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Evaluating causative factors for landslide susceptibility along the Imphal-Jiribam railway corridor in the North-Eastern part of India using a GIS-based statistical approach.
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- Environmental Science & Pollution Research, 2024, v. 31, n. 41, p. 53767, doi. 10.1007/s11356-023-28966-z
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- Article
基于元学习的广域范围滑坡易发性小样本预测.
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- Geomatics & Information Science of Wuhan University, 2024, v. 49, n. 8, p. 1367, doi. 10.13203/j.whugis20220076
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基于样本优化策略的滑坡易发性评价.
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- Geomatics & Information Science of Wuhan University, 2024, v. 49, n. 8, p. 1492, doi. 10.13203/j.whugis20220527
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- Article
多维 CNN 耦合的滑坡易发性评价方法.
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- Geomatics & Information Science of Wuhan University, 2024, v. 49, n. 8, p. 1466, doi. 10.13203/j.whugis20220325
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- Article
Sustainable Forest Management and Natural Hazard Prevention.
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- Sustainability (2071-1050), 2024, v. 16, n. 16, p. 6915, doi. 10.3390/su16166915
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- Article
Study on Landslide Susceptibility Based on Multi-Model Coupling: A Case Study of Sichuan Province, China.
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- Sustainability (2071-1050), 2024, v. 16, n. 16, p. 6803, doi. 10.3390/su16166803
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- Article
An information quantity and machine learning integrated model for landslide susceptibility mapping in Jiuzhaigou, China.
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- Natural Hazards, 2024, v. 120, n. 11, p. 10185, doi. 10.1007/s11069-024-06602-4
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- Article
Regional-scale landslide modeling using machine learning and GIS: a case study for Idukki district, Kerala, India.
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- Natural Hazards, 2024, v. 120, n. 11, p. 9935, doi. 10.1007/s11069-024-06592-3
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- Article
The influence of cartographic representation on landslide susceptibility models: empirical evidence from a Brazilian UNESCO world heritage site.
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- Natural Hazards, 2024, v. 120, n. 11, p. 9527, doi. 10.1007/s11069-024-06576-3
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- Article
Assessing framework of rainfall-induced landslide hazard considering spatiotemporal asymmetry in extreme precipitation indices under climate change.
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- Theoretical & Applied Climatology, 2024, v. 155, n. 8, p. 7961, doi. 10.1007/s00704-024-05106-2
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- Article
Refined Landslide Susceptibility Mapping Considering Land Use Changes and InSAR Deformation: A Case Study of Yulin City, Guangxi.
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- Remote Sensing, 2024, v. 16, n. 16, p. 3016, doi. 10.3390/rs16163016
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- Article
Study of Earthquake Landslide Hazard by Defining Potential Landslide Thickness Using Excess Topography: A Case Study of the 2014 Ludian Earthquake Area, China.
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- Remote Sensing, 2024, v. 16, n. 16, p. 2951, doi. 10.3390/rs16162951
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Application of Artificial Intelligence and Remote Sensing for Landslide Detection and Prediction: Systematic Review.
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- Remote Sensing, 2024, v. 16, n. 16, p. 2947, doi. 10.3390/rs16162947
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- Article
A Comprehensive Comparison of Stable and Unstable Area Sampling Strategies in Large-Scale Landslide Susceptibility Models Using Machine Learning Methods.
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- Remote Sensing, 2024, v. 16, n. 16, p. 2923, doi. 10.3390/rs16162923
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Optimized Landslide Susceptibility Mapping and Modelling Using the SBAS-InSAR Coupling Model.
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- Remote Sensing, 2024, v. 16, n. 16, p. 2873, doi. 10.3390/rs16162873
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- Article
Stacking ensemble approach in data mining methods for landslide prediction.
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- Journal of Supercomputing, 2023, v. 79, n. 8, p. 8583, doi. 10.1007/s11227-022-05006-0
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- Article
Shaking Table Model Test on the Dynamic Response of Anti-dip Rock Slope.
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- Geotechnical & Geological Engineering, 2019, v. 37, n. 3, p. 1211, doi. 10.1007/s10706-018-0679-4
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Landslide Susceptibility Mapping Using Fuzzy Logic System and Its Influences on Mainlines in Lashgarak Region, Tehran, Iran.
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- Geotechnical & Geological Engineering, 2018, v. 36, n. 2, p. 915, doi. 10.1007/s10706-017-0365-y
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- Article
Evaluation of MLP and RBF Methods for Hazard Zonation of Landslides Triggered by the Twin Ahar-Varzeghan Earthquakes.
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- Geotechnical & Geological Engineering, 2017, v. 35, n. 5, p. 2163, doi. 10.1007/s10706-017-0236-6
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Assessment of Failure Mechanism and Rehabilitation of a Landslide Within Marly Formations in NW Greece: From the Site Investigation to the Geotechnical Design.
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- Geotechnical & Geological Engineering, 2014, v. 32, n. 6, p. 1485, doi. 10.1007/s10706-014-9729-8
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- Article
Geomechanical Characterization of Zhangmu Soil-Rock Mixture Deposit.
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- Geotechnical & Geological Engineering, 2014, v. 32, n. 5, p. 1329, doi. 10.1007/s10706-014-9808-x
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- Article
A Data Based Model to Predict Landslide Induced by Rainfall in Rio de Janeiro City.
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- Geotechnical & Geological Engineering, 2012, v. 30, n. 1, p. 85, doi. 10.1007/s10706-011-9451-8
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- Article
A preliminary method for the evaluation of the landslides volume at a regional scale.
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- GeoInformatica, 2009, v. 13, n. 3, p. 277, doi. 10.1007/s10707-008-0060-5
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- Article
Harmonizing Seismic Performance via Risk Targeted Spectra: State of the art, dependencies, and implementation proposals.
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- Earthquake Engineering & Structural Dynamics, 2023, v. 52, n. 13, p. 4277, doi. 10.1002/eqe.3941
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- Article
Sector collapse at Kick 'em Jenny submarine volcano (Lesser Antilles): numerical simulation and landslide behaviour.
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- Bulletin of Volcanology, 2012, v. 74, n. 2, p. 595, doi. 10.1007/s00445-011-0554-0
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- Article
Assessing landslide movements in volcanic islands using near-shore marine geophysical data: south Pico island, Azores.
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- Bulletin of Volcanology, 2012, v. 74, n. 2, p. 483, doi. 10.1007/s00445-011-0541-5
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Distinguishing volcanic debris avalanche deposits from their reworked products: the Perrier sequence (French Massif Central).
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- Bulletin of Volcanology, 2009, v. 71, n. 9, p. 1041, doi. 10.1007/s00445-009-0285-7
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- Article
Remote Sensing for Assessing Landslides and Associated Hazards.
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- Surveys in Geophysics, 2020, v. 41, n. 6, p. 1391, doi. 10.1007/s10712-020-09609-1
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- Article
GIS-Based Groundwater Potential Mapping in Khorramabad in Lorestan, Iran, using Frequency Ratio (FR) and Weights of Evidence (WoE) Models.
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- Water Resources, 2019, v. 46, n. 5, p. 679, doi. 10.1134/S0097807819050051
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- Article
Late Pleistocene Catastrophic Landslide from the Balaganchik Ridge: Evidence from the Mitoga 2 Reference Section (Western Kamchatka).
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- Lithology & Mineral Resources, 2021, v. 56, n. 1, p. 71, doi. 10.1134/S002449022006005X
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- Article
基于时序InSAR技术的滑坡隐患识别对比研究.
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- Remote Sensing for Natural Resources, 2022, v. 34, n. 3, p. 73, doi. 10.6046/zrzyyg.2021333
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天津蓟州五名山滑坡隐患早期识别监测.
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- Journal of Geodesy & Geodynamics (1671-5942), 2022, v. 42, n. 9, p. 881, doi. 10.14075/j.jgg.2022.09.001
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Multi-hazard risk assessment for resilient and sustainable urban areas.
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- Natural Hazards, 2024, v. 120, n. 10, p. 9107, doi. 10.1007/s11069-024-06760-5
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Landslide susceptibility assessment using different rainfall event-based landslide inventories: advantages and limitations.
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- Natural Hazards, 2024, v. 120, n. 10, p. 9361, doi. 10.1007/s11069-024-06691-1
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- Article
A modular framework for FAIR shallow landslide susceptibility mapping based on machine learning.
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- Natural Hazards, 2024, v. 120, n. 9, p. 8953, doi. 10.1007/s11069-024-06563-8
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- Article
A hybrid integration of analytical hierarchy process (AHP) and the multiobjective optimization on the basis of ratio analysis (MOORA) for landslide susceptibility zonation of Aizawl, India.
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- Natural Hazards, 2024, v. 120, n. 9, p. 8571, doi. 10.1007/s11069-024-06538-9
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Socio-geoenvironmental vulnerability index (SGeoVI) derived from hybrid modeling related to populations at-risk to landslides.
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- Natural Hazards, 2024, v. 120, n. 9, p. 8121, doi. 10.1007/s11069-024-06526-z
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- Article
Optimizing seismic hazard inputs for co-seismic landslide susceptibility mapping: a probabilistic analysis.
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- Natural Hazards, 2024, v. 120, n. 9, p. 8459, doi. 10.1007/s11069-024-06517-0
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- Article
Optimizing flood susceptibility assessment in semi-arid regions using ensemble algorithms: a case study of Moroccan High Atlas.
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- Natural Hazards, 2024, v. 120, n. 8, p. 7787, doi. 10.1007/s11069-024-06550-z
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- Article
Comparative analysis of the TabNet algorithm and traditional machine learning algorithms for landslide susceptibility assessment in the Wanzhou Region of China.
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- Natural Hazards, 2024, v. 120, n. 8, p. 7627, doi. 10.1007/s11069-024-06521-4
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- Article
Landslide development and susceptibility along the Yunling–Yanjing segment of the Lancang River using grid and slope units.
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- Natural Hazards, 2024, v. 120, n. 7, p. 6149, doi. 10.1007/s11069-024-06495-3
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Offshore application of landslide susceptibility mapping using gradient-boosted decision trees: a Gulf of Mexico case study.
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- Natural Hazards, 2024, v. 120, n. 7, p. 6223, doi. 10.1007/s11069-024-06492-6
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Landslide susceptibility mapping using morphological and hydrological parameters in Sikkim Himalaya: frequency ratio model and geospatial technologies.
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- Natural Hazards, 2024, v. 120, n. 7, p. 6797, doi. 10.1007/s11069-024-06491-7
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Prediction of rainfall-induced landslide using machine learning models along highway Bandipora to Gurez road, India.
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- Natural Hazards, 2024, v. 120, n. 7, p. 6169, doi. 10.1007/s11069-024-06405-7
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- Article
Pixel-based classification method for earthquake-induced landslide mapping using remotely sensed imagery, geospatial data and temporal change information.
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- Natural Hazards, 2024, v. 120, n. 6, p. 5163, doi. 10.1007/s11069-023-06399-8
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Application and interpretability of ensemble learning for landslide susceptibility mapping along the Three Gorges Reservoir area, China.
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- Natural Hazards, 2024, v. 120, n. 5, p. 4601, doi. 10.1007/s11069-023-06374-3
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Landslide susceptibility mapping and risk assessment using total estimated susceptibility values along NH44 in Jammu and Kashmir, Western Himalaya.
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- Natural Hazards, 2024, v. 120, n. 5, p. 4257, doi. 10.1007/s11069-023-06363-6
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Developing a hybrid deep learning model with explainable artificial intelligence (XAI) for enhanced landslide susceptibility modeling and management.
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- Natural Hazards, 2024, v. 120, n. 4, p. 3719, doi. 10.1007/s11069-023-06357-4
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An integrated approach for mapping slow-moving hillslopes and characterizing their activity using InSAR, slope units and a novel 2-D deformation scheme.
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- Natural Hazards, 2024, v. 120, n. 4, p. 3919, doi. 10.1007/s11069-023-06353-8
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Coastal rocky slopes instability analysis and landslide frequency-area distribution alongside the road network in west Mediterranean context (northern of Morocco).
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- Natural Hazards, 2024, v. 120, n. 4, p. 3401, doi. 10.1007/s11069-023-06342-x
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- Article