1248 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. Long-Term Monitoring of Landslide Activity in a Debris Flow Gully Using SBAS-InSAR: A Case Study of Shawan Gully, China J. Zhang et al. 10.3390/rs17091580
4. A new landslide detection approach using the combination of the normalized difference moisture index and slope classification analysis M. Rendana et al. 10.1080/24749508.2024.2429205
5. Hydrometeorological disasters in urban areas of Costa Rica, Central America A. Quesada-Román et al. 10.1080/17477891.2020.1791034
6. Invited perspectives: Landslide populations – can they be predicted? F. Guzzetti 10.5194/nhess-21-1467-2021
7. 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
8. Deadly Myanmar mine disaster caused by poor planning, say data sleuths A. Silver 10.1038/d41586-021-01740-2
9. 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
10. A Deep-Learning-Based Algorithm for Landslide Detection over Wide Areas Using InSAR Images Considering Topographic Features N. Li et al. 10.3390/s24144583
11. Rainfall Induced Landslide Studies in Indian Himalayan Region: A Critical Review A. Dikshit et al. 10.3390/app10072466
12. 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
13. Scenarios of Human Responses to Unprecedented Social‐Environmental Extreme Events M. Rusca et al. 10.1029/2020EF001911
14. 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
15. Landslide susceptibility assessment in Tongguan District Anhui China using information value and certainty factor models D. Ding et al. 10.1038/s41598-025-93704-z
16. Mapping Landslides on EO Data: Performance of Deep Learning Models vs. Traditional Machine Learning Models N. Prakash et al. 10.3390/rs12030346
17. Spatial and Temporal Analysis of Global Landslide Reporting Using a Decade of the Global Landslide Catalog C. Dandridge et al. 10.3390/su15043323
18. Sonlu Elemanlar Yöntemi ile Depreme Bağlı Heyelan Tehlike Modelleme F. SUNBUL & A. SUNBUL 10.20854/bujse.829417
19. 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
20. Shared Blocks-Based Ensemble Deep Learning for Shallow Landslide Susceptibility Mapping T. Kavzoglu et al. 10.3390/rs13234776
21. The cost of rapid and haphazard urbanization: lessons learned from the Freetown landslide disaster Y. Cui et al. 10.1007/s10346-019-01167-x
22. Mapping Landslide Susceptibility Using Machine Learning Algorithms and GIS: A Case Study in Shexian County, Anhui Province, China Z. Wang et al. 10.3390/sym12121954
23. Aspects of different growth responses of coniferous and broadleaved tree species in landslide research K. Šilhán 10.1016/j.dendro.2025.126368
24. Impact of rock block characteristics on rockfall hazard and its implications for rockfall protection strategies along Himalayan highways: a case study A. Singh et al. 10.1007/s10064-021-02288-1
25. Estimating Rainfall Thresholds for Landslide Occurrence in the Bhutan Himalayas A. Dikshit et al. 10.3390/w11081616
26. 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
27. 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
28. Performance of logistic regression and support vector machine conjunction with the GIS and RS in the landslide susceptibility assessment: Case study in Nakhon Si Thammarat, southern Thailand K. Prathom & C. Sujitapan 10.1016/j.jksus.2024.103306
29. An optimized non-landslide sampling method for Landslide susceptibility evaluation using machine learning models S. Xu et al. 10.1007/s11069-024-07021-1
30. Towards a web service for rapid landslide mapping based on Copernicus data F. Albrecht et al. 10.1088/1755-1315/509/1/012002
31. 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
32. Infrared thermography reveals weathering hotspots at the Požáry field laboratory M. Loche et al. 10.1038/s41598-024-65527-x
33. Framework for rainfall-triggered landslide-prone critical infrastructure zonation K. Gnyawali et al. 10.1016/j.scitotenv.2023.162242
34. Utilization of google maps for depicting landslide pattern in Indonesia S. Sukristiyanti et al. 10.1088/1755-1315/500/1/012042
35. Landslide Characterization Applying Sentinel-1 Images and InSAR Technique: The Muyubao Landslide in the Three Gorges Reservoir Area, China C. Zhou et al. 10.3390/rs12203385
36. Investigation of the dynamic process of the Xinmo landslide using the discrete element method Z. Liu et al. 10.1016/j.compgeo.2020.103561
37. Evaluation of linear, nonlinear and ensemble machine learning models for landslide susceptibility assessment in southwest China B. Wang et al. 10.1080/10106049.2022.2152493
38. GIS-based landslide susceptibility zonation mapping using the analytic hierarchy process (AHP) method in parts of Kalimpong Region of Darjeeling Himalaya S. Das et al. 10.1007/s10661-022-09851-7
39. Study on Numerical Model and Dynamic Response of Ring Net in Flexible Rockfall Barriers C. Xia et al. 10.3390/su14084406
40. Development and Assessment of GIS-Based Landslide Susceptibility Mapping Models Using ANN, Fuzzy-AHP, and MCDA in Darjeeling Himalayas, West Bengal, India A. Saha et al. 10.3390/land11101711
41. Study on Optimal Pile Length in Load Section of Double-Row Buried Pile under Overtopping Failure Mode X. Li et al. 10.3390/app14010438
42. Triggering mechanics and early warning for snowmelt-rainfall-induced loess landslide K. Wulamu et al. 10.1038/s41598-024-78309-2
43. Characteristics of failure area and failure mechanism of a landslide in Yingjiang County, Yunnan, China G. Shi et al. 10.1007/s10346-020-01544-x
44. Landslide detection in the Himalayas using machine learning algorithms and U-Net S. Meena et al. 10.1007/s10346-022-01861-3
45. An Increasing Trend of Landslides as a Consequence of the Global Change J. Remondo et al. 10.1007/s41748-025-00685-0
46. Assessing Landslide Drivers in Social–Ecological–Technological Systems: The Case of Metropolitan Region of São Paulo, Brazil M. Hirye et al. 10.3390/rs15123048
47. Evaluating map quality and model performance through iterative statistics-based landslide susceptibility in eastern KY M. Crawford et al. 10.1007/s11069-025-07255-7
48. Dynahead-YOLO-Otsu: an efficient DCNN-based landslide semantic segmentation method using remote sensing images Z. Han et al. 10.1080/19475705.2024.2398103
49. Simulation of cyclic slow-to-fast landslides based on the coupled creep and frictional slip model C. Xia et al. 10.1016/j.compgeo.2024.106083
50. Exploring performance and robustness of shallow landslide susceptibility modeling at regional scale using different training and testing sets M. Conforti et al. 10.1007/s12665-023-10844-z
51. Landslide susceptibility evaluation based on landslide classification and ANN-NFR modelling in the Three Gorges Reservoir area, China J. Wang et al. 10.1016/j.ecolind.2024.111920
52. Comparison between mechanical and hydrological reinforcement effects of cultivated plants on shallow slope stability M. Bordoni et al. 10.1016/j.scitotenv.2023.168999
53. Quantifying annual occurrence probability of rainfall-induced landslide at a specific slope X. Liu & Y. Wang 10.1016/j.compgeo.2022.104877
54. Effect of spatial resolution and data splitting on landslide susceptibility mapping using different machine learning algorithms M. Abraham et al. 10.1080/19475705.2021.2011791
55. Rainfall-triggered landslides from the January 2023 1-in-200 year storm at Maungakiekie/One Tree Hill, Auckland, New Zealand G. Abazu et al. 10.1080/00288306.2025.2479699
56. Exploring the rainfall data from satellites to monitor rainfall induced landslides – A case study M. Kumar Thakur et al. 10.1016/j.asr.2020.05.015
57. Divergent patterns of landslide activity and triggering factors at a local scale of a single mountain massif (Island Beskid Mts., Western Carpathians, Poland) M. Wistuba et al. 10.1016/j.enggeo.2024.107531
58. A comparative geological, tectonic and geomorphological assessment of the Charlotte, Regent and Madina landslides, Western area, Sierra Leone Y. Lahai et al. 10.1186/s40677-021-00187-x
59. Mechanism of subsidence-buckling and instability of slopes in thick-layered rigid rock under mining J. Deng et al. 10.1007/s11629-023-7952-6
60. Community adaptive capacity in facing landslide disaster P. Wijayanti et al. 10.1088/1755-1315/1314/1/012107
61. Mapping of landslide potential in Pyeongchang-gun, South Korea, using machine learning meta-based optimization algorithms M. Fadhillah et al. 10.1016/j.ejrs.2022.03.008
62. Understanding selective triggering of landslide movement in response to rainfall, Gisborne, New Zealand A. Pola et al. 10.1080/00288306.2025.2517901
63. A comparative study of regional rainfall-induced landslide early warning models based on RF、CNN and MLP algorithms Y. Liu et al. 10.3389/feart.2024.1419421
64. Determination of Rainfall Thresholds for Landslide Prediction Using an Algorithm-Based Approach: Case Study in the Darjeeling Himalayas, India T. Teja et al. 10.3390/geosciences9070302
65. Casual-Nuevo Alausí Landslide (Ecuador, March 2023): A Case Study on the Influence of the Anthropogenic Factors L. Pilatasig et al. 10.3390/geohazards6020028
66. Application of artificial intelligence in three aspects of landslide risk assessment: A comprehensive review R. He et al. 10.1016/j.rockmb.2024.100144
67. Spatial Vulnerability Investigation by Morphotectonic Analysis of the Mandakini River Basin near Kedarnath, Uttarakhand, India using SRTM DEM in a GIS Platform and GPS Data S. Sahu & N. Bhattacharjee 10.17491/jgsi/2024/173913
68. The Spatiotemporal Evolution of Geo-Disaster Resilience in China and the Impact Mechanism of Environmental Governance H. Zhu et al. 10.3390/atmos16030247
69. Ensemble modeling of landslide susceptibility using random subspace learner and different decision tree classifiers B. Pham et al. 10.1080/10106049.2020.1737972
70. Comparing characteristics of rainfall- and earthquake-triggered landslides in the Upper Minjiang catchment, China S. Bai et al. 10.1016/j.enggeo.2020.105518
71. Spatiotemporal distribution patterns of deadly geohazard events in China, 2013–2019 Y. Huang et al. 10.1016/j.nhres.2022.10.003
72. Evaluation of the impact of climate change on rainfall for potential landslide triggering in Japan H. Tsunetaka et al. 10.1002/esp.6050
73. Leveraging local knowledge for landslide disaster risk reduction in an urban informal settlement in Manado, Indonesia E. MacAfee et al. 10.1016/j.ijdrr.2024.104710
74. 4D electrical resistivity to monitor unstable slopes in mountainous tropical regions: an example from Munnar, India A. Watlet et al. 10.1007/s10346-023-02029-3
75. Rapid Deformation Identification and Adaptive Filtering with GNSS TDCP Under Different Scenarios and Its Application in Landslide Monitoring M. Wu et al. 10.3390/rs17101751
76. Multi-hazard susceptibility mapping of landslides and earthquakes in Bhagirathi Valley region of Uttarakhand Himalaya, India N. Gupta et al. 10.1080/14498596.2024.2409083
77. The impact of the aggregation formula on indicator-based method for the assessment of building susceptibility to hydro-meteorological hazards R. Agliata et al. 10.1016/j.ijdrr.2022.102850
78. IoT-based hydrological monitoring of water-induced landslides: a case study in central Norway E. Oguz et al. 10.1007/s10064-022-02721-z
79. Geomorphological landslide inventory map of the Daunia Apennines, southern Italy F. Ardizzone et al. 10.5194/essd-15-753-2023
80. Differences in factors determining landslide hazards among three types of landslides in Japan Y. Shinohara & Y. Watanabe 10.1007/s11069-023-06075-x
81. Failure characteristics and mechanism of a landslide in weathered phyllite at Anqian iron mine, Liaoning, China S. Sun et al. 10.1007/s10064-022-02939-x
82. Deformation dynamics and hazard of slow-moving landslides: The 2023 Joshimath event, Uttarakhand Himalaya P. Dalal et al. 10.1016/j.enggeo.2025.108201
83. Characteristics and causes of natural and human-induced landslides in a tropical mountainous region: the rift flank west of Lake Kivu (Democratic Republic of the Congo) J. Maki Mateso et al. 10.5194/nhess-23-643-2023
84. Preface: Landslide–transport network interactions F. Taylor et al. 10.5194/nhess-20-2585-2020
85. 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
86. Historical damaging geo-hydrological events affecting the Catanzaro municipality (Calabria, Southern Italy), 1830–2023 M. Conforti et al. 10.1080/17445647.2025.2498977
87. 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
88. Performance and topographic preferences of dynamic and steady models for shallow landslide prediction in a small catchment W. Liang & T. Uchida 10.1007/s10346-021-01771-w
89. Multi-model combination in key steps for landslide susceptibility modeling and uncertainty analysis: a case study in Baoji City, China L. Liu & J. Deng 10.1080/19475705.2024.2344804
90. Slope deformation, reservoir variation and meteorological data at the Khoko landslide, Enguri hydroelectric basin (Georgia), during 2016–2019 A. Tibaldi et al. 10.5194/essd-13-3321-2021
91. 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
92. Land surface temperature (LST) and soil moisture index (SMI) to identify slope stability S. Putro et al. 10.1088/1755-1315/986/1/012022
93. Decoding the dynamics of July 2024 Mundakkai-Chooralmala landslide in Kerala (India): an analysis of formation mechanisms, impacts and lessons learned A. Achu et al. 10.1007/s10346-024-02454-y
94. Future changes in precipitation-caused landslide frequency in British Columbia S. Sobie 10.1007/s10584-020-02788-1
95. Landslide hazard and loss-of-life risk assessment for Muriwai, New Zealand following Cyclone Gabrielle in February 2023 M. Howard et al. 10.1080/00288306.2025.2470433
96. When image correlation is needed: Unravelling the complex dynamics of a slow-moving landslide in the tropics with dense radar and optical time series A. Dille et al. 10.1016/j.rse.2021.112402
97. A revised landslide inventory of the Campania region (Italy) F. Fusco et al. 10.1038/s41597-023-02155-6
98. Quick and automatic detection of co-seismic landslides with multi-feature deep learning model W. Huangfu et al. 10.1007/s11430-023-1306-8
99. Physics-based time-of-failure determination of rainfall-induced instability in lateritic soil slopes S. Rahul & A. Tyagi 10.1016/j.enggeo.2024.107834
100. Acid rain: an unsuspected factor predisposing Panzhihua airport landslide, China K. Li et al. 10.1007/s11356-021-13308-8
101. A modeling framework for assessing the future changes in the occurrence of extreme rain-induced landslides X. Zhang et al. 10.1016/j.gr.2025.03.009
102. 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
103. A Regularization Method for Landslide Thickness Estimation L. Borgatti et al. 10.3390/jimaging10120314
104. A Meta-Learning Approach of Optimisation for Spatial Prediction of Landslides B. Pradhan et al. 10.3390/rs13224521
105. Present and Projected Suitability of Olive Trees in a Currently Marginal Territory in the Face of Climate Change: A Case Study from N-Italy M. Bordoni et al. 10.3390/su17051949
106. Building a landslide hazard indicator with machine learning and land surface models T. Stanley et al. 10.1016/j.envsoft.2020.104692
107. Physically-based catchment-scale prediction of slope failure volume and geometry B. Van den Bout et al. 10.1016/j.enggeo.2020.105942
108. Freeze-thaw induced landslides on grasslands in cold regions J. Yang et al. 10.1016/j.catena.2022.106650
109. The research on landslide detection in remote sensing images based on improved DeepLabv3+ method Y. Li 10.1038/s41598-025-92822-y
110. Machine learning and landslide studies: recent advances and applications F. Tehrani et al. 10.1007/s11069-022-05423-7
111. Seismic, Field, and Remote Sensing Analysis of the 13 February 2024 Çöpler Gold Mine Landslide, Erzincan, Türkiye P. Büyükakpınar et al. 10.1785/0320250007
112. 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
113. Landslides across the USA: occurrence, susceptibility, and data limitations B. Mirus et al. 10.1007/s10346-020-01424-4
114. Analysis and Application of the CAUSE Model in Regional Disaster Prevention Measures Z. Tang et al. 10.3390/geohazards6020017
115. 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
116. Low-Power, Flexible Sensor Arrays with Solderless Board-to-Board Connectors for Monitoring Soil Deformation and Temperature S. Wielandt et al. 10.3390/s22072814
117. Geospatial assessment and integrated multi-model approach for landslide susceptibility mapping in Meghalaya, India N. Badavath & S. Sahoo 10.1016/j.asr.2024.11.052
118. Chronicle of destruction: the Wayanad landslide of July 30, 2024 A. Yunus et al. 10.1007/s10346-025-02494-y
119. 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
120. A rockslide-induced debris flow caused the catastrophic 2024 Wayanad disaster in Kerala, India P. Roy et al. 10.1007/s10346-025-02484-0
121. Time-Lapse Electrical Resistivity Tomography (TL-ERT) for Landslide Monitoring: Recent Advances and Future Directions V. Lapenna & A. Perrone 10.3390/app12031425
122. Multi-event assessment of typhoon-triggered landslide susceptibility in the Philippines J. Jones et al. 10.5194/nhess-23-1095-2023
123. Bayesian inverse analysis with field observation for slope failure mechanism and reliability assessment under rainfall accounting for nonstationary characteristics of soil properties X. Liu et al. 10.1016/j.sandf.2025.101568
124. Optimization of Factors of Safety and Displacements of Unsaturated Soil Slopes by the Bioinspired Metaheuristic Method K. Waris & B. Basha 10.1061/IJGNAI.GMENG-11282
125. Landslide detection from bitemporal satellite imagery using attention-based deep neural networks S. Amankwah et al. 10.1007/s10346-022-01915-6
126. A national landslide inventory for Denmark G. Luetzenburg et al. 10.5194/essd-14-3157-2022
127. Landslide Susceptibility Analysis Based on Dataset Construction of Landslides in Yiyang Using GIS and Machine Learning C. Hou et al. 10.3390/app15105597
128. 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
129. Rainfall triggers more deep-seated landslides than Cascadia earthquakes in the Oregon Coast Range, USA S. LaHusen et al. 10.1126/sciadv.aba6790
130. 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
131. Increasing landslide susceptibility in urbanized areas of Petrópolis identified through spatio-temporal analysis C. de Praga Baião et al. 10.1016/j.jsames.2025.105509
132. 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
133. 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
134. Landslide susceptibility assessment and attribution analysis in Yunnan Province based on weighted information value-logistic regression model Y. Zhu et al. 10.1080/19475705.2025.2525428
135. 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
136. Integrated Landslide Hazard Assessment Using Machine Learning, Rainfall Threshold, and RAMMS Based Rockfall Simulation in NH-05, Himachal Pradesh, India M. Singh et al. 10.1007/s12524-025-02173-4
137. Determination of the Probabilities of Landslide Events—A Case Study of Bhutan R. Sarkar & K. Dorji 10.3390/hydrology6020052
138. 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
139. Landslide Hazard and Rainfall Threshold Assessment: Incorporating Shallow and Deep-Seated Failure Mechanisms with Physics-Based Models R. Marin et al. 10.3390/geosciences14100280
140. The Role of Soil Type in Triggering Shallow Landslides in the Alps (Lombardy, Northern Italy) F. Luino et al. 10.3390/land11081125
141. 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
142. 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
143. 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
144. A Case Study of Using Numerical Analysis to Assess the Slope Stability of National Freeways in Northern Taiwan H. Chiu et al. 10.3390/app15020635
145. Historicizing Natural Hazards and Human-Induced Landscape Transformation in a Tropical Mountainous Environment in Africa: Narratives from Elderly Citizens V. Kanyiginya et al. 10.3390/land14020346
146. Dendrogeomorphic analysis of creep: possibilities and specifics of spatio-temporal reconstruction K. Šilhán 10.1007/s10346-024-02417-3
147. 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
148. A pseudo-3D methodology for regional-scale back-analysis of earthquake-induced landslides W. Gong et al. 10.1016/j.enggeo.2023.107277
149. Dynamic response evaluation of landslide to ambient noise using the HVSR method, the case of golay landslide in North Khorasan Province, Iran M. Hosseinzadeh et al. 10.1007/s10064-025-04311-1
150. 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
151. Using a Tank Model to Determine Hydro-Meteorological Thresholds for Large-Scale Landslides in Taiwan G. Lin et al. 10.3390/w12010253
152. GIS-Based Landslide Susceptibility Mapping for Land Use Planning and Risk Assessment A. Roccati et al. 10.3390/land10020162
153. The Impact of Bamboo on Rainfall-Triggered Landslide Distribution at the Regional Scale: A Case Study from SE China Z. Guo et al. 10.3390/f15122223
154. Study on rainfall infiltration characteristics and instability mechanism of a lateritic soil landslide in Yunnan, China C. Gu et al. 10.3389/feart.2024.1478570
155. 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
156. Application of Acoustic Emission Technique in Landslide Monitoring and Early Warning: A Review J. Song et al. 10.3390/app15031663
157. 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
158. 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
159. Natural hazards fatalities in Brazil, 1979–2019 G. de Azevedo Couto et al. 10.1007/s11069-023-06059-x
160. Assessment of an amended soil as a climate adaptive barrier: Element testing and physical modelling A. Rana et al. 10.1016/j.gete.2025.100693
161. 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
162. 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
163. Three-dimensional rockfall shape back analysis: methods and implications D. Bonneau et al. 10.5194/nhess-19-2745-2019
164. 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
165. Influence of buffer distance on environmental geological hazard susceptibility assessment Z. Wang et al. 10.1007/s11356-023-31739-3
166. 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
167. Revealing the Effect of Typhoons on the Stability of Residual Soil Slope by Wind Tunnel Test Z. Guo et al. 10.3390/f15050791
168. Topographic uncertainty quantification for flow-like landslide models via stochastic simulations H. Zhao & J. Kowalski 10.5194/nhess-20-1441-2020
169. Spatio-temporal cluster analysis of recent Italian landslides M. Tonini et al. 10.1080/17499518.2020.1861634
170. Laboratory Experiments of Surge Pressure Loads Acting on Downstream Dams and Reservoir Banks Caused by Landslides in Narrow, Elongated Reservoirs H. Wang et al. 10.3390/w17081133
171. 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
172. 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
173. Near-surface soil hydrothermal response feedbacks landslide activity and mechanism X. Ye et al. 10.1016/j.enggeo.2024.107690
174. Landslide Identification in UAV Images Through Recognition of Landslide Boundaries and Ground Surface Cracks Z. Cheng et al. 10.3390/rs17111900
175. A framework to optimize a designed geotechnical system probabilistically using MLP-ANN and ELECTERE decision making – a nailed wall study P. Dastpak et al. 10.1016/j.geoai.2025.100014
176. Spatial understanding of historical and future landslide variation in Africa L. Nahayo et al. 10.1007/s11069-023-06126-3
177. Landslides after wildfire: initiation, magnitude, and mobility F. Rengers et al. 10.1007/s10346-020-01506-3
178. 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
179. Overcoming the data limitations in landslide susceptibility modeling J. Woodard & B. Mirus 10.1126/sciadv.adt1541
180. Probabilistic Hydrological Estimation of LandSlides (PHELS): global ensemble landslide hazard modelling A. Felsberg et al. 10.5194/nhess-23-3805-2023
181. Assessment of cohesive soil landslide driving forces exerted on piles considering soil arching effects D. Xue et al. 10.1016/j.enggeo.2024.107825
182. Study on characteristics and impact of Kalikhola landslide, Manipur, NE India, using UAV photogrammetry R. Pattanaik & Y. Singh 10.1007/s11069-024-06484-6
183. 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
184. Effects of retained dry material on the impact, overflow and landing dynamics J. Fang et al. 10.1016/j.jrmge.2023.11.024
185. Deep learning approaches for landslide information recognition: Current scenario and opportunities N. Chandra & H. Vaidya 10.1007/s12040-024-02281-8
186. A Pattern‐Based Strategy for InSAR Phase Unwrapping and Application to Two Landslides in Colorado Y. Molan & R. Lohman 10.1029/2022JB025761
187. 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
188. Deep learning for geological hazards analysis: Data, models, applications, and opportunities Z. Ma & G. Mei 10.1016/j.earscirev.2021.103858
189. 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
190. INSPIRE standards as a framework for artificial intelligence applications: a landslide example G. Roberti et al. 10.5194/nhess-20-3455-2020
191. A hybrid machine learning model for landslide-oriented risk assessment of long-distance pipelines H. Wen et al. 10.1016/j.jenvman.2023.118177
192. An explainable AI (XAI) model for landslide susceptibility modeling B. Pradhan et al. 10.1016/j.asoc.2023.110324
193. The relation between rainfall and landslides in India: An empirical approach for prediction of landslide A. Roul et al. 10.1007/s12040-025-02551-z
194. 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
195. Soil Moisture Sensor-Based Landslide Monitoring: A Laboratory-Based Approach for Guwahati City M. Sharma & S. Laskar 10.37394/232033.2024.2.3
196. 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
197. 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
198. 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
199. Enhancing landslide susceptibility predictions with XGBoost and SHAP: a data-driven explainable AI method D. Khan et al. 10.1080/10106049.2025.2514725
200. Relationship between continuous or discontinuous of controlling factors and landslide susceptibility in the high-cold mountainous areas, China H. Shu et al. 10.1016/j.ecolind.2025.113313
201. Geologic controls of slow-moving landslides near the US West Coast Y. Xu et al. 10.1007/s10346-021-01732-3
202. Unsupervised active–transfer learning for automated landslide mapping Z. Wang & A. Brenning 10.1016/j.cageo.2023.105457
203. Topographic Analysis of Landslide Distribution Using AW3D30 Data A. Nonomura et al. 10.3390/geosciences10040115
204. A massive rock and ice avalanche caused the 2021 disaster at Chamoli, Indian Himalaya D. Shugar et al. 10.1126/science.abh4455
205. 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
206. 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
207. A Spatial Landslide Risk Assessment Based on Hazard, Vulnerability, Exposure, and Adaptive Capacity T. Tran et al. 10.3390/su16219574
208. 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
209. 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
210. A high-precision displacement prediction model for landslide geological hazards based on APSO-SVR-LSTM combination N. Wang et al. 10.3389/feart.2025.1597570
211. Granular flow simulation in a centrifugal acceleration field M. Cabrera et al. 10.1680/jgeot.18.P.260
212. Experimental study on the stability of vegetated earthen slopes under intense rainfall X. Song & Y. Tan 10.1016/j.still.2024.106028
213. 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
214. 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
215. Definition of 3D rainfall thresholds to increase operative landslide early warning system performances A. Rosi et al. 10.1007/s10346-020-01523-2
216. Rainfall Infiltration through Stratified Colluvial Deposits: Analytical Approach vs. Numerical Modelling P. Paronuzzi et al. 10.3390/geosciences14020053
217. 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
218. Rapid Detection of Landslides for the Timely Response of Disaster Mitigation and Relief D. Liu & G. Liu 10.1061/NHREFO.NHENG-2263
219. Analysis of Changes in Landslide Susceptibility according to Land Use over 38 Years in Lixian County, China J. Liu et al. 10.3390/su131910858
220. Artificial Intelligence: A new era for spatial modelling and interpreting climate-induced hazard assessment A. Dikshit et al. 10.1016/j.gsf.2024.101815
221. 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
222. 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
223. 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
224. 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
225. Utility of a swath laser rangefinder for characterizing mass movement flow depth and landslide initiation M. Obryk et al. 10.1007/s10346-025-02533-8
226. Impact Analysis of a Building Collapse Caused by a Rainfall-Induced Landslide in Kerala, India V. Santhosh Kumar & S. Chandrasekaran 10.3390/buildings12091395
227. 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
228. Landslide Susceptibility Prediction Considering Regional Soil Erosion Based on Machine-Learning Models F. Huang et al. 10.3390/ijgi9060377
229. 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
230. 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
231. Assessing landslide susceptibility based on hybrid Best-first decision tree with ensemble learning model H. Hong 10.1016/j.ecolind.2023.109968
232. Spatial dendrogeomorphic sampling based on the specific tree growth responses induced by the landslide mechanism K. Šilhán 10.1016/j.quageo.2020.101132
233. Machine Learning Reveals Lithology and Soil as Critical Parameters in Landslide Susceptibility for Petrópolis (Rio de Janeiro State, Brazil) E. Alcântara et al. 10.1016/j.nhres.2025.01.008
234. Developmental characteristics of rainfall-induced landslides from 1999 to 2016 in Wenzhou City of China H. Qin et al. 10.3389/feart.2022.1005199
235. Slit structures: Fundamental mechanisms of mechanical trapping of granular flows S. Goodwin & C. Choi 10.1016/j.compgeo.2019.103376
236. 30-year record of Himalaya mass-wasting reveals landscape perturbations by extreme events J. Jones et al. 10.1038/s41467-021-26964-8
237. Automating global landslide detection with heterogeneous ensemble deep-learning classification A. Ganerød et al. 10.1016/j.rsase.2024.101384
238. 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
239. Stability analysis of complex terrain slope based on multi-source point cloud fusion W. Zan et al. 10.1007/s11629-022-7307-8
240. “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
241. 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
242. 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
243. Landslide mapping with deep learning: the role of pre-/post-event SAR features and multi-sensor data fusion A. Orynbaikyzy et al. 10.1080/15481603.2025.2502214
244. 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
245. 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
246. Landslide inventory and susceptibility models considering the landslide typology using deep learning: Himalayas, India S. Bera et al. 10.1007/s11069-021-04731-8
247. 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
248. Landslide susceptibility and mobilization rates in the Mount Elgon region, Uganda J. Broeckx et al. 10.1007/s10346-018-1085-y
249. 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
250. Design of Miniaturized Sensing Unit for Underground Displacement 3-D Measurement Sensor N. Shentu et al. 10.1109/JSEN.2024.3452091
251. Increasing landslide deformation and activity in a changing local environment: a case study of Zhouqu County in the Bailong River Basin Z. Liu et al. 10.1007/s10064-025-04106-4
252. Geospatial distribution of landslide susceptibility modeling based on Remote Sensing and Geographic Information System K. Shitu & A. Tariq 10.1016/j.jafrearsci.2025.105732
253. Preliminary investigation of emerging suburban landsliding in Gisborne, New Zealand M. Cook et al. 10.1144/qjegh2021-087
254. An interpretable model for landslide susceptibility assessment based on Optuna hyperparameter optimization and Random Forest X. Xiao et al. 10.1080/19475705.2024.2347421
255. 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
256. 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
257. Factors controlling the formation and movement of clustered shallow landslides triggered by the extreme rainstorm in July 2023 in Beijing, China H. Ma & F. Wang 10.1016/j.geomorph.2025.109728
258. 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
259. Identify Landslide Precursors from Time Series InSAR Results M. Liu et al. 10.1007/s13753-023-00532-8
260. Tree rings indicate hazards related to a waterside landslide in the Northern Apennines, Italy – A preliminary step towards forecasting landslides and related tsunami I. Malik et al. 10.1016/j.dendro.2025.126379
261. 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
262. A Regional-Scale Landslide Early Warning System Based on the Sequential Evaluation Method: Development and Performance Analysis J. Park et al. 10.3390/app10175788
263. Estimating landslide sliding distance based on an improved Heim sled model Z. Zhang et al. 10.1016/j.catena.2021.105401
264. 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
265. Spatiotemporal distribution characteristics, causes, and prevention advice of fatal geohazards in Jiangxi Province, China C. Shao et al. 10.1016/j.scitotenv.2022.155337
266. A data-driven evaluation of post-fire landslide susceptibility E. Culler et al. 10.5194/nhess-23-1631-2023
267. A frictional weakening law of breakable granular flow influenced by shear velocity and normal stress Z. Liu et al. 10.1016/j.jrmge.2024.12.008
268. 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
269. 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
270. Türkiye Cumhuriyeti’nin 100. Yılında Türkiye Adresli Yayınların Dünya Heyelan Literatürüne Katkısı C. Gökçeoğlu 10.24232/jmd.1443848
271. Two Nitsche-based mixed finite element discretizations for the seepage problem in Richards’ equation F. Gatti et al. 10.1016/j.cma.2024.117368
272. Detecting the Vertical Structure of Extreme Precipitation in the Headwater Area of Yellow River Using the Dual‐Frequency Precipitation Radar Onboard the Global Precipitation Measurement Mission J. Song et al. 10.1002/joc.8675
273. Numerical modeling of seepage and deformation of unsaturated slope subjected to post-earthquake rainfall J. Xu et al. 10.1016/j.compgeo.2022.104791
274. Shear strain prediction of reservoir landslide based on FBG monitoring and bagging-MLP algorithm J. Wang et al. 10.1007/s10064-024-04076-z
275. Refined Zoning of Landslide Susceptibility: A Case Study in Enshi County, Hubei, China Z. Wang et al. 10.3390/ijerph19159412
276. Forecasting the magnitude of potential landslides based on InSAR techniques Y. Zhang et al. 10.1016/j.rse.2020.111738
277. Correlation between Acoustic Emission Behaviour and Dynamics Model during Three-Stage Deformation Process of Soil Landslide L. Deng et al. 10.3390/s21072373
278. Integration of Spatial Probability and Size in Slope-Unit-Based Landslide Susceptibility Assessment: A Case Study L. Li & H. Lan 10.3390/ijerph17218055
279. 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
280. Assessing the impact of climate change on landslides near Vejle, Denmark, using public data K. Svennevig et al. 10.5194/nhess-24-1897-2024
281. Assessing the impact of precipitation variability on landslide hazards in urbanized regions B. Du et al. 10.1016/j.jag.2025.104360
282. Spatiotemporal variations of fatal landslides in Turkey T. Görüm & S. Fidan 10.1007/s10346-020-01580-7
283. Integrated analysis of geophysical approaches for slope failure characterisation M. Zakaria et al. 10.1007/s12665-022-10410-z
284. The human cost of global warming: Deadly landslides and their triggers (1995–2014) U. Haque et al. 10.1016/j.scitotenv.2019.03.415
285. Landslide detection based on pixel-level contrastive learning for semi-supervised semantic segmentation in wide areas J. Lv et al. 10.1007/s10346-024-02425-3
286. 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
287. 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
288. 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
289. 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
290. 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
291. 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
292. Electrical Resistivity Tomography (ERT) Investigation for Landslides: Case Study in the Hunan Province, China M. Sun et al. 10.3390/app14073007
293. 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
294. 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
295. 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
296. Application of Bayesian Hyperparameter Optimized Random Forest and XGBoost Model for Landslide Susceptibility Mapping S. Wang et al. 10.3389/feart.2021.712240
297. Implementation of hydrometeorological thresholds for regional landslide warning in Catalonia (NE Spain) R. Palau et al. 10.1007/s10346-023-02094-8
298. Temporal patterns of nonseismically triggered landslides in Shaanxi Province, China H. Qiu et al. 10.1016/j.catena.2019.104356
299. 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
300. Changes in Human Vulnerability to Flood and Landslide: Evidences from Historical Data O. Petrucci 10.3390/su16166715
301. 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
302. 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
303. Space-time data-driven modeling of precipitation-induced shallow landslides in South Tyrol, Italy M. Moreno et al. 10.1016/j.scitotenv.2023.169166
304. Synoptic-scale precursors of landslides in the western Himalaya and Karakoram K. Hunt & A. Dimri 10.1016/j.scitotenv.2021.145895
305. Reconstruction of surface deformation characteristics in alpine canyons under shadow conditions Z. Gu & X. Yao 10.1007/s11629-021-7294-1
306. The relations between settlement and selected environmental features with regard to landslide hazard in the Polish Carpathians P. Śleszyński et al. 10.1016/j.catena.2025.108897
307. 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
308. 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
309. Coupled effects of earthquake and rainfall on landslide susceptibility in non-tropical coastal areas: assessing governing mechanisms and innovative slope protection strategy P. Khadka et al. 10.1007/s44290-025-00227-7
310. Combining remote sensing techniques and field surveys for post-earthquake reconnaissance missions G. Giardina et al. 10.1007/s10518-023-01716-9
311. 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
312. Evaluation of critical factors for typhoon-triggered landslide and subsequent debris flow in the Philippines using physically based models J. Christian Gaviola et al. 10.1051/e3sconf/202560401001
313. A participatory approach to determine the use of road cut slope design guidelines in Nepal to lessen landslides E. Robson et al. 10.5194/nhess-25-949-2025
314. 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
315. Research on the stability of loess landslides under seismic action based on simplified bishop method G. Hu et al. 10.3389/feart.2024.1490558
316. Integration of effective antecedent rainfall to improve the performance of rainfall thresholds for landslide early warning in Wanzhou District, China X. Liang et al. 10.1016/j.ijdrr.2025.105317
317. 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
318. 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
319. 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
320. Landslides forecasting using satellite rainfall estimations and machine learning in the Colombian Andean region D. Gómez et al. 10.1016/j.jsames.2023.104293
321. Analysis of an anthropogenically-induced landslide with emphasis on geological precursors M. Apon et al. 10.1016/j.rines.2024.100020
322. New global characterisation of landslide exposure R. Emberson et al. 10.5194/nhess-20-3413-2020
323. Utilizing deep learning for intelligent monitoring and early warning of slope disasters in public space design W. Ting & Y. Wang 10.3389/fenvs.2025.1536481
324. Systematic Quantification and Assessment of Digital Image Correlation Performance for Landslide Monitoring D. Hermle et al. 10.3390/geosciences13120371
325. 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
326. Dynamic Response and Failure Process of a Counter-Bedding Rock Slope under Strong Earthquake Conditions M. Guo et al. 10.3390/sym14010103
327. InSAR phase gradient reveals fault‐zone controls on the spatial distribution of slow‐moving landslides in the active orogenic region of Hazara‐Kashmir, Pakistan S. Ahmad et al. 10.1002/esp.6015
328. Entering the Era of Earth Observation-Based Landslide Warning Systems: A Novel and Exciting Framework K. Dai et al. 10.1109/MGRS.2019.2954395
329. 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
330. Landslide hazard assessment based on Bayesian optimization–support vector machine in Nanping City, China W. Xie et al. 10.1007/s11069-021-04862-y
331. 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
332. Mechanics of coseismic and postseismic acceleration of active landslides M. Kohler & A. Puzrin 10.1038/s43247-023-00797-3
333. 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
334. 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
335. Lethality level casualty assessment method for earthquake landslide hazards based on the expansion effect of the mortality rate X. Chaoxu et al. 10.1038/s41598-025-08209-6
336. Space-time landslide predictive modelling L. Lombardo et al. 10.1016/j.earscirev.2020.103318
337. Effect of basin morphometric parameters on physically-based rainfall thresholds for shallow landslides R. Marin et al. 10.1016/j.enggeo.2020.105855
338. Rapid Mapping of Rainfall-Induced Landslide Using Multi-Temporal Satellite Data M. Aman et al. 10.3390/rs17081407
339. Study on the Optimization of Pile Length of Micropiles in Soil Landslides H. Cheng et al. 10.3390/app13179980
340. 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
341. 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
342. Assessing landslide susceptibility based on hybrid multilayer perceptron with ensemble learning H. Hong 10.1007/s10064-023-03409-8
343. 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
344. Landslide topology uncovers failure movements K. Bhuyan et al. 10.1038/s41467-024-46741-7
345. Prototype of an IoT-Based Low-Cost Sensor Network for the Hydrological Monitoring of Landslide-Prone Areas P. Marino et al. 10.3390/s23042299
346. 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
347. Landslide precipitation thresholds in Rwanda J. Uwihirwe et al. 10.1007/s10346-020-01457-9
348. Empowerment of Farmer Institutions in Improving Farmer’s Bargaining Position M. Sasmi et al. 10.1088/1755-1315/1177/1/012001
349. 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
350. Geographically Weighted Random Forest Based on Spatial Factor Optimization for the Assessment of Landslide Susceptibility F. Lu et al. 10.3390/rs17091608
351. Landslide mapping from multi-sensor data through improved change detection-based Markov random field P. Lu et al. 10.1016/j.rse.2019.111235
352. Understanding fatal landslides at global scales: a summary of topographic, climatic, and anthropogenic perspectives S. Fidan et al. 10.1007/s11069-024-06487-3
353. Landslide spatial prediction using data-driven based statistical and hybrid computational intelligence algorithms X. Zhao et al. 10.1080/10106049.2025.2507919
354. Internet of Things Geosensor Network for Cost-Effective Landslide Early Warning Systems M. Gamperl et al. 10.3390/s21082609
355. Predicting the thickness of shallow landslides in Switzerland using machine learning C. Schaller et al. 10.5194/nhess-25-467-2025
356. A new strategy to map landslides with a generalized convolutional neural network N. Prakash et al. 10.1038/s41598-021-89015-8
357. Event-based rainfall-induced landslide inventories and rainfall thresholds for Malawi P. Niyokwiringirwa et al. 10.1007/s10346-023-02203-7
358. 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
359. Landslide Susceptibility Mapping in Xinjiang: Identifying Critical Thresholds and Interaction Effects Among Disaster-Causing Factors X. Feng et al. 10.3390/land14030555
360. LADI: Landslide displacement interpolation through a spatial-temporal Kalman filter A. Senogles et al. 10.1016/j.cageo.2023.105451
361. 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
362. Deformation Monitoring and Trend Analysis of Reservoir Bank Landslides by Combining Time-Series InSAR and Hurst Index X. Zhang et al. 10.3390/rs15030619
363. Global Dynamic Landslide Susceptibility Modeling Based on ResNet18: Revealing Large-Scale Landslide Hazard Evolution Trends in China H. Jiang et al. 10.3390/app15042038
364. 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
365. Mass exchange between geophysical flows and beds: Idealised computational modelling using a Herschel-Bulkley rheology S. Goodwin et al. 10.1051/e3sconf/202341501008
366. 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
367. Rainfall thresholds for shallow landslides considering rainfall temporal patterns B. Zhao et al. 10.1007/s10064-025-04144-y
368. Effects of pore water and pore air pressure on the slope failure mechanisms due to rainfall in centrifuge investigation M. Cho et al. 10.1186/s40677-024-00305-5
369. Integrating empirical models and satellite radar can improve landslide detection for emergency response K. Burrows et al. 10.5194/nhess-21-2993-2021
370. 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
371. Characteristics of Rainfall Events Triggering Landslides in Two Climatologically Different Areas: Southern Ecuador and Southern Spain J. Palenzuela Baena et al. 10.3390/hydrology7030045
372. 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
373. Application of a novel constitutive model to evaluate the shear deformation of discontinuity S. Xie et al. 10.1016/j.enggeo.2022.106693
374. 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
375. Integrating Physical and Machine Learning Models for Enhanced Landslide Prediction in Data-Scarce Environments H. Al-Najjar et al. 10.1007/s41748-024-00508-8
376. Integrated PSInSAR and SBAS-InSAR analysis for landslide detection and monitoring S. Hussain et al. 10.1016/j.pce.2025.103956
377. Efficient Identification and Monitoring of Landslides by Time-Series InSAR Combining Single- and Multi-Look Phases Z. Liu et al. 10.3390/rs14041026
378. Prediction of landslide block movement based on Kalman filtering data assimilation method Y. Liu et al. 10.1007/s11629-023-7902-3
379. Improved landslide prediction by considering continuous and discrete spatial dependency Z. Fang et al. 10.1007/s10346-024-02431-5
380. Experimental investigation on impact fragmentation and deposit characteristics of rockslides M. Ma et al. 10.1007/s10064-024-04053-6
381. 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
382. 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
383. Climate change-induced shifts in landslide susceptibility in São Sebastião (southeastern Brazil) E. Alcântara et al. 10.1016/j.nhres.2024.11.005
384. Objectives and main results of “Community Participation for Landslide Disaster Risk Reduction” thematic papers J. Klimeš et al. 10.1007/s10346-019-01246-z
385. Landslide Susceptibility Analysis: A Logistic Regression Model Case Study in Coonoor, India E. Sujatha & V. Sridhar 10.3390/hydrology8010041
386. 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
387. Landslide risk assessment based on susceptibility and vulnerability J. Mosaffaie et al. 10.1007/s10668-023-03093-4
388. 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
389. Influence of Calculation Parameters on the Slope Stability of the Historical Rasos Cemetery in Vilnius (Lithuania) R. Chmielewski et al. 10.3390/su16072891
390. 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
391. Deep learning forecast of rainfall-induced shallow landslides A. Mondini et al. 10.1038/s41467-023-38135-y
392. Landslide Risk Assessment in a Century-Old Tea Plantation Range Following Monsoonal Extremes in the Western Ghats of Kerala, India K. George et al. 10.1007/s44177-024-00082-8
393. 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
394. A ground instabilities inventory between Tetouan and Jebha (Morocco): mapping, description and analysis H. Tribak et al. 10.1007/s10064-023-03161-z
395. Landslide Inventory in the Downstream of the Niulanjiang River with ALOS PALSAR and Sentinel-1 Datasets Z. Wang et al. 10.3390/rs14122873
396. Sustainability Nexus AID: landslides and land subsidence M. Motagh et al. 10.1007/s00550-024-00549-7
397. Landslide risk index map at the municipal scale for Costa Rica A. Quesada-Román 10.1016/j.ijdrr.2021.102144
398. 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
399. 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
400. 3D displacement time series prediction of a north-facing reservoir landslide powered by InSAR and machine learning F. Chang et al. 10.1016/j.jrmge.2024.10.033
401. 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
402. 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
403. 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
404. Advancing predictive accuracy of shallow landslide using strategic data augmentation H. Qiu et al. 10.1016/j.jrmge.2024.09.010
405. 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
406. 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
407. Forecasting landslides using SIGMA model: a case study from Idukki, India M. Abraham et al. 10.1080/19475705.2021.1884610
408. The importance of input data on landslide susceptibility mapping K. Gaidzik & M. Ramírez-Herrera 10.1038/s41598-021-98830-y
409. Landslides caught on seismic networks and satellite radars A. Manconi & A. Mondini 10.5194/nhess-22-1655-2022
410. Biomechanical analysis head–neck injuries against mine falls using a simplified human model R. Garg et al. 10.1007/s12046-022-02028-5
411. Effect of the infiltration of simulated rains on soil organic carbon content and mud rheology M. Minale et al. 10.1063/5.0260301
412. 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
413. 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
414. Performance Study of Landslide Detection Using Multi-Temporal SAR Images Y. Lin et al. 10.3390/rs14102444
415. Early warning system for risk assessment in geotechnical engineering using Kolmogorov-Arnold networks S. Lin et al. 10.1016/j.jrmge.2025.02.023
416. Landslide deformation velocity real-time monitoring based on time-differenced carrier phase and its fault detection method Z. Bai et al. 10.1016/j.measurement.2024.116333
417. Deformation response and mechanism induced by rainfall of the Zhoujia landslide in Southwestern China S. Chen et al. 10.1007/s11069-025-07110-9
418. 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
419. Is the Grain Size Distribution a Key Parameter for Explaining the Long Runout of Granular Avalanches? M. Cabrera & N. Estrada 10.1029/2021JB022589
420. 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
421. Landslide utilization and driving mechanisms in alpine gorge areas of the eastern Qinghai–Tibet Plateau T. Qi et al. 10.1016/j.catena.2024.108677
422. Seismic-induced landslides susceptibility mapping of the NEOM area, northwestern Saudi Arabia using machine learning models B. El-Haddad et al. 10.1007/s12145-025-01864-3
423. 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
424. 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
425. 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
426. 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
427. 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
428. 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
429. The DEM Registration Method Without Ground Control Points for Landslide Deformation Monitoring Y. Wang et al. 10.3390/rs16224236
430. Hong Kong’s landslip warning system—40 years of progress V. Kong et al. 10.1007/s10346-020-01379-6
431. 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
432. 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
433. 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
434. Automatic recognition of active landslides by surface deformation and deep learning X. Wang et al. 10.1177/03091333241276523
435. Fast physically-based model for rainfall-induced landslide susceptibility assessment at regional scale V. Medina et al. 10.1016/j.catena.2021.105213
436. Endurance of MICP-Treated Soils under Rainfall-Drying Cycles: Insights into Erosion and Hydrologic Responses on Slopes R. Devrani et al. 10.2139/ssrn.5225564
437. Landslide hazard mapping in Chefchaouen, Morocco: AHP-GIS integration L. Dahmani et al. 10.1080/00207233.2024.2412483
438. 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
439. Numerical Simulation Study on Dominant Factors of Surge Hazards in Semi-Submerged Landslides J. Lei et al. 10.3390/w17010022
440. 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
441. 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
442. Potential of satellite-derived hydro-meteorological information for landslide initiation thresholds in Rwanda J. Uwihirwe et al. 10.5194/nhess-22-3641-2022
443. 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
444. Landslide susceptibility mapping of Phewa Watershed, Kaski, Nepal B. Kunwar et al. 10.21595/mme.2024.24231
445. Assessing the Effects of LULC Change on Landslide Hazards in Rwanda N. Hafashimana et al. 10.14232/jengeo-2022-44169
446. 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
447. Numerical Modelling of Debris Flows for Simulation-Based Decision Support: An Indian Perspective M. Abraham et al. 10.1007/s40098-024-00988-5
448. Study on Shallow Landslide Induced by Extreme Rainfall: A Case Study of Qichun County, Hubei, China Y. Li et al. 10.3390/w17040530
449. 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
450. SUSCEPTIBILITY MODELLING OF LANDSLIDES IN CENTRAL NEPAL O. IVANIK et al. 10.17721/1728-2713.107.01
451. Machine Learning: New Potential for Local and Regional Deep-Seated Landslide Nowcasting A. van Natijne et al. 10.3390/s20051425
452. Relationships between earthquakes, hurricanes, and landslides in Costa Rica A. Quesada-Román et al. 10.1007/s10346-019-01209-4
453. 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
454. 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
455. Enhancing the reliability of landslide early warning systems by machine learning H. Thirugnanam et al. 10.1007/s10346-020-01453-z
456. 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
457. 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
458. 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
459. Combining seismic signal dynamic inversion and numerical modeling improves landslide process reconstruction Y. Yan et al. 10.5194/esurf-10-1233-2022
460. 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
461. Temporal Probability Assessment and Its Use in Landslide Susceptibility Mapping for Eastern Bhutan A. Dikshit et al. 10.3390/w12010267
462. Prompt Quantitative Risk Assessment for Rain-Induced Landslides J. He et al. 10.1061/JGGEFK.GTENG-10980
463. 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
464. Comparison of Three Mixed-Effects Models for Mass Movement Susceptibility Mapping Based on Incomplete Inventory in China Y. He & Y. Zhang 10.3390/rs14236068
465. Global connections between El Nino and landslide impacts R. Emberson et al. 10.1038/s41467-021-22398-4
466. Cyclic landslide-flood chains along a major mountain river Y. Yang et al. 10.1016/j.geomorph.2023.108835
467. Project ‘‘Mass Movements in Germany’’ and its implications for nationwide landslide susceptibility assessment J. Torizin et al. 10.1007/s10064-024-03691-0
468. 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
469. 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
470. Harmonized methodology for cross-border hazard and risk assessment of earthquake-induced landslides at regional scale J. Bojadjieva et al. 10.1007/s10346-025-02505-y
471. Thermal Remote Sensing from UAVs: A Review on Methods in Coastal Cliffs Prone to Landslides M. Melis et al. 10.3390/rs12121971
472. Effects of hysteretic soil water characteristic curves on the hydromechanical behaviour Y. Yang & H. Yeh 10.1007/s12040-023-02146-6
473. 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
474. Invited perspectives: Mountain roads in Nepal at a new crossroads K. Sudmeier-Rieux et al. 10.5194/nhess-19-655-2019
475. Landslide Susceptibility Mapping Using Feature Fusion-Based CPCNN-ML in Lantau Island, Hong Kong Y. Chen et al. 10.1109/JSTARS.2021.3066378
476. Enhancing disaster risk resilience using greenspace in urbanising Quito, Ecuador C. Watson et al. 10.5194/nhess-22-1699-2022
477. A comparative analysis of mesh-based and particle-based numerical methods for landslide run-out simulations M. Fois et al. 10.1016/j.compfluid.2025.106641
478. Landslide Segmentation with Deep Learning: Evaluating Model Generalization in Rainfall-Induced Landslides in Brazil L. Soares et al. 10.3390/rs14092237
479. Integrated analysis of landslide susceptibility: geotechnical insights, frequency ratio method, and hazard mitigation strategies in a volcanic terrain B. Momene Tuwa et al. 10.1007/s12517-025-12221-5
480. Landslide monitoring techniques in the Geological Surveys of Europe M. Auflič et al. 10.1007/s10346-022-02007-1
481. Landslide displacement forecasting using deep learning and monitoring data across selected sites L. Nava et al. 10.1007/s10346-023-02104-9
482. Regional-scale InSAR investigation and landslide early warning thresholds in Umbria, Italy F. Ponziani et al. 10.1016/j.enggeo.2023.107352
483. 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
484. Spatial Coupling and Resilience Differentiation Characteristics of Landscapes in Populated Karstic Areas in Response to Landslide Disaster Risk: An Empirical Study from a Typical Karst Province in China H. Zhou et al. 10.3390/land14040847
485. 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
486. 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
487. Global projections of future landslide susceptibility under climate change Y. Duan et al. 10.1016/j.gsf.2025.102074
488. Landslide Deformation Analysis and Prediction with a VMD-SA-LSTM Combined Model C. Wen et al. 10.3390/w16202945
489. Quantification of meteorological conditions for rockfall triggers in Germany K. Nissen et al. 10.5194/nhess-22-2117-2022
490. State-of-the-Art Review on the Use of Micropiles in Slope/Landslide Protection Measures B. Otoma & R. Ayothiraman 10.1007/s40098-025-01190-x
491. 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
492. How can landslide risk maps be validated? Potential solutions with open-source databases F. Caleca et al. 10.3389/feart.2022.998885
493. Zonation of Landslide Susceptibility in Ruijin, Jiangxi, China X. Zhou et al. 10.3390/ijerph18115906
494. 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
495. Landslide Prediction Method Based on a Ground-Based Micro-Deformation Monitoring Radar L. Qi et al. 10.3390/rs12081230
496. Satellite rainfall products outperform ground observations for landslide prediction in India M. Brunetti et al. 10.5194/hess-25-3267-2021
497. 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
498. Preface to the Special Issue “Rainfall Thresholds and Other Approaches for Landslide Prediction and Early Warning” S. Segoni et al. 10.3390/w13030323
499. 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
500. Seismotectonic and anthropogenic factors controlling landslide hazard in Gafsa phosphates quarries I. Mahmoudi et al. 10.1007/s10064-024-03747-1
501. The May 2023 Rainstorm-Induced Landslides in the Emilia-Romagna Region (Northern Italy): Considerations from UAV Investigations Under Emergency Conditions L. Schilirò et al. 10.3390/geosciences15030101
502. Landslide Susceptibility Mapping Considering Landslide Spatial Aggregation Using the Dual-Frequency Ratio Method: A Case Study on the Middle Reaches of the Tarim River Basin X. Yi et al. 10.3390/rs17030381
503. SAR data and field surveys combination to update rainfall-induced shallow landslide inventory P. Miele et al. 10.1016/j.rsase.2022.100755
504. Global landslide mapping using tibetan plateau landslide dataset and improved YOLOX D. Liu et al. 10.1007/s12145-025-01825-w
505. Landslide Detection Based on Differential Fusion of Multi‐Level Features From Optical Remote Sensing Images and Topographical Data S. Guo et al. 10.1111/tgis.70046
506. 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
507. 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
508. A Modeling Platform for Landslide Stability: A Hydrological Approach M. Emadi-Tafti & B. Ataie-Ashtiani 10.3390/w11102146
509. Spatial and temporal landslide distributions using global and open landslide databases D. Gómez et al. 10.1007/s11069-023-05848-8
510. An Infrared Thermography Approach to Evaluate the Strength of a Rock Cliff M. Loche et al. 10.3390/rs13071265
511. Evaluation of Relative Active Tectonics and the Spatial Distribution of Landslides in the Yamne Valley (Arunachal Pradesh), Northeastern Himalaya, India P. Maurya et al. 10.1002/gj.5197
512. 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
513. Inventory of shallow landslides triggered by extreme precipitation in July 2023 in Beijing, China H. Ma & F. Wang 10.1038/s41597-024-03901-0
514. 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
515. Effects of debris flow rheology on overflow and impact dynamics against dual-rigid barriers C. Ng et al. 10.1680/jgeot.21.00226
516. 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
517. Unmanned Aerial Vehicles (UAVs) in Landslide Investigation and Monitoring: A Review J. Sun et al. 10.3390/drones8010030
518. Failure mechanism and landslide fragility of reinforced concrete buildings considering uncertain flow properties M. Kulariya & S. Saha 10.1080/17499518.2024.2337377
519. Statistical-spatial modeling of the potential of landslide occurrence in Yamchi catchment F. Pourfarrashzadeh et al. 10.61186/jsaeh.11.1.4
520. 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
521. Data-Driven Landslide Nowcasting at the Global Scale T. Stanley et al. 10.3389/feart.2021.640043
522. 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
523. Strategic protection of landslide vulnerable mountains for biodiversity conservation under land-cover and climate change impacts B. Li et al. 10.1073/pnas.2113416118
524. Keynote lecture. Landslide Early Warning Systems: Resources or Problems? F. Guzzetti et al. 10.1051/e3sconf/202341503010
525. Vadose Zone Thickness Limits Pore‐Fluid Pressure Rise in a Large, Slow‐Moving Earthflow C. Murphy et al. 10.1029/2021JF006415
526. 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
527. Recent advancements of landslide hydrology R. Greco et al. 10.1002/wat2.1675
528. 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
529. Contrasting Population Projections to Induce Divergent Estimates of Landslides Exposure Under Climate Change Q. Lin et al. 10.1029/2023EF003741
530. Q-Slope: Rock Slope Engineering 10 Years on N. Bar & N. Barton 10.1007/s00603-024-04064-5
531. Geological and Geomorphological Characterization of the Anthropogenic Landslide of Pie de la Cuesta in the Vitor Valley, Arequipa, Peru R. Infa et al. 10.3390/geosciences14110291
532. Assessing torrentiality in catchments of the tropical Andes: A morphometric approach S. Machuca et al. 10.1016/j.jsames.2023.104775
533. A new global landslide dam database (RAGLAD) and analysis utilizing auxiliary global fluvial datasets H. Wu et al. 10.1007/s10346-021-01817-z
534. 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
535. High-resolution geophysical monitoring of moisture accumulation preceding slope movement—a path to improved early warning A. Watlet et al. 10.1088/1748-9326/ad8fbe
536. The dynamic threat from landslides following large continental earthquakes K. Arrell et al. 10.1371/journal.pone.0308444
537. Integrated deep learning with explainable artificial intelligence for enhanced landslide management S. Alqadhi et al. 10.1007/s11069-023-06260-y
538. Understanding slow-moving landslide triggering processes using low-cost passive seismic and inclinometer monitoring S. Fiolleau et al. 10.1016/j.jappgeo.2023.105090
539. Data-driven landslide forecasting: Methods, data completeness, and real-time warning T. Xiao & L. Zhang 10.1016/j.enggeo.2023.107068
540. A QGIS framework for physically-based probabilistic modelling of landslide susceptibility: QGIS-FORM J. Ji et al. 10.1016/j.envsoft.2024.106258
541. Modeling impacts of climate change on return period of landslide triggering D. Peres & A. Cancelliere 10.1016/j.jhydrol.2018.10.036
542. A CONCEPTUAL STUDY ON METHODOLOGIES FOR LANDSLIDE HAZARD: INVENTORIES, SUSCEPTIBILITY, VULNERABILITY, AND RISK ANALYSIS A. Taye & R. Tamang 10.29121/granthaalayah.v13.i4.2025.6139
543. 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
544. Forecasting the time of failure of landslides at slope-scale: A literature review E. Intrieri et al. 10.1016/j.earscirev.2019.03.019
545. 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
546. Landslide Susceptibility Mapping with Integrated SBAS-InSAR Technique: A Case Study of Dongchuan District, Yunnan (China) Z. Zhu et al. 10.3390/s22155587
547. 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
548. Time-varying baseline error correction method for ground-based micro-deformation monitoring radar T. Lei et al. 10.23919/JSEE.2022.000091
549. InSAR-based landslide detection method with the assistance of C-index Z. Xiong et al. 10.1007/s10346-023-02120-9
550. Prediction of Landslide Susceptibility in the Karakorum under the Context of Climate Change Y. Pei et al. 10.3390/app14188562
551. Improvement of failure time prediction of rainfall-induced landslides while reducing the fluctuation by the relationship between velocity and acceleration I. Ariyarathna & K. Sasahara 10.1186/s40677-025-00313-z
552. Applying GIS to monitor the Schools’ exposure to landslide hazards in disaster-prone areas of Mount Elgon in Uganda F. Akello et al. 10.1080/19376812.2025.2480390
553. Automated Snow Avalanche Monitoring and Alert System Using Distributed Acoustic Sensing in Norway A. Turquet et al. 10.3390/geohazards5040063
554. Field data driven rockfall hazard and risk assessment along Sangla-Chitkul road, Himachal Pradesh, India V. Pandey et al. 10.1007/s10064-025-04286-z
555. A Robust SAR Speckle Tracking Workflow for Measuring and Interpreting the 3D Surface Displacement of Landslides D. Donati et al. 10.3390/rs13153048
556. Post-failure landslide change detection and analysis using optical satellite Sentinel-2 images F. Qu et al. 10.1007/s10346-020-01498-0
557. 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
558. 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
559. Development of a Landslide Early Warning System in Indonesia R. Hidayat et al. 10.3390/geosciences9100451
560. How much does the rainfall temporal resolution affect rainfall thresholds for landslide triggering? S. Gariano et al. 10.1007/s11069-019-03830-x
561. Recent rainfall-induced landslides in East Khasi Hills, Meghalaya, Northeast India N. Badavath et al. 10.1007/s10346-024-02406-6
562. 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
563. Controls on the size distributions of shallow landslides D. Bellugi et al. 10.1073/pnas.2021855118
564. Simultaneous state–parameter estimation of rainfall-induced landslide displacement using data assimilation J. Wang et al. 10.5194/nhess-19-1387-2019
565. 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
566. Comparison between Deep Learning and Tree-Based Machine Learning Approaches for Landslide Susceptibility Mapping S. Saha et al. 10.3390/w13192664
567. Landslide displacement prediction based on time series and long short-term memory networks A. Jin et al. 10.1007/s10064-024-03714-w
568. Towards a predictive multi-phase model for alpine mass movements and process cascades A. Cicoira et al. 10.1016/j.enggeo.2022.106866
569. A predictive model of societal landslide risk in Italy M. Rossi et al. 10.1016/j.earscirev.2019.04.021
570. 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
571. 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
572. Standards for shallow landslide identification in Brazil: Spatial trends and inventory mapping H. Dias & C. Grohmann 10.1016/j.jsames.2024.104805
573. Formation mechanism and evolution of the Jiaju landslide in the Dadu River, China Y. Bai et al. 10.1007/s10064-024-03611-2
574. Natural Disaster Risk Inequalities in Central America A. Quesada-Román & D. Campos-Durán 10.1080/23754931.2022.2081814
575. Landslide displacement prediction based on Variational mode decomposition and MIC-GWO-LSTM model Z. Taorui et al. 10.1007/s00477-021-02145-3
576. Rock slope failure preparation paced by total crack boundary length S. Lagarde et al. 10.1038/s43247-023-00851-0
577. 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
578. Superpixel and Supervoxel Segmentation Assessment of Landslides Using UAV-Derived Models I. Farmakis et al. 10.3390/rs14225668
579. Stability Analysis of Himalayan Rock Slope Incorporating Microstructures into Rock Mass Using DEM P. Singh & S. Pradhan 10.1007/s10706-025-03072-8
580. 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
581. A Geotechnical Investigation of 2017 Chattogram Landslides M. Islam et al. 10.3390/geosciences11080337
582. 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
583. A Simple Model for Estimating the Hydraulic Conductivity of Unsaturated Soil Z. Zhang & M. Zhang 10.3390/app14031254
584. 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
585. Detection and prediction of slope stability in unsaturated finite slopes using interpretable machine learning K. Waris et al. 10.1007/s40808-025-02454-4
586. Assessing the potential of soil moisture measurements for regional landslide early warning A. Wicki et al. 10.1007/s10346-020-01400-y
587. Advancements in soil management: Optimizing crop production through interdisciplinary approaches R. Srivastava et al. 10.1016/j.jafr.2024.101528
588. Investigation of rainfall intensity on the slope failure process using GPU-accelerated coupled MPM D. Wang et al. 10.1016/j.compgeo.2023.105718
589. 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
590. Climate Resilient Cities Assessing Differential Vulnerability to Climate Hazards in Urban India L. Rangwala et al. 10.46830/wrirpt.22.00055
591. Exploring time series models for landslide prediction: a literature review K. Ebrahim et al. 10.1186/s40677-024-00288-3
592. Assessing Global Landslide Casualty Risk Under Moderate Climate Change Based on Multiple GCM Projections X. Wang et al. 10.1007/s13753-023-00514-w
593. Multicollinearity and spatial correlation analysis of landslide conditioning factors in Langat River Basin, Selangor S. Selamat et al. 10.1007/s11069-024-06903-8
594. 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
595. Phenomenology of Avalanche Recordings From Distributed Acoustic Sensing P. Paitz et al. 10.1029/2022JF007011
596. Failure Mechanism and Movement Process Inversion of Rainfall-Induced Landslide in Yuexi Country Y. Xiao et al. 10.3390/su17125639
597. Landslide susceptibility prediction using frequency ratio model: a case study of Uttarakhand, Himalaya (India) P. Singh et al. 10.1007/s43538-023-00171-z
598. Spatiotemporal patterns of non-seismic fatal landslides in China from 2010 to 2022 Z. Li et al. 10.1007/s10346-024-02362-1
599. Assessment of Landslide Hazard in Jiangxi Using Geo-information Technology P. Ou et al. 10.3389/feart.2021.648342
600. 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
601. 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
602. Geoinformatic Analysis of Rainfall-Triggered Landslides in Crete (Greece) Based on Spatial Detection and Hazard Mapping A. Argyriou et al. 10.3390/su14073956
603. A decrease in rockfall probability under climate change conditions in Germany K. Nissen et al. 10.5194/nhess-23-2737-2023
604. Regional-scale landslide risk assessment in Central Asia F. Caleca et al. 10.5194/nhess-24-13-2024
605. 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
606. 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
607. 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
608. Approximate water vertical infiltration extremum path in unsaturated soils J. Li et al. 10.1016/j.jhydrol.2023.129989
609. Study on movement characteristics of landslide considering earthquake magnitude and duration time P. Jing et al. 10.1007/s10064-025-04182-6
610. 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
611. Are the historically known landslide events really the biggest? An insight using dendrogeomorphology K. Šilhán 10.1007/s10346-024-02354-1
612. Risk assessment of landslide casualty under incomplete information——Tienshan and Kunlun Mountainous regions of Central Asia X. Chen et al. 10.1016/j.ijdrr.2024.105057
613. 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
614. Landslide prediction based on low-cost and sustainable early warning systems with IoT Y. Liu et al. 10.1007/s10064-023-03137-z
615. Slow-moving landslide risk assessment combining Machine Learning and InSAR techniques A. Novellino et al. 10.1016/j.catena.2021.105317
616. 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
617. After 2000 Stože Landslide: Part II - Development of landslide disaster risk reduction policy in Slovenia M. Mikoš 10.15292/acta.hydro.2021.04
618. Estimating rainfall threshold and temporal probability for landslide occurrences in Darjeeling Himalayas A. Dikshit et al. 10.1007/s12303-020-0001-3
619. A review of landslide acceptable risk and tolerable risk K. Sim et al. 10.1186/s40677-022-00205-6
620. Semantic segmentation of landslide image using DeepLabv3+ and completed local binary pattern W. Wang et al. 10.1117/1.JRS.19.014502
621. 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
622. Landslide Hazard Assessment of Kashmir 10.47485/2766-2624.1048
623. 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
624. 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
625. Accurate IoT Based Slope Instability Sensing System for Landslide Detection N. Kumar M. & M. Ramesh 10.1109/JSEN.2022.3189903
626. 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
627. 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
628. Topographic controls on landslide mobility: modeling hurricane-induced landslide runout and debris-flow inundation in Puerto Rico D. Brien et al. 10.5194/nhess-25-1229-2025
629. 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
630. Exploring the multiple land degradation pathways across the planet R. Prăvălie 10.1016/j.earscirev.2021.103689
631. A Scientometric Analysis of Predicting Methods for Identifying the Environmental Risks Caused by Landslides Y. Zou & C. Zheng 10.3390/app12094333
632. 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
633. Landslide Scenario in India with Special Reference to the Himalaya and Community Resilience to Hazards G. Bhat 10.17491/jgsi/2024/174010
634. Different sampling strategies for predicting landslide susceptibilities are deemed less consequential with deep learning J. Dou et al. 10.1016/j.scitotenv.2020.137320
635. Optimization of SVR and CatBoost models using metaheuristic algorithms to assess landslide susceptibility R. Ajin et al. 10.1038/s41598-024-72663-x
636. The Post-Failure Spatiotemporal Deformation of Certain Translational Landslides May Follow the Pre-Failure Pattern L. Wang et al. 10.3390/rs14102333
637. Machine learning for landslides prevention: a survey Z. Ma et al. 10.1007/s00521-020-05529-8
638. Analysis of the fundamental differences between dam-forming landslides and all landslides H. Wu et al. 10.1016/j.geomorph.2025.109665
639. Towards a Transferable Antecedent Rainfall—Susceptibility Threshold Approach for Landsliding E. Monsieurs et al. 10.3390/w11112202
640. Landslide Susceptibility Mapping Considering Landslide Local-Global Features Based on CNN and Transformer Z. Zhao et al. 10.1109/JSTARS.2024.3379350
641. 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
642. Adaptive modeling of landslide susceptibility using Analytical Hierarchy Process and Multi-Objective Decision Optimization Y. Mao et al. 10.1016/j.asr.2024.12.061
643. InSAR-based deformation analysis around the Qiaoqi reservoir, Baoxing, Southwest China M. Kamran et al. 10.1007/s12665-025-12135-1
644. Unravelling long-term spatiotemporal deformation and hydrological triggers of slow-moving reservoir landslides with multi-platform SAR data F. Chang et al. 10.1016/j.jag.2024.104301
645. 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
646. A new method of monitoring slope displacement using millimeter wave radar J. Wang et al. 10.1007/s10346-024-02441-3
647. Assessing landslide susceptibility using geospatial technology in Bonga town, southwestern Ethiopia M. Melese & S. Gashure 10.1080/19376812.2023.2172054
648. Brief communication: Introducing rainfall thresholds for landslide triggering based on artificial neural networks P. Distefano et al. 10.5194/nhess-22-1151-2022
649. Low-Power and Wireless Communication Research on Underground Displacement Three-Dimensional Monitoring System N. Shentu et al. 10.3390/s24051592
650. Prediction of small-strain elastic stiffness of natural and artificial soft rocks subjected to freeze-thaw cycles M. Ali et al. 10.1016/j.jrmge.2024.09.060
651. 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
652. Global landslide susceptibility prediction based on the automated machine learning (AutoML) framework G. Tang et al. 10.1080/10106049.2023.2236576
653. 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
654. 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
655. Implications of landslide inventory in susceptibility modeling along a Himalayan highway corridor, India V. Pandey et al. 10.1080/02723646.2021.1872857
656. Landslide Susceptibility Mapping in Brazil: A Review H. Dias et al. 10.3390/geosciences11100425
657. Landslide Susceptibility Assessment Model Construction Using Typical Machine Learning for the Three Gorges Reservoir Area in China J. Cheng et al. 10.3390/rs14092257
658. Remote Sensing-Based Detection and Analysis of Slow-Moving Landslides in Aba Prefecture, Southwest China J. Ren et al. 10.3390/rs17081462
659. Spatiotemporal analysis and threshold modeling of rainfall-induced geological disasters in Anhui Province B. Wang et al. 10.3389/feart.2025.1541242
660. 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
661. Machine learning ensemble modelling as a tool to improve landslide susceptibility mapping reliability M. Di Napoli et al. 10.1007/s10346-020-01392-9
662. Enhancing Landslide Vulnerability Mapping Through Automated Fuzzy Logic Algorithm-Based Methodology A. Bruzón et al. 10.1007/s10706-023-02714-z
663. Evaluation of neural network models for landslide susceptibility assessment Y. Yi et al. 10.1080/17538947.2022.2062467
664. Field, experimental and numerical study for landslide mitigation in Himachal Pradesh, India: Case study A. Tiwari et al. 10.1007/s10064-025-04207-0
665. Effect of time and space partitioning strategies of samples on regional landslide susceptibility modelling K. Khanna et al. 10.1007/s10346-021-01627-3
666. 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
667. 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
668. Analysis of human exposure to landslides with a GIS multiscale approach S. Modugno et al. 10.1007/s11069-021-05186-7
669. 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
670. 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
671. 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
672. Research on the Landslide Prediction Based on the Dual Mutual-Inductance Deep Displacement 3D Measuring Sensor N. Shentu et al. 10.3390/app13010213
673. 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
674. Inventory of Landslides in the Northern Half of the Taihang Mountain Range, China X. Zhang et al. 10.3390/geosciences14030074
675. Emergency Disposal Solution for Control of a Giant Landslide and Dammed Lake in Yangtze River, China G. Chen et al. 10.3390/w11091939
676. HazMapper: a global open-source natural hazard mapping application in Google Earth Engine C. Scheip & K. Wegmann 10.5194/nhess-21-1495-2021
677. Landslide Susceptibility Mapping Using Machine Learning: A Case Study of Oregon B. Wu et al. 10.1088/1755-1315/1334/1/012032
678. 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
679. FLIDND-MCN: Fake label images detection of natural disasters with multi model convolutional neural network S. Alqhtani 10.3233/JIFS-213308
680. Time series analysis and long short-term memory neural network to predict landslide displacement B. Yang et al. 10.1007/s10346-018-01127-x
681. 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
682. “Satark”: Landslide Prediction System over Western Ghats of India J. Kulkarni et al. 10.3390/land11050689
683. Deep Learning for Exploring Landslides with Remote Sensing and Geo-Environmental Data: Frameworks, Progress, Challenges, and Opportunities Q. Zhang & T. Wang 10.3390/rs16081344
684. 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
685. 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
686. 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
687. 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
688. 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
689. 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
690. Development of a framework for the prediction of slope stability using machine learning paradigms K. Rajan et al. 10.1007/s11069-024-06819-3
691. Rainfall-induced landslide (RFIL) disaster in Dima Hasao, Assam, Northeast India S. Das et al. 10.1007/s10346-022-01962-z
692. Catastrophic landslide triggered by extreme rainfall in Chongqing, China: July 13, 2020, Niuerwan landslide C. Zhou et al. 10.1007/s10346-022-01911-w
693. Insights into landslide susceptibility in different karst erosion landforms based on interpretable machine learning D. Sun et al. 10.1002/esp.5748
694. Characterization of the Fels Landslide (Alaska) Using Combined Terrestrial, Aerial, and Satellite Remote Sensing Data D. Donati et al. 10.3390/rs16010117
695. 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
696. Influence of spatial heterogeneity on landslide susceptibility in the transboundary area of the Himalayas H. Sun et al. 10.1016/j.geomorph.2023.108723
697. 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
698. Evaluating the uncertainty in landslide susceptibility prediction: effect of spatial data variability and evaluation unit choices S. Qin et al. 10.1007/s10064-025-04180-8
699. Seasonal Landslide Activity Lags Annual Precipitation Pattern in the Pacific Northwest L. Luna & O. Korup 10.1029/2022GL098506
700. 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
701. 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
702. Optimization of Turbulence Model Parameters Using the Global Search Method Combined with Machine Learning K. Barkalov et al. 10.3390/math10152708
703. 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
704. Hazard assessment and mitigation of non-seismically fatal landslides in China F. Zhang et al. 10.1007/s11069-020-04491-x
705. 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
706. Community perceptions of landslide risk and susceptibility: a multi-country study M. Bukhari et al. 10.1007/s10346-023-02027-5
707. 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
708. A new method to compile global multi-hazard event sets J. Claassen et al. 10.1038/s41598-023-40400-5
709. Direct and semi-direct aerosol effects on the scaling of extreme sub-daily precipitation over East China S. Li et al. 10.1088/1748-9326/ad9294
710. 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
711. Can global rainfall estimates (satellite and reanalysis) aid landslide hindcasting? U. Ozturk et al. 10.1007/s10346-021-01689-3
712. 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
713. 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
714. Vulnerability of buildings to landslides: The state of the art and future needs H. Luo et al. 10.1016/j.earscirev.2023.104329
715. Potential of Documentary Evidence to Study Fatalities of Hydrological and Meteorological Events in the Czech Republic R. Brázdil et al. 10.3390/w11102014
716. 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
717. Characterization of landslide displacements in an active fault zone in Northwest China X. Shi & X. Hu 10.1002/esp.5594
718. Rock slides in paraglacial environments in South America: three-dimensional modeling of glacier retreat and landslide inducing the 2017 Santa Lucía disaster in the Chilean Patagonia F. Ochoa-Cornejo et al. 10.1007/s10346-024-02419-1
719. Incorporation of Satellite Precipitation Uncertainty in a Landslide Hazard Nowcasting System S. Hartke et al. 10.1175/JHM-D-19-0295.1
720. 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
721. Frekans Oranı Yöntemi Kullanılarak Arsuz Çayı Havzası Heyelan Duyarlılık Analizi S. Demirbilek & H. Turoğlu 10.46453/jader.1496249
722. Application of Empirical Approaches for Fast Landslide Hazard Management: The Case Study of Theilly (Italy) S. Segoni et al. 10.3390/w14213485
723. Stability analysis of reference station and compensation for monitoring stations in GNSS landslide monitoring D. Wang et al. 10.1186/s43020-023-00119-0
724. 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
725. 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
726. 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
727. Inventory and Spatial Distribution of Ancient Landslides in Hualong County, China Y. Huang et al. 10.3390/land12010136
728. Landslide Mapping From PlanetScope Images Using Improved Region-Based Level Set Evolution P. Lu et al. 10.1109/LGRS.2021.3122964
729. Airborne combined photogrammetry—infrared thermography applied to landslide remote monitoring V. Vivaldi et al. 10.1007/s10346-022-01970-z
730. Landslide susceptibility assessment of Kashmir Himalaya, India S. Zaz & S. Romshoo 10.1007/s12517-022-09699-8
731. 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
732. Disaster risk reduction and the limits of truisms: Improving the knowledge and practice interface D. Nohrstedt et al. 10.1016/j.ijdrr.2021.102661
733. Experimental investigation on anti-sliding performance of grouted micro-pipe pile groups X. Liu et al. 10.1007/s11069-022-05351-6
734. 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
735. 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
736. A review of recent studies on landslide hazard in Latin America A. Valdés Carrera et al. 10.1080/02723646.2021.1978372
737. Global detection of rainfall-triggered landslide clusters S. Benz & P. Blum 10.5194/nhess-19-1433-2019
738. Geospatial technologies for landslide monitoring: a case study of Sighetu Marmației, Romania T. Kalmar et al. 10.1007/s12665-024-11473-w
739. 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
740. Probabilistic framework for quantifying human flight failure rate to landslides S. Wang et al. 10.1016/j.enggeo.2024.107723
741. 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
742. 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
743. 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
744. Predicting Landslides Susceptible Zones in the Lesser Himalayas by Ensemble of Per Pixel and Object-Based Models U. Sur et al. 10.3390/rs14081953
745. 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
746. 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
747. 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
748. Rainfall-Induced Landslides from Initialization to Post-Failure Flows: Stochastic Analysis with Machine Learning H. Xu et al. 10.3390/math10234426
749. Uncertainty Analysis and Quantification of Rainfall-Induced Slope Instability in Fine-Grained Clayey Soils S. Espinosa Fuentes & M. El Naggar 10.3390/geotechnics5020031
750. A feature fusion method on landslide identification in remote sensing with Segment Anything Model C. Yang et al. 10.1007/s10346-024-02390-x
751. 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
752. Human Vulnerability to Landslides W. Pollock & J. Wartman 10.1029/2020GH000287
753. Risk assessment of chemical release accident triggered by landslide using Bayesian network N. Moriguchi et al. 10.1016/j.scitotenv.2023.164321
754. Multi-source landslide inventories for susceptibility assessment: a case study in the Concepción Metropolitan Area, Chile F. Castro-Venegas et al. 10.3389/feart.2025.1534295
755. Growth of Debris Flows by Soil Bed Erosion: Effects of Frictional and Hydrodynamic Shear Stresses P. Song et al. 10.1051/e3sconf/202341502021
756. Landslide susceptibility of Rwanda (Central Africa) C. Panelli et al. 10.1080/17445647.2024.2428654
757. Landslide–Anthropogenic Interactions in Urban Areas: A Multidisciplinary Case Study from Taounate, Morocco R. Sahrane et al. 10.1007/s10706-025-03204-0
758. Evaluation of a Tilt-Based Monitoring System for Rainfall-Induced Landslides: Development and Physical Modelling A. Paswan & A. Shrivastava 10.3390/w15101862
759. Landslide Susceptibility Evaluation Based on the Combination of Environmental Similarity and BP Neural Networks R. Wang et al. 10.3390/land14040839
760. 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
761. Landslide susceptibility mapping using hybrid random forest with GeoDetector and RFE for factor optimization X. Zhou et al. 10.1016/j.gsf.2021.101211
762. 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
763. Historical Landslide Fatalities in British Columbia, Canada: Trends and Implications for Risk Management A. Strouth & S. McDougall 10.3389/feart.2021.606854
764. 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
765. Temporal Variations in Landslide Distributions Following Extreme Events: Implications for Landslide Susceptibility Modeling J. Jones et al. 10.1029/2021JF006067
766. 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
767. 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
768. Livelihood, irrigation, and landslide: Unfolding the human-water-land nexus using an integrative framework J. Wang et al. 10.1016/j.landusepol.2024.107190
769. Insights Gained from the Review of Landslide Susceptibility Assessment Studies in Italy S. Segoni et al. 10.3390/rs16234491
770. Refined and dynamic susceptibility assessment of landslides using InSAR and machine learning models Y. Wei et al. 10.1016/j.gsf.2024.101890
771. 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
772. Field and Numerical Investigation of Taihu Resort Cut Slope Failure in Suzhou, China A. Raouf et al. 10.3390/app14072683
773. 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
774. Public emotions and the built environment in hazards: A case study of the Shenzhen catastrophic landslide S. Ma et al. 10.1016/j.cities.2025.105814
775. Geographical landslide early warning systems F. Guzzetti et al. 10.1016/j.earscirev.2019.102973
776. 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
777. Improved phase gradient stacking for landslide detection D. Zhang et al. 10.1007/s10346-024-02263-3
778. 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
779. 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
780. 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
781. 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
782. Automatic calculation of rainfall thresholds for landslide occurrence in Chukha Dzongkhag, Bhutan S. Gariano et al. 10.1007/s10064-018-1415-2
783. 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
784. Effects of flow-bed interactions on barrier impact W. De Silva et al. 10.1051/e3sconf/202341501005
785. Geometric approach based tool for shallow landslides propagation assessment (ShaLPA) at basin scale L. Falconi et al. 10.1016/j.envsoft.2025.106512
786. The State of Remote Sensing Capabilities of Cascading Hazards Over High Mountain Asia D. Kirschbaum et al. 10.3389/feart.2019.00197
787. IoT-Driven Microseismic Sensing System and Monitoring Platform for Landslide Detection P. Indukala et al. 10.1109/ACCESS.2024.3427386
788. High resolution landslide susceptibility mapping using ensemble machine learning and geospatial big data N. Sharma et al. 10.1016/j.catena.2023.107653
789. 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
790. Negative Poisson’s ratio and peripheral strain of an NPR anchor cable Z. Tao et al. 10.1007/s11629-022-7426-2
791. Landslide Mapping Using Multilevel-Feature-Enhancement Change Detection Network L. Wang et al. 10.1109/JSTARS.2023.3245062
792. An investigation of the combined effect of rainfall and road cut on landsliding S. Pradhan et al. 10.1016/j.enggeo.2022.106787
793. Landslide Fatality Occurrence: A Systematic Review of Research Published between January 2010 and March 2022 O. Petrucci 10.3390/su14159346
794. Landslide mapping with remote sensing: challenges and opportunities C. Zhong et al. 10.1080/01431161.2019.1672904
795. 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
796. Innovative optical fiber technique for soil moisture monitoring based on light intensity variation D. Hu et al. 10.1007/s11440-025-02696-7
797. 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
798. Widespread Initiation, Reactivation, and Acceleration of Landslides in the Northern California Coast Ranges due to Extreme Rainfall A. Handwerger et al. 10.1029/2019JF005035
799. Comprehensive review of remote sensing integration with deep learning in landslide forecasting and future directions N. Pawar & K. Sharma 10.1007/s11069-025-07171-w
800. Insights from Optimized Non-Landslide Sampling and SHAP Explainability for Landslide Susceptibility Prediction M. Li & H. Tian 10.3390/app15031163
801. Preliminary Analysis of the July 30, 2024, Wayanad Landslide Disaster in India: Causes and Impacts Q. Wang et al. 10.1016/j.nhres.2025.04.005
802. 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
803. 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
804. 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
805. A Novel Approach for Most Vulnerable Zone Identification Using MT-InSAR and Machine Learning: A Case Study from Lesser Himalayan Region V. Maurya et al. 10.1007/s12524-024-02103-w
806. A rapid run-out assessment methodology for the 2024 Wayanad debris flow V. Krishnapriya et al. 10.1038/s44304-024-00044-5
807. Assessing the impact of governance policies on landslide risk in Brazilian municipalities V. Gonçalves Sales 10.1016/j.ijdrr.2023.104058
808. Monitoring Slope Movement and Soil Hydrologic Behavior Using IoT and AI Technologies: A Systematic Review M. Alam et al. 10.3390/hydrology11080111
809. Effective landslide risk management in era of climate change, demographic change, and evolving societal priorities V. Capobianco et al. 10.1007/s10346-024-02418-2
810. 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
811. Rainfall Threshold Estimation and Landslide Forecasting for Kalimpong, India Using SIGMA Model M. Abraham et al. 10.3390/w12041195
812. Future changes of socioeconomic exposure to potential landslide hazards over mainland China D. Li et al. 10.1016/j.wace.2024.100731
813. 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
814. Spatial Landslide Risk Assessment at Phuentsholing, Bhutan A. Dikshit et al. 10.3390/geosciences10040131
815. 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
816. Forecasting Landslides Using Mobility Functions: A Case Study from Idukki District, India M. Abraham et al. 10.1007/s40098-020-00490-8
817. 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
818. Heterogeneous transfer learning considering feature representation and environmental consistency for landslide spatial prediction Z. Zhao et al. 10.1080/15481603.2024.2349343
819. 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
820. UAV, GNSS, and GIS for the Rapid Assessment of Multi-Occurrence Landslides K. Nikolakopoulos et al. 10.3390/geosciences14060160
821. What are the spatial distribution characteristics of the 4417 landslides in Minhe County, Qinghai Province, China? Q. Wang & C. Xu 10.3389/feart.2025.1501498
822. Investigation of landslides triggered by unprecedented rainfall events during 2023 monsoon in Himachal Pradesh, India E. Sana et al. 10.1007/s10346-025-02471-5
823. Numerical Investigation into the Runout Dynamics of Reservoir Landslides: Insights from the Yanguan Landslide H. Fang et al. 10.3390/w17050695
824. A multi‐sensor evaluation of precipitation uncertainty for landslide‐triggering storm events E. Culler et al. 10.1002/hyp.14260
825. 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
826. Review article: Natural hazard risk assessments at the global scale P. Ward et al. 10.5194/nhess-20-1069-2020
827. 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
828. A comparative study of regional landslide susceptibility mapping with multiple machine learning models Y. Wang et al. 10.1002/gj.4902
829. Review and Inventory of Pedological and Stratigraphical Knowledge for Investigating Shallow Landslides: A Case Study of the Cervinara Area (Central Campanian Apennines, Southern Italy) A. Ermice et al. 10.3390/geosciences15040151
830. Landslide Susceptibility mapping using random forest and extreme gradient boosting: A case study of Fengjie, Chongqing W. Zhang et al. 10.1002/gj.4683
831. Dry Spells and Extreme Precipitation are The Main Trigger of Landslides in Central Europe R. Tichavský et al. 10.1038/s41598-019-51148-2
832. 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
833. Landslide monitoring using seismic ambient noise correlation: challenges and applications M. Le Breton et al. 10.1016/j.earscirev.2021.103518
834. Landslides associated with recent road constructions in the Río Lucma catchment, eastern Cordillera Blanca, Peru A. EMMER et al. 10.1590/0001-3765202220211352
835. 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
836. Landslide Susceptibility Assessment in Hong Kong with Consideration of Spatio-Temporal Consistency A. Qiu et al. 10.3390/app142210654
837. A global perspective on a bioengineering approach to landslide mitigation using bamboo diversity S. Maddalwar et al. 10.1016/j.bamboo.2024.100093
838. 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
839. 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
840. A comprehensive analysis of landslide susceptibility in Iyidere Basin (NE, Turkey) using machine learning techniques and statistical bivariate methods K. Ersayin & A. Uzun 10.1007/s11069-025-07354-5
841. Review of landslide inventories for Nepal between 2010 and 2021 reveals data gaps in global landslide hotspot E. Harvey et al. 10.1007/s11069-024-07013-1
842. Spatial Non-Stationarity-Based Landslide Susceptibility Assessment Using PCAMGWR Model Y. Li et al. 10.3390/w14060881
843. Deep learning and benchmark machine learning based landslide susceptibility investigation, Garhwal Himalaya (India) S. Saha et al. 10.1016/j.qsa.2023.100075
844. 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
845. Türkiye’de ölümcül heyelanların dağılım karakteristikleri ve ulusal ölçekte öncelikli alanların belirlenmesi S. FİDAN & T. GÖRÜM 10.17211/tcd.731596
846. Using Field-Based Monitoring to Enhance the Performance of Rainfall Thresholds for Landslide Warning M. Abraham et al. 10.3390/w12123453
847. Shear-induced acoustic emission and energy evolution in granular-filled active waveguide L. Deng et al. 10.1016/j.rineng.2025.105079
848. 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
849. Landslides triggered by an extraordinary rainfall event in Central Italy on September 15, 2022 M. Donnini et al. 10.1007/s10346-023-02109-4
850. Rapid Mapping of Landslides Induced by Heavy Rainfall in the Emilia-Romagna (Italy) Region in May 2023 M. Ferrario & F. Livio 10.3390/rs16010122
851. 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
852. Spatial distributions and multi-factor driving mechanism of landslide in southern Liaodong Peninsula Y. Li et al. 10.3389/fevo.2023.1339265
853. Impact and a Novel Representation of Spatial Data Uncertainty in Debris Flow Susceptibility Analysis L. Kurilla & G. Fubelli 10.3390/app12136697
854. Could road constructions be more hazardous than an earthquake in terms of mass movement? H. Tanyaş et al. 10.1007/s11069-021-05199-2
855. 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
856. Mechanistic insights from emergent landslides in physical experiments O. Beaulieu et al. 10.1130/G47875.1
857. Kinematics of Irrigation‐Induced Landslides in a Washington Desert: Impacts of Basal Geometry Y. Xu et al. 10.1029/2021JF006355
858. Landslide detection, monitoring and prediction with remote-sensing techniques N. Casagli et al. 10.1038/s43017-022-00373-x
859. The Role of Citrus Groves in Rainfall-Triggered Landslide Hazards in Uwajima, Japan N. Lusiana & Y. Shinohara 10.3390/w14132113
860. 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
861. IoT-Based Geotechnical Monitoring of Unstable Slopes for Landslide Early Warning in the Darjeeling Himalayas M. Abraham et al. 10.3390/s20092611
862. 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
863. Constructing a Large-Scale Landslide Database Across Heterogeneous Environments Using Task-Specific Model Updates S. Nagendra et al. 10.1109/JSTARS.2022.3177025
864. 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
865. 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
866. A Bibliometric Analysis of Geological Hazards Monitoring Technologies Z. Liu et al. 10.3390/su17030962
867. Recognition of Landslide Triggering Mechanisms and Dynamics Using GNSS, UAV Photogrammetry and In Situ Monitoring Data T. Peternel et al. 10.3390/rs14143277
868. 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
869. Delineating Non-Susceptible Landslide Areas in China Based on Topographic Index and Quantile Non-Linear Model S. Ma et al. 10.3390/f15040678
870. 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
871. Mitigation and management of rainfall induced rockslides along the national highways of Himalayan region, India P. C et al. 10.1080/19475705.2021.1928772
872. Long-term analysis of rainfall-induced landslides in Umbria, central Italy S. Gariano et al. 10.1007/s11069-021-04539-6
873. Developing landslide hazard scenario using the historical events for the Kashmir Himalaya B. Shah et al. 10.1007/s11069-022-05542-1
874. 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
875. 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
876. 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
877. 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
878. Exploring the Potential of Native Urease-Producing Bacteria of Hilly Terrain for Soil Strength Enhancement R. Devrani et al. 10.1080/01490451.2024.2388823
879. 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
880. 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
881. Landslide Mapping and Susceptibility Assessment Using Geospatial Analysis and Earth Observation Data E. Psomiadis et al. 10.3390/land9050133
882. 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
883. InSAR-derived predisaster spatio-temporal evolution of a reactivated landslide K. He et al. 10.1007/s10064-024-03661-6
884. SkySlide: A Hybrid Method for Landslide Susceptibility Assessment based on Landslide-Occurring Data Only A. Mutlu & F. Goz 10.1093/comjnl/bxaa063
885. Numerical investigation of landslide kinetics for the recent Mabian landslide (Sichuan, China) J. Wei et al. 10.1007/s10346-019-01237-0
886. 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
887. Twisting Theory: A New Artificial Adaptive System for Landslide Prediction P. Buscema et al. 10.3390/geosciences13040115
888. 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
889. Model Test of Mechanical Response of Negative Poisson’s Ratio Anchor Cable in Rainfall-Induced Landslides G. Shi et al. 10.3390/buildings15101745
890. DebrisFlow Predictor: an agent-based runout program for shallow landslides R. Guthrie & A. Befus 10.5194/nhess-21-1029-2021
891. 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
892. Stability Prediction of Rainfall-Induced Shallow Landslides: A Case Study of Mountainous Area in China K. Song et al. 10.3390/w15162938
893. Transfer learning for landslide susceptibility modeling using domain adaptation and case-based reasoning Z. Wang et al. 10.5194/gmd-15-8765-2022
894. Biotech Crops, Input Use and Landslides Case Study of Herbicide Tolerant Corn in the Philippine Highlands L. Bequet 10.1016/j.ecolecon.2020.106773
895. Quantitative Land-Use and Landslide Assessment: A Case Study in Rize, Türkiye N. Kasahara et al. 10.3390/w14111811
896. Geomorphic evaluation of landslides along the Teesta river valley, Sikkim Himalaya, India V. Gupta et al. 10.1002/gj.4377
897. Evaluating the performances of satellite-based rainfall data for global rainfall-induced landslide warnings G. Jia et al. 10.1007/s10346-019-01277-6
898. 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
899. 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
900. Unveiling the amplifying impact: Anthropogenic activities and the two-fold surge in landslides in the Lesser Himalayas S. Kaushal et al. 10.1016/j.catena.2025.108771
901. 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
902. An Integrated Approach of Machine Learning, Remote Sensing, and GIS Data for the Landslide Susceptibility Mapping I. Ullah et al. 10.3390/land11081265
903. 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
904. Classification of Landslide Activity on a Regional Scale Using Persistent Scatterer Interferometry at the Moselle Valley (Germany) A. Kalia 10.3390/rs10121880
905. Multi-Level Data Analyses for Characterizing Rainfall-Induced Landslide Scenarios: The Example of Catanzaro Municipality (South Italy) O. Petrucci et al. 10.3390/w15132437
906. Prevention of Mountain Disasters and Maintenance of Residential Area through Real-Time Terrain Rendering S. Sung et al. 10.3390/su13052950
907. Exploring Shallow Geological Structures in Landslides Using the Semi-Airborne Transient Electromagnetic Method J. Wu et al. 10.3390/rs16173186
908. Deformation and failure analysis of heterogeneous slope using nonlinear spatial probabilistic finite element method P. Garg et al. 10.3934/math.20241283
909. 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
910. Rainfall affected stability analysis of Maddingley Brown Coal eastern batter using Plaxis 3D L. Zhao & G. You 10.1007/s12517-020-06038-7
911. InSAR-Based Active Landslide Detection and Characterization Along the Upper Reaches of the Yellow River J. Du et al. 10.1109/JSTARS.2023.3263003
912. Landslide vulnerability mapping using GIS-based statistical model for sustainable ecosystem management in the Himalayan region of Teesta River basin, India S. Pal et al. 10.1186/s12302-025-01107-8
913. Machine learning-based rainfall-induced landslide susceptibility model and short-term early warning assessment in South Korea S. Lee et al. 10.1007/s10346-025-02513-y
914. 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
915. 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
916. Quantifying the Effect of Precipitation on Landslide Hazard in Urbanized and Non‐Urbanized Areas E. Johnston et al. 10.1029/2021GL094038
917. Fatigue behaviors of pre-flawed orthoclase granite under monotonic and multi-level cyclic loadings Y. Li et al. 10.1016/j.tafmec.2025.104858
918. 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
919. Landslide dynamic hazard prediction based on precipitation variation trend and backpropagation neural network R. Huang et al. 10.1080/10106049.2024.2322058
920. Threshold assessment of rainfall-induced landslides in Sangzhi County: statistical analysis and physical model Y. Sheng et al. 10.1007/s10064-022-02890-x
921. Composite Anchors for Slope Stabilisation: Monitoring of their In-Situ Behaviour with Optical Fibre S. Cola et al. 10.3390/geosciences9050240
922. A Stochastic Dynamical Model of Slope Creep and Failure Q. Lei & D. Sornette 10.1029/2022GL102587
923. 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
924. Updating Inventory, Deformation, and Development Characteristics of Landslides in Hunza Valley, NW Karakoram, Pakistan by SBAS-InSAR X. Su et al. 10.3390/rs14194907
925. Developing a landslide vulnerability assessment for the national road network in Laos G. Hearn & P. Pongpanya 10.1144/qjegh2020-110
926. A slow-moving landslide risk assessment procedure using thematic maps and InSAR data: a case study C. Dai et al. 10.1080/17499518.2025.2467994
927. Using DInSAR to inventory landslide geological disaster in Bijie, Guizhou, China C. Shen et al. 10.3389/feart.2022.1024710
928. Landslide Hazard Assessment Method Considering the Deformation Factor: A Case Study of Zhouqu, Gansu Province, Northwest China C. Dai et al. 10.3390/rs15030596
929. 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
930. A community-operated landslide early warning approach: Myanmar case study N. Dixon et al. 10.1186/s40677-022-00220-7
931. The Anomalously Old Bush Stream Rock Avalanche and Its Implications for Landslide Inventories in Dynamic Landscapes S. McColl 10.3389/feart.2020.00103
932. 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
933. How climate change and unplanned urban sprawl bring more landslides U. Ozturk et al. 10.1038/d41586-022-02141-9
934. 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
935. 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
936. 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
937. 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
938. Predicting Railway Slope Failure Under Heavy Rainfall Using the Soil Moisture Extended Cohesive Damage Element Method S. Loku-Pathirage et al. 10.3390/geohazards6010014
939. Field research on preferential infiltration in rainfall-induced loess landslides J. Ma et al. 10.1016/j.enggeo.2025.108184
940. Predicting and Understanding Landslide Events With Explainable AI E. Collini et al. 10.1109/ACCESS.2022.3158328
941. Impact of sampling for landslide susceptibility assessment using interpretable machine learning models B. Wu et al. 10.1007/s10064-024-03980-8
942. A global landslide non-susceptibility map G. Jia et al. 10.1016/j.geomorph.2021.107804
943. 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
944. 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
945. 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
946. 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
947. Assessing uncertainties in landslide susceptibility predictions in a changing environment (Styrian Basin, Austria) R. Knevels et al. 10.5194/nhess-23-205-2023
948. 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
949. Change detection of slow-moving landslide with multi-source SBAS-InSAR and Light-U2Net J. Cai et al. 10.1016/j.jag.2025.104387
950. Analysis of landslide-induced fatalities and injuries in Bangladesh: 2000-2018 N. Sultana & S. Ricart Casadevall 10.1080/23311886.2020.1737402
951. Early prediction framework for a rainfall-induced landslide: validation through a real case study P. Sudani & K. Patil 10.1007/s12046-023-02242-9
952. 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
953. Landslide hazard assessment and mapping at national scale for Malawi Y. Thiery et al. 10.1016/j.jafrearsci.2024.105187
954. 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
955. 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
956. 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
957. SLEM (Shallow Landslide Express Model): A Simplified Geo-Hydrological Model for Powerlines Geo-Hazard Assessment A. Abbate & L. Mancusi 10.3390/w16111507
958. Parametric Study of Rainfall-Induced Instability in Fine-Grained Sandy Soil S. Espinosa F & M. El Naggar 10.3390/geotechnics4040059
959. 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
960. 3D simulation of Vajont disaster. Part 1: Numerical formulation and validation A. Franci et al. 10.1016/j.enggeo.2020.105854
961. 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
962. Reanalysis of Soil Moisture Used for Rainfall Thresholds for Rainfall-Induced Landslides: The Italian Case Study N. Bezak et al. 10.3390/w13141977
963. 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
964. Landslide risk assessment in mining areas using hybrid machine learning methods under fuzzy environment L. Dong et al. 10.1016/j.ecolind.2024.112736
965. Integrated Landslide Risk Assessment via a Landslide Susceptibility Model Based on Intelligent Optimization Algorithms X. Dai et al. 10.3390/rs17030545
966. Landslide susceptibility modeling by interpretable neural network K. Youssef et al. 10.1038/s43247-023-00806-5
967. 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
968. 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
969. Landslide Distribution and Development Characteristics in the Beiluo River Basin F. Liu et al. 10.3390/land13071038
970. 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
971. Comprehensive investigation and kinematic assessment of a small catastrophic landslide in Shiban Valley, Leshan City, Sichuan Province, China Y. Liu et al. 10.1007/s10346-025-02503-0
972. Revealing the relation between spatial patterns of rainfall return levels and landslide density S. Mtibaa & H. Tsunetaka 10.5194/esurf-11-461-2023
973. A methodology for road cutting design guidelines based on field observations E. Robson et al. 10.1016/j.enggeo.2022.106771
974. 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
975. Revealing the Importance of Capillary and Collisional Stresses on Soil Bed Erosion Induced by Debris Flows P. Song & C. Choi 10.1029/2020JF005930
976. 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
977. Global Landslide Forecasting System for Hazard Assessment and Situational Awareness S. Khan et al. 10.3389/feart.2022.878996
978. 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
979. 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
980. Consequences of slope instability and existing practices of mitigation in hydropower projects of Nepal S. Regmi & R. Dahal 10.1186/s40677-024-00289-2
981. A hybrid ensemble-based deep-learning framework for landslide susceptibility mapping L. Lv et al. 10.1016/j.jag.2022.102713
982. 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
983. 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
984. 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
985. 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
986. An Index for Snowmelt-Induced Landslide Prediction for Zavoj Lake, Serbia R. Marković et al. 10.3390/atmos15030256
987. Landslide susceptibility analysis using machine learning: Insights from the bend Subcarpathians-Carpathians, Romania V. Ilinca et al. 10.1016/j.geomorph.2025.109872
988. 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
989. Coupling RBF neural network with ensemble learning techniques for landslide susceptibility mapping B. Pham et al. 10.1016/j.catena.2020.104805
990. 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
991. Characterizing the scale of regional landslide triggering from storm hydrometeorology J. Perkins et al. 10.5194/nhess-25-1037-2025
992. 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
993. 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
994. The Geomorphic Effectiveness of Landslides E. Dente et al. 10.1029/2023JF007191
995. A reliability evaluation of four landslide failure forecasting methods in real-time monitoring applications S. Sharifi et al. 10.1007/s10346-024-02293-x
996. 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
997. 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
998. 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
999. 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
1000. 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
1001. Quantifying effects of changes in forest age distribution on the landslide frequency in Japan N. Lusiana et al. 10.1007/s11069-024-06537-w
1002. Study on the Progress in Climate-Change-Oriented Human Settlement Research Q. Yao et al. 10.3390/su15075733
1003. Centrifuge model tests of h-type anti-slide pile reinforced slope under different rainfall duration H. Zhang et al. 10.1080/19648189.2024.2338771
1004. 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
1005. Non-Structural Landslide Risk Mitigation: Schemes, Application and Case Studies T. Chauhan et al. 10.1007/s40098-024-00996-5
1006. 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
1007. Time capsule for landslide risk assessment Y. Lei et al. 10.1080/17499518.2023.2164899
1008. A Semiautomatic Pixel-Object Method for Detecting Landslides Using Multitemporal ALOS-2 Intensity Images B. Adriano et al. 10.3390/rs12030561
1009. 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
1010. Slope-Unit Scale Landslide Susceptibility Mapping Based on the Random Forest Model in Deep Valley Areas H. Deng et al. 10.3390/rs14174245
1011. Rapid mapping of landslides using satellite SAR imagery: A progressive learning approach N. Prakash et al. 10.1016/j.acags.2025.100224
1012. 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
1013. Towards A Geo-Hydro-Mechanical Characterization of Landslide Classes: Preliminary Results F. Cotecchia et al. 10.3390/app10227960
1014. Perceptions of landslide risks and warnings in Hong Kong M. Yik et al. 10.1007/s10346-022-02021-3
1015. Climate change and landslide hazard in stiff clays and clay shales L. Comegna et al. 10.1007/s10346-025-02487-x
1016. 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
1017. Joint detection and classification of rockfalls in a microseismic monitoring network L. Feng et al. 10.1093/gji/ggaa287
1018. Automated Monitoring and Emergency Response System for Sensitive Areas Along High-Speed Railway Lines C. Chiu et al. 10.1051/e3sconf/202451203003
1019. DCI-PGCN: Dual-Channel Interaction Portable Graph Convolutional Network for Landslide Detection W. Li et al. 10.1109/TGRS.2023.3273623
1020. Landslide Risk Assessment Using a Combined Approach Based on InSAR and Random Forest W. Liu et al. 10.3390/rs14092131
1021. 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
1022. 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
1023. 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
1024. Distribution and temporal-spatial characteristics of geohazards in a rainstorm-prone area of SE China considering the land use Z. Guo et al. 10.1016/j.bgtech.2025.100184
1025. Laboratory Landquakes: Insights From Experiments Into the High‐Frequency Seismic Signal Generated by Geophysical Granular Flows M. Arran et al. 10.1029/2021JF006172
1026. GIS-driven multi-phase simulation framework for assessing rainfall-triggered landslides using SPH-FDM techniques A. Sajwan et al. 10.1007/s40571-025-01015-x
1027. 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
1028. Slope stability and surface displacement analysis of the Kuther Landslide in the Dehar Watershed, Himachal Himalaya, Northern India A. Kumar et al. 10.1007/s44288-024-00107-0
1029. Mapping Landslide Susceptibility Over Large Regions With Limited Data J. Woodard et al. 10.1029/2022JF006810
1030. Landslide failures detection and mapping using Synthetic Aperture Radar: Past, present and future A. Mondini et al. 10.1016/j.earscirev.2021.103574
1031. Fatal landslides in China from 1940 to 2020: occurrences and vulnerabilities S. Zhang et al. 10.1007/s10346-023-02034-6
1032. Shape and Dimension Estimations of Landslide Rupture Zones via Correlations of Characteristic Parameters G. Domej et al. 10.3390/geosciences10050198
1033. Landslide Risk Assessment as a Reference for Disaster Prevention and Mitigation: A Case Study of the Renhe District, Panzhihua City, China Y. Zhou et al. 10.3390/rs17132120
1034. 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
1035. Assessment of Physical Vulnerability and Uncertainties for Debris Flow Hazard: A Review concerning Climate Change M. Khan et al. 10.3390/land11122240
1036. Rainfall-induced runoff and debris flows: modelling the Cervinara 1999 cascade flow-like mass movements S. Cuomo et al. 10.1007/s10064-025-04283-2
1037. GIS-Based Expert Knowledge for Landslide Susceptibility Mapping (LSM): Case of Mostaganem Coast District, West of Algeria R. Senouci et al. 10.3390/su13020630
1038. 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
1039. Evaluation of social vulnerability to natural hazards: a case of Barton on Sea, England K. Kantamaneni 10.1007/s12517-019-4819-9
1040. Integrated Methodology for Potential Landslide Identification in Highly Vegetation-Covered Areas L. Yan et al. 10.3390/rs15061518
1041. 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
1042. Stability Evaluation of Engineered Slopes Using Coupled Empirical and Analytical Approach Along NH-9, Lesser Himalayas, India P. Haris & T. Siddique 10.1007/s40098-025-01226-2
1043. FSLAM: A QGIS plugin for fast regional susceptibility assessment of rainfall-induced landslides Z. Guo et al. 10.1016/j.envsoft.2022.105354
1044. 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
1045. 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
1046. 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
1047. Landslide Geomorphology: Pattern, Process and Stability H. Qiu & Y. Wei 10.1007/s12583-024-0131-z
1048. Landslide Inventorization and Susceptibility Mapping in the SemiArid Kargil-Ladakh Region of Northwestern Himalaya M. Akbar et al. 10.17491/jgsi/2024/173894
1049. 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
1050. 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
1051. The downward spiral entangling soil sealing and hydrogeological disasters A. Gatto et al. 10.1088/1748-9326/ad5fa1
1052. Keynote lecture. The planar setup: A window through the complex interactions in granular flows M. Cabrera et al. 10.1051/e3sconf/202341502004
1053. Mapping method of rainfall-induced landslide hazards by infiltration and slope stability analysis N. Dolojan et al. 10.1007/s10346-020-01617-x
1054. Landslides, a Key Landform in the Global Geological Heritage C. Morino et al. 10.3389/feart.2022.864760
1055. 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
1056. 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
1057. Spatiotemporal variations of non-seismically fatal landslides in Northwest China: A case study from Shaanxi province B. Lian et al. 10.1016/j.jseaes.2024.106389
1058. 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
1059. 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
1060. 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
1061. 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
1062. 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
1063. Landslide Risk Assessment in Eastern Kentucky, USA: Developing a Regional Scale, Limited Resource Approach M. Crawford et al. 10.3390/rs14246246
1064. 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
1065. 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
1066. Spatial Analysis of Landslide Potential in Agricultural Areas of Wadaslintang Catchment Area, Central Java Province Indonesia G. Nafisa et al. 10.29303/jrpb.v13i1.678
1067. Behavior of soil slopes reinforced with composite-structural piles Y. Xiang et al. 10.1088/1755-1315/1334/1/012016
1068. Invited perspectives: Building sustainable and resilient communities – recommended actions for natural hazard scientists J. Gill et al. 10.5194/nhess-21-187-2021
1069. 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
1070. Assessment of landslide susceptibility in watersheds during extreme rainfall using a complex network of slope units C. Wang et al. 10.1038/s41598-025-89039-4
1071. AutoGluon: A revolutionary framework for landslide hazard analysis W. Qi et al. 10.1016/j.nhres.2021.07.002
1072. A comprehensive global database of giant landslides on volcanic islands J. Blahůt et al. 10.1007/s10346-019-01275-8
1073. 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
1074. 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
1075. Simple rules to minimise exposure to coseismic landslide hazard D. Milledge et al. 10.5194/nhess-19-837-2019
1076. Multisource Data Fusion and Adversarial Nets for Landslide Extraction from UAV-Photogrammetry-Derived Data H. He et al. 10.3390/rs14133059
1077. Causes of episodic movement of the Baijiabao landslide based on multiple-time scale analysis Z. Fu et al. 10.1007/s10346-023-02201-9
1078. Deformation Monitoring Exploration of Different Elevations in Western Sichuan, China Z. Zheng et al. 10.3390/rs17071284
1079. Role of remote sensing and geotechnical studies in assessing the landslide vulnerability in the Chamoli region of Uttarakhand, India S. Singh et al. 10.1007/s42452-025-06498-0
1080. An InSAR and depth-integrated coupled model for potential landslide hazard assessment S. Zhou et al. 10.1007/s11440-021-01429-w
1081. 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
1082. Assessing Urban Landslide Dynamics through Multi-Temporal InSAR Techniques and Slope Numerical Modeling N. Necula et al. 10.3390/rs13193862
1083. 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
1084. Quantitative Hazard Prediction of Rainfall-Induced Shallow Landslides Considering Triggering and Predisposing Factors: A Case of Natural Terrain Landslides in Hong Kong Y. Chen et al. 10.1109/JSTARS.2025.3570020
1085. 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
1086. Enhancing landslide hazard prevention: Mapping vulnerability via considering the effects of human factors D. Yin et al. 10.1016/j.ijdrr.2024.104509
1087. 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
1088. 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
1089. Worldwide Research Trends in Landslide Science P. Carrión-Mero et al. 10.3390/ijerph18189445
1090. 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
1091. 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
1092. Landslide risk assessment by integrating hazards and vulnerability indices in Southeast Bangladesh N. Sultana et al. 10.1016/j.ijdrr.2024.104991
1093. EFFECT OF PARTICLE SIZE DISTRIBUTIONS ON GRANULAR FLOW SIMULATIONS USING DISCRETE ELEMENT METHOD D. WATANABE et al. 10.2208/jscejge.77.4_392
1094. 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
1095. 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
1096. 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
1097. 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
1098. Random forest-based screening of environmental geohazard probability factors in Panshi city, China L. Qi et al. 10.1016/j.asr.2024.09.055
1099. Impact of terrain variation on landslide mobility: Insights from DEM simulations S. Zhou et al. 10.1016/j.compgeo.2024.107050
1100. 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
1101. 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
1102. 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
1103. Method for Landslide Area Detection with RVI Data Which Indicates Base Soil Areas Changed from Vegetated Areas K. Arai et al. 10.3390/rs17040628
1104. 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
1105. Time and path prediction of landslides using InSAR and flow model P. Roy et al. 10.1016/j.rse.2022.112899
1106. 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
1107. 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
1108. Landslides Detection and Mapping with an Advanced Multi-Temporal Satellite Optical Technique V. Satriano et al. 10.3390/rs15030683
1109. 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
1110. Geophysical Monitoring of Moisture‐Induced Landslides: A Review J. Whiteley et al. 10.1029/2018RG000603
1111. 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
1112. CHILDA – Czech Historical Landslide Database M. Bíl et al. 10.5194/nhess-21-2581-2021
1113. Determining the impact of anthropogenic activities and climate change on landslide susceptibility for the Himalayan region A. Tyagi et al. 10.1007/s11069-024-07011-3
1114. 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
1115. An Assessment of Negative Samples and Model Structures in Landslide Susceptibility Characterization Based on Bayesian Network Models S. Khabiri et al. 10.3390/rs15123200
1116. Towards hydrometeorological thresholds of reservoir-induced landslide from subsurface strain observations X. Ye et al. 10.1007/s11431-023-2657-3
1117. Assessment of landslide susceptibility and risk factors in China D. Wang et al. 10.1007/s11069-021-04812-8
1118. Multi-hazard susceptibility and exposure assessment of the Hindu Kush Himalaya J. Rusk et al. 10.1016/j.scitotenv.2021.150039
1119. Spatiotemporal Analysis of Ecological Security Based on Landscape Patterns H. Zhang et al. 10.3390/ijgi13060204
1120. Temporal and spatial distributions of landslides in the Qinba Mountains, Shaanxi Province, China H. Qiu et al. 10.1080/19475705.2018.1536080
1121. Landslide susceptibility mapping using statistical and machine learning models (case study: Austria) M. Moharrami & M. Jelokhani-Niaraki 10.61186/jgst.13.2.79
1122. Landslide susceptibility assessment for Uttarakhand, a Himalayan state of India, using multi-criteria decision making, bivariate, and machine learning models V. Chauhan et al. 10.1186/s40677-024-00307-3
1123. Nationwide Susceptibility Mapping of Landslides in Kenya Using the Fuzzy Analytic Hierarchy Process Model S. Zhou et al. 10.3390/land9120535
1124. Brief communication: Key papers of 20 years in Natural Hazards and Earth System Sciences A. Gain et al. 10.5194/nhess-22-985-2022
1125. Influence of sampling design on landslide susceptibility modeling in lithologically heterogeneous areas A. Dornik et al. 10.1038/s41598-022-06257-w
1126. Machine learning-based assessment of regional-scale variation of landslide susceptibility in central Vietnam R. Das et al. 10.1371/journal.pone.0308494
1127. A multi-source landslide early warning model based on dynamic monitoring data and the SAAHP-FCE method D. Wang et al. 10.1080/19475705.2025.2513536
1128. 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
1129. 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
1130. 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
1131. Detailed inventory and initial analysis of landslides triggered by extreme rainfall in the northern Huaiji County, Guangdong Province, China, from June 6 to 9, 2020 C. Xie et al. 10.1186/s40677-025-00311-1
1132. 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
1133. Highway Proneness Appraisal to Landslides along Taiping to Ipoh Segment Malaysia, Using MCDM and GIS Techniques I. Yamusa et al. 10.3390/su14159096
1134. 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
1135. Landslide Risk Modeling using Data Mining in Hyrcanian Forests N. Nazariani & A. Fallah 10.61186/jwmr.14.27.123
1136. An integrated landslide susceptibility assessment in the Karakoram Mountains based on SBAS-InSAR and machine learning: a case study of the Hunza Valley X. Su et al. 10.1007/s10064-025-04299-8
1137. 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
1138. Future climate change implications in Bhutan from a downscaled and bias‐adjusted CMIP6 multimodel ensemble F. Lehner et al. 10.1002/joc.8623
1139. 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
1140. Rainfall-Induced Landslide Assessment under Different Precipitation Thresholds Using Remote Sensing Data: A Central Andes Case G. Maragaño-Carmona et al. 10.3390/w15142514
1141. Kinematic behavior and sliding geometry of large anthropogenic-induced landslides using three-dimensional time series InSAR: insights from the Li-Kan Road landslide J. Du et al. 10.1007/s10346-025-02542-7
1142. Regional chronology of landslide movements based on anatomical growth responses of trees: The České středohoří highlands K. Šilhán 10.1016/j.catena.2025.108764
1143. Calibration and Performance Evaluation of Cost-Effective Capacitive Moisture Sensor in Slope Model Experiments M. Hidayat et al. 10.3390/s24248156
1144. 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
1145. Application of novel distributed fibre-optic sensing for slope deformation monitoring: a comprehensive review A. Acharya & T. Kogure 10.1007/s13762-022-04697-5
1146. 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
1147. 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
1148. Exploring disaster ontologies from Chinese and Western perspectives: commonalities and nuances S. Goodall et al. 10.1108/DPM-03-2021-0108
1149. 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
1150. 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
1151. Applications of UAV in landslide research: a review B. Chen et al. 10.1007/s10346-025-02547-2
1152. Engineering geomorphological investigation of the Kasavu landslide, Viti Levu, Fiji A. Ram et al. 10.1007/s10346-019-01191-x
1153. 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
1154. Current understanding and uncertainties associated with climate change and the impact on slope stability: A systematic literature review F. Tetteh et al. 10.1016/j.nhres.2025.01.011
1155. Research on Uncertainty of Landslide Susceptibility Prediction—Bibliometrics and Knowledge Graph Analysis Z. Yang et al. 10.3390/rs14163879
1156. 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
1157. Global Dynamic Rainfall-Induced Landslide Susceptibility Mapping Using Machine Learning B. Li et al. 10.3390/rs14225795
1158. 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
1159. 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
1160. Spatial joint hazard assessment of landslide susceptibility and intensity within a single framework: Environmental insights from the Wenchuan earthquake Z. Tang et al. 10.1016/j.scitotenv.2025.178545
1161. Research on SSA-LSTM-Based Slope Monitoring and Early Warning Model S. Yang et al. 10.3390/su141610246
1162. A New Deep Learning Neural Network Model for the Identification of InSAR Anomalous Deformation Areas T. Zhang et al. 10.3390/rs14112690
1163. Editorial: Big Earth Data for Disaster Risk Reduction F. Chen et al. 10.3389/feart.2021.727547
1164. 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
1165. Pleistocene chronicles of large landslides activity on the western flank of the Central Andes revealed by cosmogenic nuclide dating F. Delgado et al. 10.1016/j.jsames.2024.105290
1166. 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
1167. 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
1168. Rainfall infiltration and slope stability of alpine colluvial terraces subject to storms (NE Italy) P. Paronuzzi & A. Bolla 10.1016/j.enggeo.2023.107199
1169. Prioritization of Subwatershed Using Remote Sensing and Geographic Information System in Gandaki Province, Nepal D. Poudel et al. 10.1002/wwp2.12260
1170. Roads and landslides in Nepal: how development affects environmental risk B. McAdoo et al. 10.5194/nhess-18-3203-2018
1171. An Integrated Approach for Earth Infrastructure Monitoring Using UAV and ERI: A Systematic Review U. Igwenagu et al. 10.3390/drones9030225
1172. 2-D Cross-Plot Model Analysis Using Integrated Geophysical Methods for Landslides Assessment M. Zakaria et al. 10.3390/app11020747
1173. An integrated approach based landslide susceptibility mapping: case of Muzaffarabad region, Pakistan M. Basharat et al. 10.1080/19475705.2023.2210255
1174. How water, wind, waves and ice shape landscapes and landforms: Historical contributions to geomorphic science J. Gardner 10.1016/j.geomorph.2019.02.031
1175. Sustainable rural infrastructure: guidelines for roadside slope excavation P. Paudyal et al. 10.1186/s40677-023-00240-x
1176. Mass Movement Hazard and Exposure in the Himalaya S. Dubey et al. 10.1029/2022EF003253
1177. A novel approach for displacement interval forecasting of landslides with step-like displacement pattern Q. Ge et al. 10.1080/17499518.2021.1892769
1178. Redefining landslide susceptibility under extreme rainfall events using deep learning A. Achu et al. 10.1016/j.geomorph.2023.109033
1179. Physics-informed data assimilation model for displacement prediction of hydrodynamic pressure-driven landslide Y. Liu et al. 10.1016/j.compgeo.2024.106085
1180. 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
1181. 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
1182. Improved rainfall infiltration model for probabilistic slope stability assessment considering transition layers and spatial variability S. Jiang et al. 10.1016/j.enggeo.2025.108096
1183. Improving the forecast performance of landslide susceptibility mapping by using ensemble gradient boosting algorithms H. Ha et al. 10.1007/s10668-024-04694-3
1184. 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
1185. The Alasu rock avalanche in the Tianshan Mountains, China: fragmentation, landforms, and kinematics Q. Lin et al. 10.1007/s10346-023-02167-8
1186. 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
1187. Enhanced landslide susceptibility zonation using GIS-Based ensemble techniques A. Sharma et al. 10.1007/s12665-024-12032-z
1188. Evaluating landslide susceptibility: an AHP method-based approach enhanced with optimized random forest modeling X. Zhang et al. 10.1007/s11069-023-06306-1
1189. Identifying Potential Landslides on Giant Niexia Slope (China) Based on Integrated Multi-Remote Sensing Technologies X. Dong et al. 10.3390/rs14246328
1190. Post‐landslide soil and vegetation recovery in a dry, montane system is slow and patchy B. Buma & Ł. Pawlik 10.1002/ecs2.3346
1191. Real‐Time Forecast of Catastrophic Landslides via Dragon‐King Detection Q. Lei et al. 10.1029/2022GL100832
1192. 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
1193. Impact of precipitation on Beishan landslide deformation from 1986 to 2023 M. Liu et al. 10.3389/feart.2023.1304969
1194. Spatial Prediction of Landslide Susceptibility using Various Machine Learning Based Binary Classification Methods N. Anh et al. 10.17491/jgsi/2024/174002
1195. Displacement residuals reveal landslide regime shifts L. Nava et al. 10.1007/s10346-024-02353-2
1196. Guidelines for Studying Diverse Types of Compound Weather and Climate Events E. Bevacqua et al. 10.1029/2021EF002340
1197. Consideration of spatial heterogeneity in landslide susceptibility mapping using geographical random forest model R. Quevedo et al. 10.1080/10106049.2021.1996637
1198. Landslide Susceptibility Assessment by Novel Hybrid Machine Learning Algorithms B. Thai Pham et al. 10.3390/su11164386
1199. Landslide Susceptibility Mapping Using GIS-Based Data Mining Algorithms V. Vakhshoori et al. 10.3390/w11112292
1200. 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
1201. 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
1202. 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
1203. Influence of human activity on landslide susceptibility development in the Three Gorges area Y. Li et al. 10.1007/s11069-020-04264-6
1204. Investigating the role of rock weathering and clay mineralogy in landslide occurrences within the exposed Tertiary Formations in Rangamati area S. Hossain et al. 10.1186/s40677-025-00324-w
1205. 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
1206. Century-long history of rural community landslide risk reduction J. Klimeš et al. 10.1016/j.ijdrr.2020.101756
1207. 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
1208. Deformation Slope Extraction and Influencing Factor Analysis Using LT-1 Satellite Data: A Case Study of Chongqing and Surrounding Areas, China J. Liu et al. 10.3390/rs17010156
1209. Spatiotemporal Characteristics and Rainfall Thresholds of Geological Landslide Disasters in ASEAN Countries W. Lu et al. 10.3390/atmos15050599
1210. Risk resilience of growing settlements in landslide prone hilly areas: case study on Kalimpong-I block, Darjeeling District, West Bengal C. Laha Salui et al. 10.1007/s11069-025-07324-x
1211. Unsupervised Change Detection Methods Applied to Landslide Mapping: Case Study in São Sebastião, Brazil G. Moço et al. 10.1111/tgis.13256
1212. GIS-based evolution and comparisons of landslide susceptibility mapping of the East Sikkim Himalaya N. Gupta et al. 10.1080/19475683.2022.2040587
1213. Cost-benefit methodology for road slope stabilisation E. Robson et al. 10.1016/j.trgeo.2024.101282
1214. Rainfall threshold for prediction of shallow landslides in the Garhwal Himalaya, India S. Saha & B. Bera 10.1016/j.geogeo.2024.100285
1215. Study on microstructure and permeability of a red clay area subjected to dry-wet cycles using X-ray micro computed tomography and AVIZO Z. Zhang et al. 10.1016/j.jhydrol.2025.133027
1216. Deformation Feature Extraction for GNSS Landslide Monitoring Series Based on Robust Adaptive Sliding-Window Algorithm G. Huang et al. 10.3389/feart.2022.884500
1217. 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
1218. Discriminating Landslide Waveforms in Continuous Seismic Data Using Power Spectral Density Analysis R. Rekapalli et al. 10.1029/2024GL110466
1219. 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
1220. 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
1221. Rainfall Threshold for Shallow Landslides Initiation and Analysis of Long-Term Rainfall Trends in a Mediterranean Area A. Roccati et al. 10.3390/atmos11121367
1222. Investigation on the failure mechanism of slope deformations induced by water-level fluctuation with InSAR and numerical simulation: a case study L. Jiang et al. 10.1144/qjegh2023-146
1223. Failure characteristics and instability mechanism of the Hengshanbei catastrophic high-locality landslide in Guangdong, China J. Wang et al. 10.1007/s11069-025-07158-7
1224. The geoenvironmental factors influencing slope failures in the Majerda basin, Algerian-Tunisian border I. Arif et al. 10.1007/s41207-023-00423-w
1225. 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
1226. 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
1227. Life and death of slow-moving landslides P. Lacroix et al. 10.1038/s43017-020-0072-8
1228. 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
1229. 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
1230. Editorial: Advances and applications in modeling, assessment, and mitigation of landslide disasters Z. Chen et al. 10.3389/feart.2024.1480635
1231. 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
1232. 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
1233. 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
1234. The Role of Hydraulic Hysteresis on the Hydrological Response of Pyroclastic Silty Covers G. Rianna et al. 10.3390/w11030628
1235. Towards Automatic Landslide-Quake Identification Using a Random Forest Classifier G. Lin et al. 10.3390/app10113670
1236. Exploring available landslide inventories for susceptibility analysis in Gipuzkoa province (Spain) T. Bornaetxea et al. 10.1007/s11069-023-06103-w
1237. A novel framework for landslide displacement prediction using MT-InSAR and machine learning techniques C. Zhou et al. 10.1016/j.enggeo.2024.107497
1238. 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
1239. 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
1240. 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
1241. 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
1242. Experimental Investigation on Integrated Subsurface Monitoring of Soil Slope Using Acoustic Emission and Mechanical Measurement L. Deng et al. 10.3390/app11167173
1243. A Comparison of Alternative GIS Data Model Methods for Landslide Susceptibility Mapping with XGBoost and SHAP Ş. Bediroğlu 10.31466/kfbd.1446997
1244. ANALYSIS OF SPATIAL PATTERNS OF LANDSLIDE FORMATION WITH GIS TOOLS (ZAKARPATSKA OBLAST) S. Shekhunova et al. 10.15407/ugz2022.03.011
1245. 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
1246. Dendrogeomorphological analysis of landslides on the undercut river terrace bank (a case study in Czech Republic) K. Šilhán 10.1007/s10346-021-01833-z
1247. Risk assessment and management of rainfall-induced landslides in tropical regions: a review M. Amarasinghe et al. 10.1007/s11069-023-06277-3
1248. Spatiotemporal activity characteristic analysis and hazard assessment of rainfall-induced landslide for the Eurasian continent by considering mountain-hazards developing environment differences D. Cheng et al. 10.1007/s10064-025-04259-2