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Landslide susceptibility mapping based on Support Vector Machine: A case study on natural slopes of Hong Kong, China
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Land subsidence hazard assessment based on novel hybrid approach: BWM, weighted overlay index (WOI), and support vector machine (SVM)
inferred← citeshttps://doi.org/10.1007/s11069-023-05865-7openalex-snapshot
Uncertainty in regional scale assessment of landslide susceptibility using various resolutions
inferred← citeshttps://doi.org/10.1007/s11069-024-06596-zopenalex-snapshot
Classification machine learning models for urban flood hazard mapping: case study of Zaio, NE Morocco
inferred← citeshttps://doi.org/10.1007/s11069-024-06665-3openalex-snapshot
A support vector machine model of landslide susceptibility mapping based on hyperparameter optimization using the Bayesian algorithm: a case study of the highways in the southern Qinghai–Tibet Plateau
inferred← citeshttps://doi.org/10.1007/s11069-024-06930-5openalex-snapshot
Spatial variations of landslide severity with respect to meteorological and soil related factors
inferred← citeshttps://doi.org/10.1007/s11069-025-07579-4openalex-snapshot
Physics-based landslide susceptibility machine learning model for mountainous solar power plants
inferred← citeshttps://doi.org/10.1007/s11069-026-08261-zopenalex-snapshot
Comparative assessment of ensemble machine learning models for landslide susceptibility mapping in Kohima–Mokokchung, Nagaland, India
inferred← citeshttps://doi.org/10.1007/s11269-017-1660-3openalex-snapshot
Application of Support Vector Machine, Random Forest, and Genetic Algorithm Optimized Random Forest Models in Groundwater Potential Mapping
inferred← citeshttps://doi.org/10.1007/s11356-020-09281-3openalex-snapshot
Disaster resilience assessment based on the spatial and temporal aggregation effects of earthquake-induced hazards
inferred← citeshttps://doi.org/10.1007/s11356-022-20213-1openalex-snapshot
Advanced machine learning algorithms for flood susceptibility modeling — performance comparison: Red Sea, Egypt
inferred← citeshttps://doi.org/10.1007/s11356-023-31688-xopenalex-snapshot
Dynamic landslide susceptibility mapping based on the PS-InSAR deformation intensity
inferred← citeshttps://doi.org/10.1007/s11356-024-34949-5openalex-snapshot
Predictive landslide susceptibility modeling in the southeastern hilly region of Bangladesh: application of machine learning algorithms in Khagrachari district
inferred← citeshttps://doi.org/10.1007/s11431-010-3219-xopenalex-snapshot
A new method of pseudo absence data generation in landslide susceptibility mapping with a case study of Shenzhen
inferred← citeshttps://doi.org/10.1007/s11442-017-1386-4openalex-snapshot
Comparative evaluation of geological disaster susceptibility using multi-regression methods and spatial accuracy validation
inferred← citeshttps://doi.org/10.1007/s11600-025-01769-1openalex-snapshot
A systematic review and comprehensive evaluation of artificial intelligence approaches for prediction flood susceptibility
inferred← citeshttps://doi.org/10.1007/s11629-013-2847-6openalex-snapshot
Landslide susceptibility mapping along Bhalubang — Shiwapur area of mid-Western Nepal using frequency ratio and conditional probability models
inferred← citeshttps://doi.org/10.1007/s11629-014-3134-xopenalex-snapshot
Using statistical learning algorithms in regional landslide susceptibility zonation with limited landslide field data
inferred← citeshttps://doi.org/10.1007/s11629-016-4126-9openalex-snapshot
Landslide susceptibility mapping using an integrated model of information value method and logistic regression in the Bailongjiang watershed, Gansu Province, China
inferred← citeshttps://doi.org/10.1007/s11629-017-4363-6openalex-snapshot
Predicting landslide scenes under potential earthquake scenarios in the Xianshuihe fault zone, Southwest China
inferred← citeshttps://doi.org/10.1007/s11629-017-4404-1openalex-snapshot
Evaluating effectiveness of frequency ratio, fuzzy logic and logistic regression models in assessing landslide susceptibility: a case from Rudraprayag district, India
inferred← citeshttps://doi.org/10.1007/s11629-018-4884-7openalex-snapshot
Optimization of causative factors using logistic regression and artificial neural network models for landslide susceptibility assessment in Ujung Loe Watershed, South Sulawesi Indonesia
inferred← citeshttps://doi.org/10.1007/s11629-020-6471-yopenalex-snapshot
Comparison of different sampling strategies for debris flow susceptibility mapping: A case study using the centroids of the scarp area, flowing area and accumulation area of debris flow watersheds
inferred← citeshttps://doi.org/10.1007/s11629-025-0006-5openalex-snapshot
Research progress in landslide susceptibility assessment driven by machine learning: A bibliometric analysis
inferred← citeshttps://doi.org/10.1007/s11707-018-0704-1openalex-snapshot
Unsupervised learning on scientific ocean drilling datasets from the South China Sea
inferred← citeshttps://doi.org/10.1007/s11709-022-0858-5openalex-snapshot
Structural performance assessment of GFRP elastic gridshells by machine learning interpretability methods
inferred← citeshttps://doi.org/10.1007/s11859-019-1395-5openalex-snapshot
Susceptibility Assessment of Landslides in Alpine-Canyon Region Using Multiple GIS-Based Models
inferred← citeshttps://doi.org/10.1007/s12040-013-0282-2openalex-snapshot
Landslide susceptibility mapping using support vector machine and GIS at the Golestan Province, Iran
inferred← citeshttps://doi.org/10.1007/s12040-019-1159-9openalex-snapshot
Landslide susceptibility mapping of the Tehri reservoir rim area using the weights of evidence method
inferred← citeshttps://doi.org/10.1007/s12145-018-0335-9openalex-snapshot
A comparison of slope units and grid cells as mapping units for landslide susceptibility assessment
inferred← citeshttps://doi.org/10.1007/s12145-022-00889-2openalex-snapshot
Landslide identification using machine learning techniques: Review, motivation, and future prospects
inferred← citeshttps://doi.org/10.1007/s12145-024-01453-wopenalex-snapshot
A debris flow susceptibility mapping study considering sample heterogeneity
inferred← citeshttps://doi.org/10.1007/s12145-025-01816-xopenalex-snapshot
Predicting flood risks using advanced machine learning algorithms with a focus on Bangladesh: influencing factors, gaps and future challenges
inferred← citeshttps://doi.org/10.1007/s12145-025-01833-wopenalex-snapshot
Estimation of soil properties using machine learning techniques to improve hydrological modeling in a semiarid environment: Campo de Cartagena (Spain)
inferred← citeshttps://doi.org/10.1007/s12145-025-01862-5openalex-snapshot
Landslide hazard zonation using advanced machine learning algorithms based on statistical models (Case study: Sarvabad, Iran)
inferred← citeshttps://doi.org/10.1007/s12303-018-0038-8openalex-snapshot
Comparison of landslide susceptibility maps using random forest and multivariate adaptive regression spline models in combination with catchment map units
inferred← citeshttps://doi.org/10.1007/s12303-024-0044-yopenalex-snapshot
Deep learning algorithms based landslide vulnerability modeling in highly landslide prone areas of Tamil Nadu, India
inferred← citeshttps://doi.org/10.1007/s12517-012-0610-xopenalex-snapshot
Landslide susceptibility mapping at Vaz Watershed (Iran) using an artificial neural network model: a comparison between multilayer perceptron (MLP) and radial basic function (RBF) algorithms
inferred← citeshttps://doi.org/10.1007/s12517-012-0646-yopenalex-snapshot
Controlling parameter analyses and hazard mapping for earthquake-triggered landslides: an example from a square region in Beichuan County, Sichuan Province, China
inferred← citeshttps://doi.org/10.1007/s12517-012-0807-zopenalex-snapshot
Application of frequency ratio, statistical index, and weights-of-evidence models and their comparison in landslide susceptibility mapping in Central Nepal Himalaya
inferred← citeshttps://doi.org/10.1007/s12517-012-0825-xopenalex-snapshot
GIS-based landslide susceptibility mapping with probabilistic likelihood ratio and spatial multi-criteria evaluation models (North of Tehran, Iran)
inferred← citeshttps://doi.org/10.1007/s12517-014-1369-zopenalex-snapshot
Landslide susceptibility mapping based on GIS and information value model for the Chencang District of Baoji, China
inferred← citeshttps://doi.org/10.1007/s12517-016-2722-1openalex-snapshot
Landslide susceptibility zonation using GIS and evidential belief function model
inferred← citeshttps://doi.org/10.1007/s12517-017-2918-zopenalex-snapshot
Comparing GIS-based support vector machine kernel functions for landslide susceptibility mapping
inferred← citeshttps://doi.org/10.1007/s12517-017-3026-9openalex-snapshot
Spatial distribution analysis and susceptibility mapping of landslides triggered before and after Mw7.8 Gorkha earthquake along Upper Bhote Koshi, Nepal
inferred← citeshttps://doi.org/10.1007/s12517-020-5060-2openalex-snapshot
Landsat images and artificial intelligence techniques used to map volcanic ashfall and pyroclastic material following the eruption of Mount Agung, Indonesia
inferred← citeshttps://doi.org/10.1007/s12517-021-07006-5openalex-snapshot
Applying support vector machines optimized by genetic algorithm for estimating the spatial distribution of mean annual precipitation
inferred← citeshttps://doi.org/10.1007/s12517-021-07532-2openalex-snapshot
Performance analysis of landslide susceptibility assessment under different factor-filtering models
inferred← citeshttps://doi.org/10.1007/s12517-024-12022-2openalex-snapshot
Comparative landslide susceptibility assessment using information value and frequency ratio bivariate statistical methods: a case study from Northwestern Himalayas, Jammu and Kashmir, India
inferred← citeshttps://doi.org/10.1007/s12518-018-0229-zopenalex-snapshot
A comparative analysis of artificial neural network (ANN), wavelet neural network (WNN), and support vector machine (SVM) data-driven models to mineral potential mapping for copper mineralizations in the Shahr-e-Babak region, Kerman, Iran
inferred← citeshttps://doi.org/10.1007/s12524-018-0791-1openalex-snapshot
Spatial Prediction of Rainfall-Induced Landslides Using Aggregating One-Dependence Estimators Classifier
inferred← citeshttps://doi.org/10.1007/s12524-022-01582-zopenalex-snapshot
Application of Machine Learning and Geospatial Techniques for Groundwater Potential Mapping
inferred← citeshttps://doi.org/10.1007/s12524-024-02091-xopenalex-snapshot
Synergetic Usage of Different Landslide Susceptibility Maps to Assess Landslide Hazard Potential in Wayanad District, Kerala
inferred← citeshttps://doi.org/10.1007/s12583-012-0236-7openalex-snapshot
Landslide hazard mapping using GIS and weight of evidence model in Qingshui River watershed of 2008 Wenchuan earthquake struck region
inferred← citeshttps://doi.org/10.1007/s12594-015-0242-3openalex-snapshot
Classification of Alteration Zones Based on Whole-rock Geochemical Data using Support Vector Machine
inferred← citeshttps://doi.org/10.1007/s12594-018-0862-5openalex-snapshot
A Novel Classifier Based on Composite Hyper-cubes on Iterated Random Projections for Assessment of Landslide Susceptibility
inferred← citeshttps://doi.org/10.1007/s12665-009-0394-9openalex-snapshot
Comparison of landslide susceptibility mapping methodologies for Koyulhisar, Turkey: conditional probability, logistic regression, artificial neural networks, and support vector machine
inferred← citeshttps://doi.org/10.1007/s12665-010-0531-5openalex-snapshot
Application of Dempster-Shafer theory of evidence to GIS-based landslide susceptibility analysis
inferred← citeshttps://doi.org/10.1007/s12665-010-0705-1openalex-snapshot
Use of GIS-based fuzzy logic relations and its cross application to produce landslide susceptibility maps in three test areas in Malaysia
inferred← citeshttps://doi.org/10.1007/s12665-011-1196-4openalex-snapshot
GIS-based landslide susceptibility mapping using bivariate statistical analysis in Devrek (Zonguldak-Turkey)
inferred← citeshttps://doi.org/10.1007/s12665-013-2217-2openalex-snapshot
Landslide susceptibility mapping using rough sets and back-propagation neural networks in the Three Gorges, China
inferred← citeshttps://doi.org/10.1007/s12665-013-2628-0openalex-snapshot
Appraisal of land use/land cover of mangrove forest ecosystem using support vector machine
inferred← citeshttps://doi.org/10.1007/s12665-013-2863-4openalex-snapshot
Landslide susceptibility assessment using object mapping units, decision tree, and support vector machine models in the Three Gorges of China
inferred← citeshttps://doi.org/10.1007/s12665-014-3389-0openalex-snapshot
Landslide susceptibility mapping by comparing the WLC and WofE multi-criteria methods in the West Crete Island, Greece
inferred← citeshttps://doi.org/10.1007/s12665-014-3442-zopenalex-snapshot
Using maximum entropy modeling for landslide susceptibility mapping with multiple geoenvironmental data sets
inferred← citeshttps://doi.org/10.1007/s12665-014-3749-9openalex-snapshot
RETRACTED ARTICLE: GIS-based landslide susceptibility mapping using analytical hierarchy process (AHP) and certainty factor (CF) models for the Baozhong region of Baoji City, China
inferred← citeshttps://doi.org/10.1007/s12665-014-3775-7openalex-snapshot
Evaluating landslide hazards using RCP 4.5 and 8.5 scenarios
inferred← citeshttps://doi.org/10.1007/s12665-015-4028-0openalex-snapshot
Remote sensing and GIS-based landslide susceptibility mapping using frequency ratio, logistic regression, and fuzzy logic methods at the central Zab basin, Iran
inferred← citeshttps://doi.org/10.1007/s12665-015-4866-9openalex-snapshot
Spatial prediction of landslide hazard at the Luxi area (China) using support vector machines
inferred← citeshttps://doi.org/10.1007/s12665-015-5093-0openalex-snapshot
Landslide susceptibility mapping based on GIS and support vector machine models for the Qianyang County, China
inferred← citeshttps://doi.org/10.1007/s12665-015-5233-6openalex-snapshot
Landslide susceptibility mapping using an ensemble statistical index (Wi) and adaptive neuro-fuzzy inference system (ANFIS) model at Alborz Mountains (Iran)
inferred← citeshttps://doi.org/10.1007/s12665-016-5580-yopenalex-snapshot
GIS based frequency ratio and index of entropy models to landslide susceptibility mapping (Daguan, China)
inferred← citeshttps://doi.org/10.1007/s12665-016-5774-3openalex-snapshot
A novel hybrid KPCA and SVM with PSO model for identifying debris flow hazard degree: a case study in Southwest China
inferred← citeshttps://doi.org/10.1007/s12665-016-5919-4openalex-snapshot
GIS-based modeling of rainfall-induced landslides using data mining-based functional trees classifier with AdaBoost, Bagging, and MultiBoost ensemble frameworks
inferred← citeshttps://doi.org/10.1007/s12665-016-6211-3openalex-snapshot
Evaluation of different models in rainfall-triggered landslide susceptibility mapping: a case study in Chunan, southeast China
inferred← citeshttps://doi.org/10.1007/s12665-017-6640-7openalex-snapshot
A comparative study of landslide susceptibility mapping using weight of evidence, logistic regression and support vector machine and evaluated by SBAS-InSAR monitoring: Zhouqu to Wudu segment in Bailong River Basin, China
inferred← citeshttps://doi.org/10.1007/s12665-017-6689-3openalex-snapshot
A comparative study of sequential minimal optimization-based support vector machines, vote feature intervals, and logistic regression in landslide susceptibility assessment using GIS
inferred← citeshttps://doi.org/10.1007/s12665-018-7268-yopenalex-snapshot
Bagging based Support Vector Machines for spatial prediction of landslides
inferred← citeshttps://doi.org/10.1007/s12665-018-7548-6openalex-snapshot
Developing a landslide susceptibility map based on remote sensing, fuzzy logic and expert knowledge of the Island of Lefkada, Greece
inferred← citeshttps://doi.org/10.1007/s12665-019-8094-6openalex-snapshot
A comparison of GIS-based landslide susceptibility assessment of the Satuk village (Yenice, NW Turkey) by frequency ratio and multi-criteria decision methods
inferred← citeshttps://doi.org/10.1007/s12665-019-8562-zopenalex-snapshot
A comparative study of support vector machine and logistic model tree classifiers for shallow landslide susceptibility modeling
inferred← citeshttps://doi.org/10.1007/s12665-021-09381-4openalex-snapshot
Evaluation of landslide susceptibility based on the occurrence mechanism of landslide: a case study in Yuan' an county, China
inferred← citeshttps://doi.org/10.1007/s12665-021-09599-2openalex-snapshot
Modeling gully erosion susceptibility in Phuentsholing, Bhutan using deep learning and basic machine learning algorithms
inferred← citeshttps://doi.org/10.1007/s12665-021-09711-6openalex-snapshot
Henry’s gas solubility optimization algorithm in formulating deep neural network for landslide susceptibility assessment in mountainous areas
inferred← citeshttps://doi.org/10.1007/s12665-021-09737-wopenalex-snapshot
Landslide susceptibility assessment for a transmission line in Gansu Province, China by using a hybrid approach of fractal theory, information value, and random forest models
inferred← citeshttps://doi.org/10.1007/s12665-021-09788-zopenalex-snapshot
A hybrid model using data mining and multi-criteria decision-making methods for landslide risk mapping at Golestan Province, Iran
inferred← citeshttps://doi.org/10.1007/s12665-021-09910-1openalex-snapshot
Landslide susceptibility in the Belt and Road Countries: continental step of a multi-scale approach
inferred← citeshttps://doi.org/10.1007/s12665-022-10233-yopenalex-snapshot
Landslide susceptibility mapping: improvements in variable weights estimation through machine learning algorithms—a case study of upper Indus River Basin, Pakistan
inferred← citeshttps://doi.org/10.1007/s12665-022-10375-zopenalex-snapshot
Evaluation of landslide susceptibility of the Ya’an–Linzhi section of the Sichuan–Tibet Railway based on deep learning
inferred← citeshttps://doi.org/10.1007/s12665-023-10846-xopenalex-snapshot
A comparative study of different machine learning models for landslide susceptibility prediction: a case study of Kullu-to-Rohtang pass transport corridor, India
inferred← citeshttps://doi.org/10.1007/s13369-022-06560-8openalex-snapshot
Predictive Performances of Ensemble Machine Learning Algorithms in Landslide Susceptibility Mapping Using Random Forest, Extreme Gradient Boosting (XGBoost) and Natural Gradient Boosting (NGBoost)
inferred← citeshttps://doi.org/10.1007/s13753-022-00401-wopenalex-snapshot
Machine Learning-Based Evaluation of Susceptibility to Geological Hazards in the Hengduan Mountains Region, China
inferred← citeshttps://doi.org/10.1007/s40098-024-00957-yopenalex-snapshot
Comparative Analysis of Machine Learning, Statistical, and MCDA Methods for Rainfall-Induced Landslide Susceptibility Mapping in the Eco-Sensitive Koyna River Basin of India
inferred← citeshttps://doi.org/10.1007/s40808-016-0240-5openalex-snapshot
Uncertainty in landslide occurrence prediction using Dempster–Shafer theory
inferred← citeshttps://doi.org/10.1007/s40808-023-01914-zopenalex-snapshot
Innovative methods for rapid flood inundation mapping in Pul-e-Alam and Khoshi districts of Afghanistan using Landsat 9 images: spectral indices vs. machine learning models
inferred← citeshttps://doi.org/10.1007/s41324-025-00640-1openalex-snapshot
Landslide susceptibility mapping along Taba Penanjung area, Bengkulu province, Indonesia using machine learning (ML) techniques
inferred← citeshttps://doi.org/10.1007/s41748-020-00179-1openalex-snapshot
Estimating the Impact of Daily Weather on the Temporal Pattern of COVID-19 Outbreak in India
inferred← citeshttps://doi.org/10.1007/s42452-020-03307-8openalex-snapshot
Three oversampling methods applied in a comparative landslide spatial research in Penang Island, Malaysia
inferred← citeshttps://doi.org/10.1007/s43538-024-00305-xopenalex-snapshot
A holistic approach of remote sensing, GIS, and machine learning for shallow landslide susceptibility mapping in Gaganbawada region of Western Ghats, India
inferred← citeshttps://doi.org/10.1007/s43621-025-02084-xopenalex-snapshot
Remote sensing and GIS-driven landslide susceptibility mapping using machine learning for sustainable land management: a study from the Chittagong Hill Tracts of Bangladesh
inferred← citeshttps://doi.org/10.1016/b978-0-12-409548-9.10461-0openalex-snapshot
Assessment of GIS-Based Machine Learning Algorithms for Spatial Modeling of Landslide Susceptibility: Case Study in Iran
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