Comparative analysis of gradient boosting algorithms for landslide susceptibility mapping

An efficient XGBoost–DNN-based classification model for network intrusion detection system

(2020) Preethi Devan et al.   NEURAL COMPUTING & APPLICATIONS

Multi-geohazards susceptibility mapping based on machine learning—a case study in Jiuzhaigou, China

(2020) Juan Cao et al.   NATURAL HAZARDS

Comparison of Support Vector Machine, Bayesian Logistic Regression, and Alternating Decision Tree Algorithms for Shallow Landslide Susceptibility Mapping along a Mountainous Road in the West of Iran

(2020) Viet-Ha Nhu et al.   Applied Sciences-Basel

Comparison of Approaches for Urban Functional Zones Classification Based on Multi-Source Geospatial Data: A Case Study in Yuzhong District, Chongqing, China

(2019) Kai Cao et al.   Sustainability

Performance Analysis of Advanced Decision Tree-Based Ensemble Learning Algorithms for Landslide Susceptibility Mapping

(2019) Emrehan Kutlug Sahin et al.   Geocarto International

Random forest and artificial neural networks in landslide susceptibility modeling: a case study of the Fão River Basin, Southern Brazil

(2019) Guilherme Garcia de Oliveira et al.   NATURAL HAZARDS

Data Mining and Statistical Approaches in Debris-Flow Susceptibility Modelling Using Airborne LiDAR Data

(2019) Usman Salihu Lay et al.   SENSORS

Identification of soil erosion-susceptible areas using fuzzy logic and analytical hierarchy process modeling in an agricultural watershed of Burdwan district, India

(2019) Sunil Saha et al.   Environmental Earth Sciences

Performance Evaluation of the GIS-Based Data-Mining Techniques Decision Tree, Random Forest, and Rotation Forest for Landslide Susceptibility Modeling

(2019) Soyoung Park et al.   Sustainability

Parameters Derived from and/or Used with Digital Elevation Models (DEMs) for Landslide Susceptibility Mapping and Landslide Risk Assessment: A Review

(2019) Nayyer Saleem et al.   ISPRS International Journal of Geo-Information

Spatial mapping of the provenance of storm dust: Application of data mining and ensemble modelling

(2019) Hamid Gholami et al.   ATMOSPHERIC RESEARCH

Landslide susceptibility mapping using J48 Decision Tree with AdaBoost, Bagging and Rotation Forest ensembles in the Guangchang area (China)

(2018) Haoyuan Hong et al.   CATENA

Landslide susceptibility modeling applying machine learning methods: A case study from Longju in the Three Gorges Reservoir area, China

(2018) Chao Zhou et al.   COMPUTERS & GEOSCIENCES

Landslide susceptibility mapping using maximum entropy and support vector machine models along the highway corridor, Garhwal Himalaya

(2018) Vijendra Kumar Pandey et al.   Geocarto International

A Comparative Assessment of Canonical Correlation Forest, Random Forest, Rotation Forest and Logistic Regression Methods for Landslide Susceptibility Mapping

(2018) Emrehan Kutlug Sahin et al.   Geocarto International

Landslide susceptibility mapping & prediction using Support Vector Machine for Mandakini River Basin, Garhwal Himalaya, India

(2017) Deepak Kumar et al.   GEOMORPHOLOGY

A novel hybrid artificial intelligence approach based on the rotation forest ensemble and naïve Bayes tree classifiers for a landslide susceptibility assessment in Langao County, China

(2017) Wei Chen et al.   Geomatics Natural Hazards & Risk

Random forests and evidential belief function-based landslide susceptibility assessment in Western Mazandaran Province, Iran

(2016) Hamid Reza Pourghasemi et al.   Environmental Earth Sciences

A comparative study on the landslide susceptibility mapping using evidential belief function and weights of evidence models

(2016) QIQING WANG et al.   Journal of Earth System Science

A novel fuzzy K-nearest neighbor inference model with differential evolution for spatial prediction of rainfall-induced shallow landslides in a tropical hilly area using GIS

(2016) Dieu Tien Bui et al.   Landslides

Prediction of shallow landslide occurrence: Validation of a physically-based approach through a real case study

(2016) Luca Schilirò et al.   SCIENCE OF THE TOTAL ENVIRONMENT

Evaluating machine learning and statistical prediction techniques for landslide susceptibility modeling

(2015) J.N. Goetz et al.   COMPUTERS & GEOSCIENCES

GIS-based assessment of landslide susceptibility using certainty factor and index of entropy models for the Qianyang County of Baoji city, China

(2015) Qiqing Wang et al.   Journal of Earth System Science

Binary logistic regression versus stochastic gradient boosted decision trees in assessing landslide susceptibility for multiple-occurring landslide events: application to the 2009 storm event in Messina (Sicily, southern Italy)

(2015) L. Lombardo et al.   NATURAL HAZARDS

Prediction of water pollution sources using artificial neural networks in the study areas of Sivas, Karabük and Bartın (Turkey)

(2014) Tülay Ekemen Keskin et al.   Environmental Earth Sciences

Evaluation and comparison of landslide susceptibility mapping methods: a case study for the Ulus district, Bartın, northern Turkey

(2014) Arif Mert Eker et al.   INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE

An assessment of multivariate and bivariate approaches in landslide susceptibility mapping: a case study of Duzkoy district

(2014) Taskin Kavzoglu et al.   NATURAL HAZARDS

Optimization of landslide conditioning factors using very high-resolution airborne laser scanning (LiDAR) data at catchment scale

(2014) Mustafa Neamah Jebur et al.   REMOTE SENSING OF ENVIRONMENT

A regional level preliminary landslide susceptibility study of the upper Indus river basin

(2014) M. Farooq Ahmed et al.   European Journal of Remote Sensing

Risk assessment of soil erosion in semi-arid mountainous watershed in Saudi Arabia by RUSLE model coupled with remote sensing and GIS

(2014) Javed Mallick et al.   Geocarto International

GIS-based landslide susceptibility mapping with probabilistic likelihood ratio and spatial multi-criteria evaluation models (North of Tehran, Iran)

(2013) H. R. Pourghasemi et al.   Arabian Journal of Geosciences

Evaluation of prediction capability of the artificial neural networks for mapping landslide susceptibility in the Turbolo River catchment (northern Calabria, Italy)

(2013) Massimo Conforti et al.   CATENA

First steps towards a landslide inventory map of the Central Karakoram National Park

(2013) Chiara Calligaris et al.   European Journal of Remote Sensing

A comparative assessment of prediction capabilities of Dempster–Shafer and Weights-of-evidence models in landslide susceptibility mapping using GIS

(2012) HamidReza Pourghasemi et al.   Geomatics Natural Hazards & Risk

An easy-to-use MATLAB program (MamLand) for the assessment of landslide susceptibility using a Mamdani fuzzy algorithm

(2011) A. Akgun et al.   COMPUTERS & GEOSCIENCES

Landslide susceptibility assessment: what are the effects of mapping unit and mapping method?

(2011) A. Erener et al.   Environmental Earth Sciences

Landslide susceptibility mapping in Injae, Korea, using a decision tree

(2010) Young-Kwang Yeon et al.   ENGINEERING GEOLOGY

Assessment of Landslide Susceptibility by Decision Trees in the Metropolitan Area of Istanbul, Turkey

(2010) H. A. Nefeslioglu et al.   MATHEMATICAL PROBLEMS IN ENGINEERING

Geomorphology and GIS analysis for mapping gully erosion susceptibility in the Turbolo stream catchment (Northern Calabria, Italy)

(2010) Massimo Conforti et al.   NATURAL HAZARDS

An assessment on the use of logistic regression and artificial neural networks with different sampling strategies for the preparation of landslide susceptibility maps

(2008) H.A. Nefeslioglu et al.   ENGINEERING GEOLOGY

Spatial data for landslide susceptibility, hazard, and vulnerability assessment: An overview

(2008) Cees J. van Westen et al.   ENGINEERING GEOLOGY

Guidelines for landslide susceptibility, hazard and risk zoning for land-use planning

(2008) Robin Fell et al.   ENGINEERING GEOLOGY

Landslide susceptibility mapping based on Support Vector Machine: A case study on natural slopes of Hong Kong, China

(2008) X. Yao et al.   GEOMORPHOLOGY

Landslide susceptibility zonation mapping and its validation in part of Garhwal Lesser Himalaya, India, using binary logistic regression analysis and receiver operating characteristic curve method

(2008) John Mathew et al.   Landslides