2023.100075
679. Numerical simulation of Submarine non-rigid landslide by an explicit three-step incompressible smoothed particle hydrodynamics S. Hosseini Mobara et al. 10.1016/j.enganabound.2021.05.025
680. Türkiye’de ölümcül heyelanların dağılım karakteristikleri ve ulusal ölçekte öncelikli alanların belirlenmesi S. FİDAN & T. GÖRÜM 10.17211/tcd.731596
681. Using Field-Based Monitoring to Enhance the Performance of Rainfall Thresholds for Landslide Warning M. Abraham et al. 10.3390/w12123453
682. A Comparative Assessment of Machine Learning Models for Landslide Susceptibility Mapping in the Rugged Terrain of Northern Pakistan N. Shahzad et al. 10.3390/app12052280
683. Landslides triggered by an extraordinary rainfall event in Central Italy on September 15, 2022 M. Donnini et al. 10.1007/s10346-023-02109-4
684. Rapid Mapping of Landslides Induced by Heavy Rainfall in the Emilia-Romagna (Italy) Region in May 2023 M. Ferrario & F. Livio 10.3390/rs16010122
685. The ITAlian rainfall-induced LandslIdes CAtalogue, an extensive and accurate spatio-temporal catalogue of rainfall-induced landslides in Italy S. Peruccacci et al. 10.5194/essd-15-2863-2023
686. Spatial distributions and multi-factor driving mechanism of landslide in southern Liaodong Peninsula Y. Li et al. 10.3389/fevo.2023.1339265
687. Impact and a Novel Representation of Spatial Data Uncertainty in Debris Flow Susceptibility Analysis L. Kurilla & G. Fubelli 10.3390/app12136697
688. Could road constructions be more hazardous than an earthquake in terms of mass movement? H. Tanyaş et al. 10.1007/s11069-021-05199-2
689. Landslide susceptibility zonation using integrated supervised and unsupervised machine learning techniques in the Bhagirathi Eco-Sensitive Zone (BESZ), Uttarakhand, Himalaya, India M. Devi et al. 10.1007/s12040-024-02344-w
690. Mechanistic insights from emergent landslides in physical experiments O. Beaulieu et al. 10.1130/G47875.1
691. Kinematics of Irrigation‐Induced Landslides in a Washington Desert: Impacts of Basal Geometry Y. Xu et al. 10.1029/2021JF006355
692. Landslide detection, monitoring and prediction with remote-sensing techniques N. Casagli et al. 10.1038/s43017-022-00373-x
693. The Role of Citrus Groves in Rainfall-Triggered Landslide Hazards in Uwajima, Japan N. Lusiana & Y. Shinohara 10.3390/w14132113
694. Landslide causative factors evaluation using GIS in the tectonically active Glafkos River area, northwestern Peloponnese, Greece G. Bathrellos et al. 10.1016/j.geomorph.2024.109285
695. IoT-Based Geotechnical Monitoring of Unstable Slopes for Landslide Early Warning in the Darjeeling Himalayas M. Abraham et al. 10.3390/s20092611
696. Spatiotemporal analysis of ecological vulnerability along Bangladesh-China-India-Myanmar economic corridor through a grid level prototype model Y. Jin et al. 10.1016/j.ecolind.2020.106933
697. Constructing a Large-Scale Landslide Database Across Heterogeneous Environments Using Task-Specific Model Updates S. Nagendra et al. 10.1109/JSTARS.2022.3177025
698. Monitoring Seasonal Movement Characteristics of the Landslide Based on Time-Series InSAR Technology: The Cheyiping Landslide Case Study, China Y. Gou et al. 10.3390/rs15010051
699. Aplicação do índice estatístico e análise multicritério no mapeamento da suscetibilidade a deslizamentos, no município do Ipojuca, Pernambuco, Brasil C. Duarte et al. 10.26848/rbgf.v17.2.p1015-1037
700. Recognition of Landslide Triggering Mechanisms and Dynamics Using GNSS, UAV Photogrammetry and In Situ Monitoring Data T. Peternel et al. 10.3390/rs14143277
701. GIS-based modeling of landslide susceptibility zonation by integrating the frequency ratio and objective–subjective weighting approach: a case study in a tropical monsoon climate region P. Hoa et al. 10.3389/fenvs.2023.1175567
702. Delineating Non-Susceptible Landslide Areas in China Based on Topographic Index and Quantile Non-Linear Model S. Ma et al. 10.3390/f15040678
703. A geotechnical approach to compare different slope stabilization techniques for failed slope in the Darjeeling hills, India A. Chawla et al. 10.1007/s12665-023-11054-3
704. Mitigation and management of rainfall induced rockslides along the national highways of Himalayan region, India P. C et al. 10.1080/19475705.2021.1928772
705. Long-term analysis of rainfall-induced landslides in Umbria, central Italy S. Gariano et al. 10.1007/s11069-021-04539-6
706. Developing landslide hazard scenario using the historical events for the Kashmir Himalaya B. Shah et al. 10.1007/s11069-022-05542-1
707. Benchmarking Physical Model Experiments with Numerical Simulations for the Wangjiashan Landslide-Induced Surge Waves in the Baihetan Reservoir Area A. Shi et al. 10.3390/w16131930
708. Towards an understanding of landslide risk assessment and its economic losses: a scientometric analysis N. Marín-Rodríguez et al. 10.1007/s10346-024-02272-2
709. Landslide vulnerability assessment based on entropy method: a case study from Kegalle district, Sri Lanka E. Perera et al. 10.1007/s40808-019-00615-w
710. Using distributed root soil moisture data to enhance the performance of rainfall thresholds for landslide warning Y. Guo et al. 10.1007/s11069-022-05588-1
711. Exploring the Potential of Native Urease-Producing Bacteria of Hilly Terrain for Soil Strength Enhancement R. Devrani et al. 10.1080/01490451.2024.2388823
712. Geospatial landslide inventory of India—an insight into occurrence and exposure on a national scale T. Martha et al. 10.1007/s10346-021-01645-1
713. Complex and Cascading Triggering of Submarine Landslides and Turbidity Currents at Volcanic Islands Revealed From Integration of High-Resolution Onshore and Offshore Surveys M. Clare et al. 10.3389/feart.2018.00223
714. Landslide Mapping and Susceptibility Assessment Using Geospatial Analysis and Earth Observation Data E. Psomiadis et al. 10.3390/land9050133
715. A Novel Decomposition-Ensemble Learning Model Based on Ensemble Empirical Mode Decomposition and Recurrent Neural Network for Landslide Displacement Prediction X. Niu et al. 10.3390/app11104684
716. InSAR-derived predisaster spatio-temporal evolution of a reactivated landslide K. He et al. 10.1007/s10064-024-03661-6
717. SkySlide: A Hybrid Method for Landslide Susceptibility Assessment based on Landslide-Occurring Data Only A. Mutlu & F. Goz 10.1093/comjnl/bxaa063
718. Numerical investigation of landslide kinetics for the recent Mabian landslide (Sichuan, China) J. Wei et al. 10.1007/s10346-019-01237-0
719. Deformation and Failure Process of Slope Caused by Underground Mining: A Case Study of Pusa Collapse in Nayong County, Guizhou Province, China S. Xiong et al. 10.1155/2022/1592703
720. Twisting Theory: A New Artificial Adaptive System for Landslide Prediction P. Buscema et al. 10.3390/geosciences13040115
721. Displacement prediction of landslides at slope-scale: Review of physics-based and data-driven approaches W. Gong et al. 10.1016/j.earscirev.2024.104948
722. DebrisFlow Predictor: an agent-based runout program for shallow landslides R. Guthrie & A. Befus 10.5194/nhess-21-1029-2021
723. Assessment Of Temporal Variability In The Level Of Population Vulnerability To Natural And Man-Made Hazards (The Case Of Moscow Districts) R. Babkin et al. 10.24057/2071-9388-2022-116
724. Stability Prediction of Rainfall-Induced Shallow Landslides: A Case Study of Mountainous Area in China K. Song et al. 10.3390/w15162938
725. Transfer learning for landslide susceptibility modeling using domain adaptation and case-based reasoning Z. Wang et al. 10.5194/gmd-15-8765-2022
726. Biotech Crops, Input Use and Landslides Case Study of Herbicide Tolerant Corn in the Philippine Highlands L. Bequet 10.1016/j.ecolecon.2020.106773
727. Quantitative Land-Use and Landslide Assessment: A Case Study in Rize, Türkiye N. Kasahara et al. 10.3390/w14111811
728. Geomorphic evaluation of landslides along the Teesta river valley, Sikkim Himalaya, India V. Gupta et al. 10.1002/gj.4377
729. Evaluating the performances of satellite-based rainfall data for global rainfall-induced landslide warnings G. Jia et al. 10.1007/s10346-019-01277-6
730. Influence of the mapping unit for regional landslide early warning systems: comparison between pixels and polygons in Catalonia (NE Spain) R. Palau et al. 10.1007/s10346-020-01425-3
731. Large-scale field test on deformation mechanism and stability enhancement of soil slope reinforced by the micro-NPR bolt W. Dai et al. 10.1007/s12665-024-11434-3
732. Assessing damage data availability in national landslide databases for SFDRR reporting: a case study of Kuala Lumpur as a local-level application T. Bhuiyan et al. 10.1007/s10346-023-02085-9
733. An Integrated Approach of Machine Learning, Remote Sensing, and GIS Data for the Landslide Susceptibility Mapping I. Ullah et al. 10.3390/land11081265
734. Spatiotemporal deformation characteristics of Outang landslide and identification of triggering factors using data mining B. Yang et al. 10.1016/j.jrmge.2023.09.030
735. Classification of Landslide Activity on a Regional Scale Using Persistent Scatterer Interferometry at the Moselle Valley (Germany) A. Kalia 10.3390/rs10121880
736. Multi-Level Data Analyses for Characterizing Rainfall-Induced Landslide Scenarios: The Example of Catanzaro Municipality (South Italy) O. Petrucci et al. 10.3390/w15132437
737. Prevention of Mountain Disasters and Maintenance of Residential Area through Real-Time Terrain Rendering S. Sung et al. 10.3390/su13052950
738. Exploring Shallow Geological Structures in Landslides Using the Semi-Airborne Transient Electromagnetic Method J. Wu et al. 10.3390/rs16173186
739. Deformation and failure analysis of heterogeneous slope using nonlinear spatial probabilistic finite element method P. Garg et al. 10.3934/math.20241283
740. Global debris flow susceptibility based on a comparative analysis of a single global model versus a continent-by-continent approach L. Kurilla & G. Fubelli 10.1007/s11069-022-05313-y
741. Rainfall affected stability analysis of Maddingley Brown Coal eastern batter using Plaxis 3D L. Zhao & G. You 10.1007/s12517-020-06038-7
742. InSAR-Based Active Landslide Detection and Characterization Along the Upper Reaches of the Yellow River J. Du et al. 10.1109/JSTARS.2023.3263003
743. A numerical study on the effects of particle size distribution on run-out distance of granular flow D. Watanabe et al. 10.1016/j.sandf.2022.101242
744. A new algorithm for landslide dynamic monitoring with high temporal resolution by Kalman filter integration of multiplatform time-series InSAR processing J. Cai et al. 10.1016/j.jag.2022.102812
745. Quantifying the Effect of Precipitation on Landslide Hazard in Urbanized and Non‐Urbanized Areas E. Johnston et al. 10.1029/2021GL094038
746. Performance Evaluation of Long NDVI Timeseries from AVHRR, MODIS and Landsat Sensors over Landslide-Prone Locations in Qinghai-Tibetan Plateau P. Sajadi et al. 10.3390/rs13163172
747. Landslide dynamic hazard prediction based on precipitation variation trend and backpropagation neural network R. Huang et al. 10.1080/10106049.2024.2322058
748. Threshold assessment of rainfall-induced landslides in Sangzhi County: statistical analysis and physical model Y. Sheng et al. 10.1007/s10064-022-02890-x
749. Composite Anchors for Slope Stabilisation: Monitoring of their In-Situ Behaviour with Optical Fibre S. Cola et al. 10.3390/geosciences9050240
750. A Stochastic Dynamical Model of Slope Creep and Failure Q. Lei & D. Sornette 10.1029/2022GL102587
751. What ecological factors to integrate in landslide susceptibility mapping? An exploratory review of current trends in support of eco-DRR M. Broquet et al. 10.1016/j.pdisas.2024.100328
752. Updating Inventory, Deformation, and Development Characteristics of Landslides in Hunza Valley, NW Karakoram, Pakistan by SBAS-InSAR X. Su et al. 10.3390/rs14194907
753. Developing a landslide vulnerability assessment for the national road network in Laos G. Hearn & P. Pongpanya 10.1144/qjegh2020-110
754. Using DInSAR to inventory landslide geological disaster in Bijie, Guizhou, China C. Shen et al. 10.3389/feart.2022.1024710
755. Landslide Hazard Assessment Method Considering the Deformation Factor: A Case Study of Zhouqu, Gansu Province, Northwest China C. Dai et al. 10.3390/rs15030596
756. Different Approaches to Use Morphometric Attributes in Landslide Susceptibility Mapping Based on Meso-Scale Spatial Units: A Case Study in Rio de Janeiro (Brazil) V. Canavesi et al. 10.3390/rs12111826
757. A community-operated landslide early warning approach: Myanmar case study N. Dixon et al. 10.1186/s40677-022-00220-7
758. The Anomalously Old Bush Stream Rock Avalanche and Its Implications for Landslide Inventories in Dynamic Landscapes S. McColl 10.3389/feart.2020.00103
759. Landslide susceptibility modelling in the Doda Kishtwar Ramban (DKR) region of Jammu and Kashmir using Remote Sensing and Geographic Information System A. Taloor et al. 10.1016/j.qsa.2024.100189
760. How climate change and unplanned urban sprawl bring more landslides U. Ozturk et al. 10.1038/d41586-022-02141-9
761. Development and assessment of a novel hybrid machine learning-based landslide susceptibility mapping model in the Darjeeling Himalayas A. Saha et al. 10.1007/s00477-023-02528-8
762. An Investigation of Landslide Susceptibility Using Logistic Regression and Statistical Index Methods in Dailekh District, Nepal D. Rai et al. 10.1007/s11769-022-1304-2
763. Dynamic fragmentation of intact rock blocks and its influence on mobility: insights from discrete element analysis Z. Liu et al. 10.1007/s10346-024-02349-y
764. Economic landslide susceptibility under a socio-economic perspective: an application to Umbria Region (Central Italy) M. Donnini et al. 10.1007/s10037-020-00143-6
765. Predicting and Understanding Landslide Events With Explainable AI E. Collini et al. 10.1109/ACCESS.2022.3158328
766. Impact of sampling for landslide susceptibility assessment using interpretable machine learning models B. Wu et al. 10.1007/s10064-024-03980-8
767. A global landslide non-susceptibility map G. Jia et al. 10.1016/j.geomorph.2021.107804
768. Long-term landslide impacts and adaptive responses in rural communities: Using historical cases to validate the cumulative causation approach P. Raška et al. 10.1016/j.ijdrr.2023.103748
769. Landslide Displacement Prediction Based on Time Series and PSO-BP Model in Three Georges Reservoir, China D. Gao et al. 10.1007/s12583-021-1575-z
770. An optimization-based discrete element model for dry granular flows: Application to granular collapse on erodible beds H. Martin et al. 10.1016/j.jcp.2023.112665
771. Systematic assessment of GPM IMERG V06 precipitation products with dense rain gauge observations over Zhejiang Province, China Z. Bi et al. 10.1002/joc.7838
772. Assessing uncertainties in landslide susceptibility predictions in a changing environment (Styrian Basin, Austria) R. Knevels et al. 10.5194/nhess-23-205-2023
773. Assessing the risk of slope failure to highway infrastructure using automated time-lapse electrical resistivity tomography monitoring J. Whiteley et al. 10.1016/j.trgeo.2023.101129
774. Analysis of landslide-induced fatalities and injuries in Bangladesh: 2000-2018 N. Sultana & S. Ricart Casadevall 10.1080/23311886.2020.1737402
775. Early prediction framework for a rainfall-induced landslide: validation through a real case study P. Sudani & K. Patil 10.1007/s12046-023-02242-9
776. A comparative evaluation of landslide susceptibility mapping using machine learning-based methods in Bogor area of Indonesia D. Melati et al. 10.1007/s12665-023-11402-3
777. Landslide hazard assessment and mapping at national scale for Malawi Y. Thiery et al. 10.1016/j.jafrearsci.2024.105187
778. Landslide susceptibility mapping with GIS in high mountain area of Nepal: a comparison of four methods P. Gautam et al. 10.1007/s12665-021-09650-2
779. Probabilistic simulation of entire process of rainfall-induced landslides using random finite element and material point methods with hydro-mechanical coupling X. Liu & Y. Wang 10.1016/j.compgeo.2020.103989
780. Assessment and mapping of landslides in steep mountainous terrain using PS-InSAR: A case study of Karimabad Valley in Chitral M. Ahmad et al. 10.1016/j.kjs.2023.09.007
781. SLEM (Shallow Landslide Express Model): A Simplified Geo-Hydrological Model for Powerlines Geo-Hazard Assessment A. Abbate & L. Mancusi 10.3390/w16111507
782. Shallow Landslide Susceptibility Mapping: A Comparison between Logistic Model Tree, Logistic Regression, Naïve Bayes Tree, Artificial Neural Network, and Support Vector Machine Algorithms V. Nhu et al. 10.3390/ijerph17082749
783. 3D simulation of Vajont disaster. Part 1: Numerical formulation and validation A. Franci et al. 10.1016/j.enggeo.2020.105854
784. The optimal rainfall thresholds and probabilistic rainfall conditions for a landslide early warning system for Chuncheon, Republic of Korea W. Lee et al. 10.1007/s10346-020-01603-3
785. Reanalysis of Soil Moisture Used for Rainfall Thresholds for Rainfall-Induced Landslides: The Italian Case Study N. Bezak et al. 10.3390/w13141977
786. Deep convolutional neural networks with Bee Collecting Pollen Algorithm (BCPA)-based landslide data balancing and spatial prediction J. Aruna Jasmine & C. Heltin Genitha 10.3233/JIFS-234924
787. Landslide risk assessment in mining areas using hybrid machine learning methods under fuzzy environment L. Dong et al. 10.1016/j.ecolind.2024.112736
788. Landslide susceptibility modeling by interpretable neural network K. Youssef et al. 10.1038/s43247-023-00806-5
789. The role of plants in the prevention of soil-slip: the G-SLIP model and its application on territorial scale through G-XSLIP platform L. Montrasio et al. 10.1007/s10346-023-02031-9
790. A Thermo-Poro-Mechanics Model Predicts the Transition from Creep to Rapid Movement of Large Landslides H. Zhang et al. 10.1007/s00603-024-03980-w
791. Landslide Distribution and Development Characteristics in the Beiluo River Basin F. Liu et al. 10.3390/land13071038
792. Risk at the margins: A natural hazards perspective on the Syrian refugee crisis in Lebanon W. Pollock et al. 10.1016/j.ijdrr.2018.11.026
793. Revealing the relation between spatial patterns of rainfall return levels and landslide density S. Mtibaa & H. Tsunetaka 10.5194/esurf-11-461-2023
794. A methodology for road cutting design guidelines based on field observations E. Robson et al. 10.1016/j.enggeo.2022.106771
795. Landslide susceptibility mapping in the Loess Plateau of northwest China using three data-driven techniques-a case study from middle Yellow River catchment Z. Guo et al. 10.3389/feart.2022.1033085
796. Revealing the Importance of Capillary and Collisional Stresses on Soil Bed Erosion Induced by Debris Flows P. Song & C. Choi 10.1029/2020JF005930
797. Rainfall Induced Shallow Landslide Temporal Probability Modelling and Early Warning Research in Mountains Areas: A Case Study of Qin-Ba Mountains, Western China Y. Song et al. 10.3390/rs14235952
798. Global Landslide Forecasting System for Hazard Assessment and Situational Awareness S. Khan et al. 10.3389/feart.2022.878996
799. Landslide activity detection based on Sentinel-1 PSI datasets of the Ground Motion Service Germany—the Trittenheim case study A. Kalia 10.1007/s10346-022-01958-9
800. Optimization of rainfall thresholds for landslide early warning through false alarm reduction and a multi-source validation N. Nocentini et al. 10.1007/s10346-023-02176-7
801. Consequences of slope instability and existing practices of mitigation in hydropower projects of Nepal S. Regmi & R. Dahal 10.1186/s40677-024-00289-2
802. A hybrid ensemble-based deep-learning framework for landslide susceptibility mapping L. Lv et al. 10.1016/j.jag.2022.102713
803. 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
804. The Hooskanaden Landslide: historic and recent surge behavior of an active earthflow on the Oregon Coast S. Alberti et al. 10.1007/s10346-020-01466-8
805. Spatio-temporal variability of monsoon precipitation and their effect on precipitation triggered landslides in relation to relief in Himalayas R. Kashyap et al. 10.1007/s41324-021-00392-8
806. National-scale data-driven rainfall induced landslide susceptibility mapping for China by accounting for incomplete landslide data Q. Lin et al. 10.1016/j.gsf.2021.101248
807. An Index for Snowmelt-Induced Landslide Prediction for Zavoj Lake, Serbia R. Marković et al. 10.3390/atmos15030256
808. Effects of improper emergency mitigations on a large-scale landslide triggered by road excavation: A case study of the Fengping landslide, Hubei province, China Y. Luo et al. 10.1007/s10064-024-03725-7
809. Coupling RBF neural network with ensemble learning techniques for landslide susceptibility mapping B. Pham et al. 10.1016/j.catena.2020.104805
810. A GIS-based Spatial Prediction of Landslide Hazard Zones and Mapping in an Eastern Himalayan Hilly Region Using Large Scale Soil Mapping and Analytical Hierarchy Process R. Srinivasan et al. 10.1007/s12524-022-01579-8
811. Global Assessment of the Capability of Satellite Precipitation Products to Retrieve Landslide-Triggering Extreme Rainfall Events O. Marc et al. 10.1175/EI-D-21-0022.1
812. A Virtual Reality Simulation of a Real Landslide for Education and Training: Case of Chiradzulu, Malawi, 2023 Landslide A. Asgary et al. 10.3390/geohazards5030032
813. The Geomorphic Effectiveness of Landslides E. Dente et al. 10.1029/2023JF007191
814. A reliability evaluation of four landslide failure forecasting methods in real-time monitoring applications S. Sharifi et al. 10.1007/s10346-024-02293-x
815. InSAR Study of Landslides: Early Detection, Three-Dimensional, and Long-Term Surface Displacement Estimation—A Case of Xiaojiang River Basin, China H. Jia et al. 10.3390/rs14071759
816. InSAR Displacement with High-Resolution Optical Remote Sensing for the Early Detection and Deformation Analysis of Active Landslides in the Upper Yellow River K. Tu et al. 10.3390/w15040769
817. Simulation des écoulements gravitaires avec les modèles d’écoulement en couche mince : état de l’art et exemple d’application aux coulées de débris de la Rivière du Prêcheur (Martinique, Petites Antilles) M. Peruzzetto et al. 10.1051/geotech/2023020
818. Learnings from rapid response efforts to remotely detect landslides triggered by the August 2021 Nippes earthquake and Tropical Storm Grace in Haiti P. Amatya et al. 10.1007/s11069-023-06096-6
819. Spatial variation in the frequency and magnitude of mass movement in a semiarid, complex‐terrain agricultural watershed on the Loess Plateau of China T. Zhu et al. 10.1002/ldr.3296
820. Quantifying effects of changes in forest age distribution on the landslide frequency in Japan N. Lusiana et al. 10.1007/s11069-024-06537-w
821. Study on the Progress in Climate-Change-Oriented Human Settlement Research Q. Yao et al. 10.3390/su15075733
822. Centrifuge model tests of h-type anti-slide pile reinforced slope under different rainfall duration H. Zhang et al. 10.1080/19648189.2024.2338771
823. InSAR-based detection method for mapping and monitoring slow-moving landslides in remote regions with steep and mountainous terrain: An application to Nepal D. Bekaert et al. 10.1016/j.rse.2020.111983
824. Non-Structural Landslide Risk Mitigation: Schemes, Application and Case Studies T. Chauhan et al. 10.1007/s40098-024-00996-5
825. Multi-dimensional and long-term time series monitoring and early warning of landslide hazard with improved cross-platform SAR offset tracking method Y. Yin et al. 10.1007/s11431-021-2008-6
826. Time capsule for landslide risk assessment Y. Lei et al. 10.1080/17499518.2023.2164899
827. A Semiautomatic Pixel-Object Method for Detecting Landslides Using Multitemporal ALOS-2 Intensity Images B. Adriano et al. 10.3390/rs12030561
828. An integrated approach for landslide susceptibility–vulnerability–risk assessment of building infrastructures in hilly regions of India A. Singh et al. 10.1007/s10668-020-00804-z
829. Slope-Unit Scale Landslide Susceptibility Mapping Based on the Random Forest Model in Deep Valley Areas H. Deng et al. 10.3390/rs14174245
830. Using historical data for developing a hazard and disaster profile of the Kashmir valley for the period 1900–2020 N. Ali et al. 10.1007/s11069-022-05440-6
831. Towards A Geo-Hydro-Mechanical Characterization of Landslide Classes: Preliminary Results F. Cotecchia et al. 10.3390/app10227960
832. Perceptions of landslide risks and warnings in Hong Kong M. Yik et al. 10.1007/s10346-022-02021-3
833. Application of statistical probabilistic methods in landslide susceptibility assessment in Kurseong and its surrounding area of Darjeeling Himalayan, India: RS-GIS approach A. Saha & S. Saha 10.1007/s10668-020-00783-1
834. Joint detection and classification of rockfalls in a microseismic monitoring network L. Feng et al. 10.1093/gji/ggaa287
835. Automated Monitoring and Emergency Response System for Sensitive Areas Along High-Speed Railway Lines C. Chiu et al. 10.1051/e3sconf/202451203003
836. DCI-PGCN: Dual-Channel Interaction Portable Graph Convolutional Network for Landslide Detection W. Li et al. 10.1109/TGRS.2023.3273623
837. Landslide Risk Assessment Using a Combined Approach Based on InSAR and Random Forest W. Liu et al. 10.3390/rs14092131
838. A model for interpreting the deformation mechanism of reservoir landslides in the Three Gorges Reservoir area, China Z. Zou et al. 10.5194/nhess-21-517-2021
839. 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
840. 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
841. Laboratory Landquakes: Insights From Experiments Into the High‐Frequency Seismic Signal Generated by Geophysical Granular Flows M. Arran et al. 10.1029/2021JF006172
842. Understanding the scale effects of topographical variables on landslide susceptibility mapping in Sikkim Himalaya using deep learning approaches A. Saha et al. 10.1080/10106049.2022.2136255
843. Mapping Landslide Susceptibility Over Large Regions With Limited Data J. Woodard et al. 10.1029/2022JF006810
844. Landslide failures detection and mapping using Synthetic Aperture Radar: Past, present and future A. Mondini et al. 10.1016/j.earscirev.2021.103574
845. Fatal landslides in China from 1940 to 2020: occurrences and vulnerabilities S. Zhang et al. 10.1007/s10346-023-02034-6
846. Shape and Dimension Estimations of Landslide Rupture Zones via Correlations of Characteristic Parameters G. Domej et al. 10.3390/geosciences10050198
847. Constructing a complete landslide inventory dataset for the 2018 monsoon disaster in Kerala, India, for land use change analysis L. Hao et al. 10.5194/essd-12-2899-2020
848. Assessment of Physical Vulnerability and Uncertainties for Debris Flow Hazard: A Review concerning Climate Change M. Khan et al. 10.3390/land11122240
849. GIS-Based Expert Knowledge for Landslide Susceptibility Mapping (LSM): Case of Mostaganem Coast District, West of Algeria R. Senouci et al. 10.3390/su13020630
850. Evaluating landslide response in a seismic and rainfall regime: a case study from the SE Carpathians, Romania V. Kumar et al. 10.5194/nhess-21-3767-2021
851. Evaluation of social vulnerability to natural hazards: a case of Barton on Sea, England K. Kantamaneni 10.1007/s12517-019-4819-9
852. Integrated Methodology for Potential Landslide Identification in Highly Vegetation-Covered Areas L. Yan et al. 10.3390/rs15061518
853. Inventory of landslides triggered by an extreme rainfall event in Marche-Umbria, Italy, on 15 September 2022 M. Santangelo et al. 10.1038/s41597-023-02336-3
854. FSLAM: A QGIS plugin for fast regional susceptibility assessment of rainfall-induced landslides Z. Guo et al. 10.1016/j.envsoft.2022.105354
855. Insights from the topographic characteristics of a large global catalog of rainfall-induced landslide event inventories R. Emberson et al. 10.5194/nhess-22-1129-2022
856. Assessing the importance of conditioning factor selection in landslide susceptibility for the province of Belluno (region of Veneto, northeastern Italy) S. Meena et al. 10.5194/nhess-22-1395-2022
857. Rapid characterisation of landslide heterogeneity using unsupervised classification of electrical resistivity and seismic refraction surveys J. Whiteley et al. 10.1016/j.enggeo.2021.106189
858. Landslide Inventorization and Susceptibility Mapping in the SemiArid Kargil-Ladakh Region of Northwestern Himalaya M. Akbar et al. 10.17491/jgsi/2024/173894
859. Cluster landslides and associated damage in the Dima Hasao district of Assam, India due to heavy rainfall in May 2022 P. Roy et al. 10.1007/s10346-022-01977-6
860. Integrating Landslide Typology with Weighted Frequency Ratio Model for Landslide Susceptibility Mapping: A Case Study from Lanzhou City of Northwestern China H. Shu et al. 10.3390/rs13183623
861. The downward spiral entangling soil sealing and hydrogeological disasters A. Gatto et al. 10.1088/1748-9326/ad5fa1
862. Keynote lecture. The planar setup: A window through the complex interactions in granular flows M. Cabrera et al. 10.1051/e3sconf/202341502004
863. Mapping method of rainfall-induced landslide hazards by infiltration and slope stability analysis N. Dolojan et al. 10.1007/s10346-020-01617-x
864. Landslides, a Key Landform in the Global Geological Heritage C. Morino et al. 10.3389/feart.2022.864760
865. Physical vulnerability of reinforced concrete buildings under debris avalanche impact based on GF-discrepancy and DEM-FEM J. Pu et al. 10.1007/s11069-023-06294-2
866. Complex sliding characteristics of landslides and evaluation of the reinforcement with arched anti-slide piles based on 3D discrete element method: a case study Q. Xie et al. 10.1007/s11069-024-06564-7
867. From empirically to physically based early warning predictions of rainfall-induced landslides in silty volcanic soils: the Lattari Mountains case study G. Rianna et al. 10.1007/s10064-023-03228-x
868. The performance of landslides frequency-area distribution analyses using a newly developed fully automatic tool A. Bounab et al. 10.1007/s12518-024-00581-8
869. A Data-Driven Model on Google Earth Engine for Landslide Susceptibility Assessment in the Hengduan Mountains, the Qinghai–Tibetan Plateau W. Wu et al. 10.3390/rs14184662
870. Trees as bioindicators of hillslope degradation by debris flows and dangerous rockfalls along the Lefthand Canyon, Colorado Front Range Ł. Pawlik et al. 10.1002/ldr.4575
871. Enhancing the Accuracy of the REPTree by Integrating the Hybrid Ensemble Meta-Classifiers for Modelling the Landslide Susceptibility of Idukki District, South-western India R. Ajin et al. 10.1007/s12524-022-01599-4
872. Landslide Risk Assessment in Eastern Kentucky, USA: Developing a Regional Scale, Limited Resource Approach M. Crawford et al. 10.3390/rs14246246
873. Internal Force Analysis and Field Test of Lattice Beam Based on Winkler Theory for Elastic Foundation Beam J. Li et al. 10.1155/2019/5130654
874. Combined Effect of the Microstructure and Mechanical Behavior of Lateritic Soils in the Instability of a Road Cut Slope in Rwanda R. Valentino et al. 10.3390/geohazards5020029
875. Behavior of soil slopes reinforced with composite-structural piles Y. Xiang et al. 10.1088/1755-1315/1334/1/012016
876. Invited perspectives: Building sustainable and resilient communities – recommended actions for natural hazard scientists J. Gill et al. 10.5194/nhess-21-187-2021
877. Dynamic deformation monitoring and scenario simulation of the Xiaomojiu landslide in the Jinsha River Basin, China C. Zhang et al. 10.1007/s10346-023-02103-w
878. AutoGluon: A revolutionary framework for landslide hazard analysis W. Qi et al. 10.1016/j.nhres.2021.07.002
879. A comprehensive global database of giant landslides on volcanic islands J. Blahůt et al. 10.1007/s10346-019-01275-8
880. Numerical investigation on the sliding process and deposit feature of an earthquake-induced landslide: a case study H. Wang et al. 10.1007/s10346-020-01446-y
881. A Framework to Project Future Rainfall Scenarios: An Application to Shallow Landslide-Triggering Summer Rainfall in Wanzhou County China J. Ferrer et al. 10.3390/w14060873
882. Simple rules to minimise exposure to coseismic landslide hazard D. Milledge et al. 10.5194/nhess-19-837-2019
883. Multisource Data Fusion and Adversarial Nets for Landslide Extraction from UAV-Photogrammetry-Derived Data H. He et al. 10.3390/rs14133059
884. Causes of episodic movement of the Baijiabao landslide based on multiple-time scale analysis Z. Fu et al. 10.1007/s10346-023-02201-9
885. An InSAR and depth-integrated coupled model for potential landslide hazard assessment S. Zhou et al. 10.1007/s11440-021-01429-w
886. Space-time modeling of cascading hazards: Chaining wildfires, rainfall and landslide events through machine learning M. Di Napoli et al. 10.1016/j.catena.2024.108452
887. Assessing Urban Landslide Dynamics through Multi-Temporal InSAR Techniques and Slope Numerical Modeling N. Necula et al. 10.3390/rs13193862
888. Atmospheric triggering conditions and climatic disposition of landslides in Kyrgyzstan and Tajikistan at the beginning of the 21st century X. Wang et al. 10.5194/nhess-21-2125-2021
889. Reconstruction and verification of mechanism and triggering conditions of the Hermitage landslide at the Vaches Noires cliffs (Normandy) M. Kouah et al. 10.1016/j.geomorph.2024.109399
890. Enhancing landslide hazard prevention: Mapping vulnerability via considering the effects of human factors D. Yin et al. 10.1016/j.ijdrr.2024.104509
891. The impact of environmental change on landslides, fatal landslides, and their triggers in Pakistan (2003–2019) W. Shabbir et al. 10.1007/s11356-022-24291-z
892. Exploration of Multi-Decadal Landslide Frequency and Vegetation Recovery Conditions Using Remote-Sensing Big Data M. Aman et al. 10.1007/s41748-024-00432-x
893. Worldwide Research Trends in Landslide Science P. Carrión-Mero et al. 10.3390/ijerph18189445
894. Unified model rainfall forecasts over India during 2007–2018: Evaluating extreme rains over hilly regions K. Sharma et al. 10.1007/s12040-021-01595-1
895. Probabilistic back-analysis of rainfall-induced landslides for slope reliability prediction with multi-source information S. Jiang et al. 10.1016/j.jrmge.2024.02.008
896. EFFECT OF PARTICLE SIZE DISTRIBUTIONS ON GRANULAR FLOW SIMULATIONS USING DISCRETE ELEMENT METHOD D. WATANABE et al. 10.2208/jscejge.77.4_392
897. Review on the progress and future prospects of geological disasters prediction in the era of artificial intelligence X. Zhang et al. 10.1007/s11069-024-06673-3
898. Revalidation Technique on Landslide Susceptibility Modelling: An Approach to Local Level Disaster Risk Management in Kuala Lumpur, Malaysia E. Affandi et al. 10.3390/app13020768
899. Application of ML- based approach for co-seismic landslides susceptibility mapping and identification of important controlling factors in eastern Himalayan region S. Kumar & A. Sengupta 10.1007/s12665-024-11911-9
900. An Ensemble Approach of Feature Selection and Machine Learning Models for Regional Landslide Susceptibility Mapping in the Arid Mountainous Terrain of Southern Peru C. Kumar et al. 10.3390/rs15051376
901. Random forest-based screening of environmental geohazard probability factors in Panshi city, China L. Qi et al. 10.1016/j.asr.2024.09.055
902. Assessment of landslide susceptibility for Meghalaya (India) using bivariate (frequency ratio and Shannon entropy) and multi-criteria decision analysis (AHP and fuzzy-AHP) models N. Agrawal & J. Dixit 10.1080/27669645.2022.2101256
903. Analysis of deformation characteristics of reverse slope under the influence of reservoir water based on community detection L. Xie et al. 10.1007/s12665-022-10252-9
904. Landslide spatial prediction utilizing fuzzy unordered rules induction ensemble models: a case study in Thai Nguyen, Vietnam H. Ha et al. 10.1007/s40808-023-01888-y
905. A Comparative Study of Landslide Susceptibility Mapping Using SVM and PSO-SVM Models Based on Grid and Slope Units S. Zhao et al. 10.1155/2021/8854606
906. Time and path prediction of landslides using InSAR and flow model P. Roy et al. 10.1016/j.rse.2022.112899
907. Inventory of large landslides along the Central Western Andes (ca. 15°–20° S): Landslide distribution patterns and insights on controlling factors F. Delgado et al. 10.1016/j.jsames.2022.103824
908. Towards establishing rainfall thresholds for a real-time landslide early warning system in Sikkim, India G. Harilal et al. 10.1007/s10346-019-01244-1
909. Landslides Detection and Mapping with an Advanced Multi-Temporal Satellite Optical Technique V. Satriano et al. 10.3390/rs15030683
910. Landslide susceptibility and building exposure assessment using machine learning models and geospatial analysis techniques C. Luu et al. 10.1016/j.asr.2024.08.046
911. Geophysical Monitoring of Moisture‐Induced Landslides: A Review J. Whiteley et al. 10.1029/2018RG000603
912. Landslide susceptibility modeling in a complex mountainous region of Sikkim Himalaya using new hybrid data mining approach A. Islam et al. 10.1080/10106049.2021.2009920
913. CHILDA – Czech Historical Landslide Database M. Bíl et al. 10.5194/nhess-21-2581-2021
914. Evaluation of machine learning-based algorithms for landslide detection across satellite sensors for the 2019 Cyclone Idai event, Chimanimani District, Zimbabwe R. Das & K. Wegmann 10.1007/s10346-022-01912-9
915. An Assessment of Negative Samples and Model Structures in Landslide Susceptibility Characterization Based on Bayesian Network Models S. Khabiri et al. 10.3390/rs15123200
916. Towards hydrometeorological thresholds of reservoir-induced landslide from subsurface strain observations X. Ye et al. 10.1007/s11431-023-2657-3
917. Assessment of landslide susceptibility and risk factors in China D. Wang et al. 10.1007/s11069-021-04812-8
918. Multi-hazard susceptibility and exposure assessment of the Hindu Kush Himalaya J. Rusk et al. 10.1016/j.scitotenv.2021.150039
919. Spatiotemporal Analysis of Ecological Security Based on Landscape Patterns H. Zhang et al. 10.3390/ijgi13060204
920. Temporal and spatial distributions of landslides in the Qinba Mountains, Shaanxi Province, China H. Qiu et al. 10.1080/19475705.2018.1536080
921. Landslide susceptibility mapping using statistical and machine learning models (case study: Austria) M. Moharrami & M. Jelokhani-Niaraki 10.61186/jgst.13.2.79
922. Nationwide Susceptibility Mapping of Landslides in Kenya Using the Fuzzy Analytic Hierarchy Process Model S. Zhou et al. 10.3390/land9120535
923. Brief communication: Key papers of 20 years in <i>Natural Hazards and Earth System Sciences</i> A. Gain et al. 10.5194/nhess-22-985-2022
924. Influence of sampling design on landslide susceptibility modeling in lithologically heterogeneous areas A. Dornik et al. 10.1038/s41598-022-06257-w
925. Machine learning-based assessment of regional-scale variation of landslide susceptibility in central Vietnam R. Das et al. 10.1371/journal.pone.0308494
926. Evaluation of potential changes in landslide susceptibility and landslide occurrence frequency in China under climate change Q. Lin et al. 10.1016/j.scitotenv.2022.158049
927. 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
928. 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
929. Observations and computational multi‐phase modelling in tropical river settings show complex channel changes downstream from rainfall‐triggered landslides D. Panici et al. 10.1002/esp.5841
930. Highway Proneness Appraisal to Landslides along Taiping to Ipoh Segment Malaysia, Using MCDM and GIS Techniques I. Yamusa et al. 10.3390/su14159096
931. 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
932. Landslide Risk Modeling using Data Mining in Hyrcanian Forests N. Nazariani & A. Fallah 10.61186/jwmr.14.27.123
933. Integrated impacts of vegetation and soil type on slope stability: A case study of Kheyrud Forest, Iran M. Emadi-Tafti et al. 10.1016/j.ecolmodel.2021.109498
934. Future climate change implications in Bhutan from a downscaled and bias‐adjusted CMIP6 multimodel ensemble F. Lehner et al. 10.1002/joc.8623
935. 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
936. Rainfall-Induced Landslide Assessment under Different Precipitation Thresholds Using Remote Sensing Data: A Central Andes Case G. Maragaño-Carmona et al. 10.3390/w15142514
937. 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
938. Application of novel distributed fibre-optic sensing for slope deformation monitoring: a comprehensive review A. Acharya & T. Kogure 10.1007/s13762-022-04697-5
939. Deep learning algorithms based landslide vulnerability modeling in highly landslide prone areas of Tamil Nadu, India S. Saha et al. 10.1007/s12303-024-0044-y
940. 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
941. Exploring disaster ontologies from Chinese and Western perspectives: commonalities and nuances S. Goodall et al. 10.1108/DPM-03-2021-0108
942. Simulated or measured soil moisture: which one is adding more value to regional landslide early warning? A. Wicki et al. 10.5194/hess-25-4585-2021
943. 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
944. Engineering geomorphological investigation of the Kasavu landslide, Viti Levu, Fiji A. Ram et al. 10.1007/s10346-019-01191-x
945. A novel landslide susceptibility optimization framework to assess landslide occurrence probability at the regional scale for environmental management X. Sun et al. 10.1016/j.jenvman.2022.116108
946. Research on Uncertainty of Landslide Susceptibility Prediction—Bibliometrics and Knowledge Graph Analysis Z. Yang et al. 10.3390/rs14163879
947. Hydrological-hydrodynamic simulation and analysis of the possible influence of the wind in the extraordinary flood of 1941 in Porto Alegre T. Possa et al. 10.1590/2318-0331.272220220028
948. Global Dynamic Rainfall-Induced Landslide Susceptibility Mapping Using Machine Learning B. Li et al. 10.3390/rs14225795
949. Landslide susceptibility mapping with r.landslide: A free open-source GIS-integrated tool based on Artificial Neural Networks L. Bragagnolo et al. 10.1016/j.envsoft.2019.104565
950. 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
951. Research on SSA-LSTM-Based Slope Monitoring and Early Warning Model S. Yang et al. 10.3390/su141610246
952. A New Deep Learning Neural Network Model for the Identification of InSAR Anomalous Deformation Areas T. Zhang et al. 10.3390/rs14112690
953. Editorial: Big Earth Data for Disaster Risk Reduction F. Chen et al. 10.3389/feart.2021.727547
954. 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
955. 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
956. Detection of slow‐moving landslides through automated monitoring of surface deformation using Sentinel‐2 satellite imagery M. Van Wyk de Vries et al. 10.1002/esp.5775
957. Rainfall infiltration and slope stability of alpine colluvial terraces subject to storms (NE Italy) P. Paronuzzi & A. Bolla 10.1016/j.enggeo.2023.107199
958. Roads and landslides in Nepal: how development affects environmental risk B. McAdoo et al. 10.5194/nhess-18-3203-2018
959. 2-D Cross-Plot Model Analysis Using Integrated Geophysical Methods for Landslides Assessment M. Zakaria et al. 10.3390/app11020747
960. An integrated approach based landslide susceptibility mapping: case of Muzaffarabad region, Pakistan M. Basharat et al. 10.1080/19475705.2023.2210255
961. How water, wind, waves and ice shape landscapes and landforms: Historical contributions to geomorphic science J. Gardner 10.1016/j.geomorph.2019.02.031
962. Sustainable rural infrastructure: guidelines for roadside slope excavation P. Paudyal et al. 10.1186/s40677-023-00240-x
963. Mass Movement Hazard and Exposure in the Himalaya S. Dubey et al. 10.1029/2022EF003253
964. A novel approach for displacement interval forecasting of landslides with step-like displacement pattern Q. Ge et al. 10.1080/17499518.2021.1892769
965. Redefining landslide susceptibility under extreme rainfall events using deep learning A. Achu et al. 10.1016/j.geomorph.2023.109033
966. Physics-informed data assimilation model for displacement prediction of hydrodynamic pressure-driven landslide Y. Liu et al. 10.1016/j.compgeo.2024.106085
967. 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
968. 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
969. Improving the forecast performance of landslide susceptibility mapping by using ensemble gradient boosting algorithms H. Ha et al. 10.1007/s10668-024-04694-3
970. Evaluation and prediction of compound geohazards in highly urbanized regions across China's Greater Bay Area K. He et al. 10.1016/j.jclepro.2024.141641
971. The Alasu rock avalanche in the Tianshan Mountains, China: fragmentation, landforms, and kinematics Q. Lin et al. 10.1007/s10346-023-02167-8
972. Assessing the effectiveness of landslide slope stability by analysing structural mitigation measures and community risk perception A. Kamal et al. 10.1007/s11069-023-05947-6
973. Evaluating landslide susceptibility: an AHP method-based approach enhanced with optimized random forest modeling X. Zhang et al. 10.1007/s11069-023-06306-1
974. Identifying Potential Landslides on Giant Niexia Slope (China) Based on Integrated Multi-Remote Sensing Technologies X. Dong et al. 10.3390/rs14246328
975. Post‐landslide soil and vegetation recovery in a dry, montane system is slow and patchy B. Buma & Ł. Pawlik 10.1002/ecs2.3346
976. Real‐Time Forecast of Catastrophic Landslides via Dragon‐King Detection Q. Lei et al. 10.1029/2022GL100832
977. 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
978. Impact of precipitation on Beishan landslide deformation from 1986 to 2023 M. Liu et al. 10.3389/feart.2023.1304969
979. Spatial Prediction of Landslide Susceptibility using Various Machine Learning Based Binary Classification Methods N. Anh et al. 10.17491/jgsi/2024/174002
980. Displacement residuals reveal landslide regime shifts L. Nava et al. 10.1007/s10346-024-02353-2
981. Guidelines for Studying Diverse Types of Compound Weather and Climate Events E. Bevacqua et al. 10.1029/2021EF002340
982. Consideration of spatial heterogeneity in landslide susceptibility mapping using geographical random forest model R. Quevedo et al. 10.1080/10106049.2021.1996637
983. Landslide Susceptibility Assessment by Novel Hybrid Machine Learning Algorithms B. Thai Pham et al. 10.3390/su11164386
984. Landslide Susceptibility Mapping Using GIS-Based Data Mining Algorithms V. Vakhshoori et al. 10.3390/w11112292
985. Evaluation of Slope Stability in an Urban Area as a Basis for Territorial Planning: A Case Study P. Carrión-Mero et al. 10.3390/app11115013
986. Hazard Assessment of Debris Flow Based on Infinite Irrelevance Method and Probabilistic Neural Network Coupling Model C. Wang et al. 10.1109/ACCESS.2022.3162597
987. A depth-averaged SPH study on spreading mechanisms of geophysical flows in debris basins: Implications for terminal barrier design requirements S. Goodwin & C. Choi 10.1016/j.compgeo.2021.104503
988. Influence of human activity on landslide susceptibility development in the Three Gorges area Y. Li et al. 10.1007/s11069-020-04264-6
989. Breaking Limits of Remote Sensing by Deep Learning From Simulated Data for Flood and Debris-Flow Mapping N. Yokoya et al. 10.1109/TGRS.2020.3035469
990. Century-long history of rural community landslide risk reduction J. Klimeš et al. 10.1016/j.ijdrr.2020.101756
991. A near-real-time global landslide incident reporting tool demonstrator using social media and artificial intelligence C. Pennington et al. 10.1016/j.ijdrr.2022.103089
992. Spatiotemporal Characteristics and Rainfall Thresholds of Geological Landslide Disasters in ASEAN Countries W. Lu et al. 10.3390/atmos15050599
993. Unsupervised Change Detection Methods Applied to Landslide Mapping: Case Study in São Sebastião, Brazil G. Moço et al. 10.1111/tgis.13256
994. GIS-based evolution and comparisons of landslide susceptibility mapping of the East Sikkim Himalaya N. Gupta et al. 10.1080/19475683.2022.2040587
995. Cost-benefit methodology for road slope stabilisation E. Robson et al. 10.1016/j.trgeo.2024.101282
996. Rainfall threshold for prediction of shallow landslides in the Garhwal Himalaya, India S. Saha & B. Bera 10.1016/j.geogeo.2024.100285
997. Deformation Feature Extraction for GNSS Landslide Monitoring Series Based on Robust Adaptive Sliding-Window Algorithm G. Huang et al. 10.3389/feart.2022.884500
998. Assessment of Ground Instabilities’ Causative Factors Using Multivariate Statistical Analysis Methods: Case of the Coastal Region of Northwestern Rif, Morocco H. Tribak et al. 10.3390/geosciences12100383
999. Improvement of landslide hazard assessments for regulatory zoning in France: STATE–OF–THE-ART perspectives and considerations Y. Thiery et al. 10.1016/j.ijdrr.2020.101562
1000. 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
1001. Rainfall Threshold for Shallow Landslides Initiation and Analysis of Long-Term Rainfall Trends in a Mediterranean Area A. Roccati et al. 10.3390/atmos11121367
1002. The geoenvironmental factors influencing slope failures in the Majerda basin, Algerian-Tunisian border I. Arif et al. 10.1007/s41207-023-00423-w
1003. Village relocation as solution of the landslide risk, is it always the right choice? The case study of Cavallerizzo ghost village (Calabria, southern Italy) F. Ietto et al. 10.1016/j.ijdrr.2022.103267
1004. Pixel-Based Spatio-Statistical Analysis of Landslide Probability in Humid and Seismically Active Areas of Himalaya and Hindukush S. Khan et al. 10.3390/su16093556
1005. Life and death of slow-moving landslides P. Lacroix et al. 10.1038/s43017-020-0072-8
1006. Revolutionising construction safety: benefits of harnessing artificial intelligence tools for dynamic monitoring of safety compliance on construction projects in Nigeria I. Adamu et al. 10.1108/IJBPA-02-2024-0050
1007. Parallel simulations for fast‐moving landslides: Space‐time mesh adaptation and sharp tracking of the wetting front F. Gatti et al. 10.1002/fld.5186
1008. Assessing the Effectiveness of TRIGRS for Predicting Unstable Areas in a Tropical Mountain Basin (Colombian Andes) R. Marin et al. 10.1007/s10706-020-01630-w
1009. Lethality level analysis of secondary landslides based on field survey data: a case study of Luding earthquake L. Yao et al. 10.1007/s10346-023-02172-x
1010. Landslides in the glaciated mountains of the Cordillera Blanca, Peru—types, spatial distribution, and conditioning factors J. Klimeš et al. 10.1007/s10346-024-02387-6
1011. The Role of Hydraulic Hysteresis on the Hydrological Response of Pyroclastic Silty Covers G. Rianna et al. 10.3390/w11030628
1012. Towards Automatic Landslide-Quake Identification Using a Random Forest Classifier G. Lin et al. 10.3390/app10113670
1013. Exploring available landslide inventories for susceptibility analysis in Gipuzkoa province (Spain) T. Bornaetxea et al. 10.1007/s11069-023-06103-w
1014. A novel framework for landslide displacement prediction using MT-InSAR and machine learning techniques C. Zhou et al. 10.1016/j.enggeo.2024.107497
1015. How size and trigger matter: analyzing rainfall- and earthquake-triggered landslide inventories and their causal relation in the Koshi River basin, central Himalaya J. Zhang et al. 10.5194/nhess-19-1789-2019
1016. Exploring the association between landslides and fluvial suspended sediment in a semi-arid basin in central Chile I. Vergara et al. 10.1016/j.geomorph.2022.108129
1017. A Comparative Analysis of Slope Failure Prediction Using a Statistical and Machine Learning Approach on Displacement Data: Introducing a Tailored Performance Metric S. Chaulagain et al. 10.3390/buildings13112691
1018. Application of potential machine learning models in landslide susceptibility assessment: A case study of Van Yen district, Yen Bai province, Vietnam V. Tran et al. 10.1016/j.qsa.2024.100181
1019. Experimental Investigation on Integrated Subsurface Monitoring of Soil Slope Using Acoustic Emission and Mechanical Measurement L. Deng et al. 10.3390/app11167173
1020. A Comparison of Alternative GIS Data Model Methods for Landslide Susceptibility Mapping with XGBoost and SHAP Ş. Bediroğlu 10.31466/kfbd.1446997
1021. ANALYSIS OF SPATIAL PATTERNS OF LANDSLIDE FORMATION WITH GIS TOOLS (ZAKARPATSKA OBLAST) S. Shekhunova et al. 10.15407/ugz2022.03.011
1022. Satellite InSAR as a New Tool for the Verification of Landslide Engineering Remedial Works at the Regional Scale: A Case Study in the Three Gorges Resevoir Area, China S. Liu et al. 10.3390/app10186435
1023. Dendrogeomorphological analysis of landslides on the undercut river terrace bank (a case study in Czech Republic) K. Šilhán 10.1007/s10346-021-01833-z
1024. Risk assessment and management of rainfall-induced landslides in tropical regions: a review M. Amarasinghe et al. 10.1007/s11069-023-06277-3