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51. 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
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54. 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
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58. 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
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74. 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
75. 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
76. 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
77. Slope deformation, reservoir variation and meteorological data at the Khoko landslide, Enguri hydroelectric basin (Georgia), during 2016–2019 A. Tibaldi et al. 10.5194/essd-13-3321-2021
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877. 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
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883. 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
884. 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
885. Laboratory Landquakes: Insights From Experiments Into the High‐Frequency Seismic Signal Generated by Geophysical Granular Flows M. Arran et al. 10.1029/2021JF006172
886. 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
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889. Fatal landslides in China from 1940 to 2020: occurrences and vulnerabilities S. Zhang et al. 10.1007/s10346-023-02034-6
890. Shape and Dimension Estimations of Landslide Rupture Zones via Correlations of Characteristic Parameters G. Domej et al. 10.3390/geosciences10050198
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892. Assessment of Physical Vulnerability and Uncertainties for Debris Flow Hazard: A Review concerning Climate Change M. Khan et al. 10.3390/land11122240
893. GIS-Based Expert Knowledge for Landslide Susceptibility Mapping (LSM): Case of Mostaganem Coast District, West of Algeria R. Senouci et al. 10.3390/su13020630
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895. Evaluation of social vulnerability to natural hazards: a case of Barton on Sea, England K. Kantamaneni 10.1007/s12517-019-4819-9
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903. 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
904. 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
905. The downward spiral entangling soil sealing and hydrogeological disasters A. Gatto et al. 10.1088/1748-9326/ad5fa1
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908. Landslides, a Key Landform in the Global Geological Heritage C. Morino et al. 10.3389/feart.2022.864760
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911. 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
912. 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
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914. 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
915. 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
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917. Landslide Risk Assessment in Eastern Kentucky, USA: Developing a Regional Scale, Limited Resource Approach M. Crawford et al. 10.3390/rs14246246
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921. Invited perspectives: Building sustainable and resilient communities – recommended actions for natural hazard scientists J. Gill et al. 10.5194/nhess-21-187-2021
922. 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
923. AutoGluon: A revolutionary framework for landslide hazard analysis W. Qi et al. 10.1016/j.nhres.2021.07.002
924. A comprehensive global database of giant landslides on volcanic islands J. Blahůt et al. 10.1007/s10346-019-01275-8
925. 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
926. 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
927. Simple rules to minimise exposure to coseismic landslide hazard D. Milledge et al. 10.5194/nhess-19-837-2019
928. Multisource Data Fusion and Adversarial Nets for Landslide Extraction from UAV-Photogrammetry-Derived Data H. He et al. 10.3390/rs14133059
929. Causes of episodic movement of the Baijiabao landslide based on multiple-time scale analysis Z. Fu et al. 10.1007/s10346-023-02201-9
930. An InSAR and depth-integrated coupled model for potential landslide hazard assessment S. Zhou et al. 10.1007/s11440-021-01429-w
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932. Assessing Urban Landslide Dynamics through Multi-Temporal InSAR Techniques and Slope Numerical Modeling N. Necula et al. 10.3390/rs13193862
933. 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
934. 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
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937. 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
938. Worldwide Research Trends in Landslide Science P. Carrión-Mero et al. 10.3390/ijerph18189445
939. 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
940. 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
941. Landslide risk assessment by integrating hazards and vulnerability indices in Southeast Bangladesh N. Sultana et al. 10.1016/j.ijdrr.2024.104991
942. EFFECT OF PARTICLE SIZE DISTRIBUTIONS ON GRANULAR FLOW SIMULATIONS USING DISCRETE ELEMENT METHOD D. WATANABE et al. 10.2208/jscejge.77.4_392
943. 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
944. 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
945. 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
946. 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
947. Random forest-based screening of environmental geohazard probability factors in Panshi city, China L. Qi et al. 10.1016/j.asr.2024.09.055
948. 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
949. 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
950. 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
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955. Landslides Detection and Mapping with an Advanced Multi-Temporal Satellite Optical Technique V. Satriano et al. 10.3390/rs15030683
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958. 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
959. CHILDA – Czech Historical Landslide Database M. Bíl et al. 10.5194/nhess-21-2581-2021
960. 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
961. 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
962. An Assessment of Negative Samples and Model Structures in Landslide Susceptibility Characterization Based on Bayesian Network Models S. Khabiri et al. 10.3390/rs15123200
963. Towards hydrometeorological thresholds of reservoir-induced landslide from subsurface strain observations X. Ye et al. 10.1007/s11431-023-2657-3
964. Assessment of landslide susceptibility and risk factors in China D. Wang et al. 10.1007/s11069-021-04812-8
965. Multi-hazard susceptibility and exposure assessment of the Hindu Kush Himalaya J. Rusk et al. 10.1016/j.scitotenv.2021.150039
966. Spatiotemporal Analysis of Ecological Security Based on Landscape Patterns H. Zhang et al. 10.3390/ijgi13060204
967. Temporal and spatial distributions of landslides in the Qinba Mountains, Shaanxi Province, China H. Qiu et al. 10.1080/19475705.2018.1536080
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969. Nationwide Susceptibility Mapping of Landslides in Kenya Using the Fuzzy Analytic Hierarchy Process Model S. Zhou et al. 10.3390/land9120535
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971. Influence of sampling design on landslide susceptibility modeling in lithologically heterogeneous areas A. Dornik et al. 10.1038/s41598-022-06257-w
972. Machine learning-based assessment of regional-scale variation of landslide susceptibility in central Vietnam R. Das et al. 10.1371/journal.pone.0308494
973. 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
974. 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
975. 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
976. 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
977. Highway Proneness Appraisal to Landslides along Taiping to Ipoh Segment Malaysia, Using MCDM and GIS Techniques I. Yamusa et al. 10.3390/su14159096
978. 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
979. Landslide Risk Modeling using Data Mining in Hyrcanian Forests N. Nazariani & A. Fallah 10.61186/jwmr.14.27.123
980. 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
981. Future climate change implications in Bhutan from a downscaled and bias‐adjusted CMIP6 multimodel ensemble F. Lehner et al. 10.1002/joc.8623
982. 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
983. Rainfall-Induced Landslide Assessment under Different Precipitation Thresholds Using Remote Sensing Data: A Central Andes Case G. Maragaño-Carmona et al. 10.3390/w15142514
984. Calibration and Performance Evaluation of Cost-Effective Capacitive Moisture Sensor in Slope Model Experiments M. Hidayat et al. 10.3390/s24248156
985. 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
986. Application of novel distributed fibre-optic sensing for slope deformation monitoring: a comprehensive review A. Acharya & T. Kogure 10.1007/s13762-022-04697-5
987. 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
988. 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
989. Exploring disaster ontologies from Chinese and Western perspectives: commonalities and nuances S. Goodall et al. 10.1108/DPM-03-2021-0108
990. 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
991. 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
992. Engineering geomorphological investigation of the Kasavu landslide, Viti Levu, Fiji A. Ram et al. 10.1007/s10346-019-01191-x
993. 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
994. Research on Uncertainty of Landslide Susceptibility Prediction—Bibliometrics and Knowledge Graph Analysis Z. Yang et al. 10.3390/rs14163879
995. 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
996. Global Dynamic Rainfall-Induced Landslide Susceptibility Mapping Using Machine Learning B. Li et al. 10.3390/rs14225795
997. 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
998. 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
999. Research on SSA-LSTM-Based Slope Monitoring and Early Warning Model S. Yang et al. 10.3390/su141610246
1000. A New Deep Learning Neural Network Model for the Identification of InSAR Anomalous Deformation Areas T. Zhang et al. 10.3390/rs14112690
1001. Editorial: Big Earth Data for Disaster Risk Reduction F. Chen et al. 10.3389/feart.2021.727547
1002. 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
1003. 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
1004. 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
1005. 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
1006. Rainfall infiltration and slope stability of alpine colluvial terraces subject to storms (NE Italy) P. Paronuzzi & A. Bolla 10.1016/j.enggeo.2023.107199
1007. Roads and landslides in Nepal: how development affects environmental risk B. McAdoo et al. 10.5194/nhess-18-3203-2018
1008. 2-D Cross-Plot Model Analysis Using Integrated Geophysical Methods for Landslides Assessment M. Zakaria et al. 10.3390/app11020747
1009. An integrated approach based landslide susceptibility mapping: case of Muzaffarabad region, Pakistan M. Basharat et al. 10.1080/19475705.2023.2210255
1010. How water, wind, waves and ice shape landscapes and landforms: Historical contributions to geomorphic science J. Gardner 10.1016/j.geomorph.2019.02.031
1011. Sustainable rural infrastructure: guidelines for roadside slope excavation P. Paudyal et al. 10.1186/s40677-023-00240-x
1012. Mass Movement Hazard and Exposure in the Himalaya S. Dubey et al. 10.1029/2022EF003253
1013. A novel approach for displacement interval forecasting of landslides with step-like displacement pattern Q. Ge et al. 10.1080/17499518.2021.1892769
1014. Redefining landslide susceptibility under extreme rainfall events using deep learning A. Achu et al. 10.1016/j.geomorph.2023.109033
1015. Physics-informed data assimilation model for displacement prediction of hydrodynamic pressure-driven landslide Y. Liu et al. 10.1016/j.compgeo.2024.106085
1016. 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
1017. 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
1018. Improving the forecast performance of landslide susceptibility mapping by using ensemble gradient boosting algorithms H. Ha et al. 10.1007/s10668-024-04694-3
1019. 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
1020. The Alasu rock avalanche in the Tianshan Mountains, China: fragmentation, landforms, and kinematics Q. Lin et al. 10.1007/s10346-023-02167-8
1021. 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
1022. Enhanced landslide susceptibility zonation using GIS-Based ensemble techniques A. Sharma et al. 10.1007/s12665-024-12032-z
1023. Evaluating landslide susceptibility: an AHP method-based approach enhanced with optimized random forest modeling X. Zhang et al. 10.1007/s11069-023-06306-1
1024. Identifying Potential Landslides on Giant Niexia Slope (China) Based on Integrated Multi-Remote Sensing Technologies X. Dong et al. 10.3390/rs14246328
1025. Post‐landslide soil and vegetation recovery in a dry, montane system is slow and patchy B. Buma & Ł. Pawlik 10.1002/ecs2.3346
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