Landslide Susceptibility Mapping: Machine and Ensemble Learning Based on Remote Sensing Big Data

Landslide Susceptibility Prediction Based on Remote Sensing Images and GIS: Comparisons of Supervised and Unsupervised Machine Learning Models

(2020) Zhilu Chang et al.   Remote Sensing

Big Earth Observation Data Integration in Remote Sensing Based on a Distributed Spatial Framework

(2020) Yinyi Cheng et al.   Remote Sensing

Integration of convolutional neural network and conventional machine learning classifiers for landslide susceptibility mapping

(2020) Zhice Fang et al.   COMPUTERS & GEOSCIENCES

GIS-based landslide susceptibility mapping using numerical risk factor bivariate model and its ensemble with linear multivariate regression and boosted regression tree algorithms

(2019) Alireza Arabameri et al.   Journal of Mountain Science

The Influence of Different Knowledge-Driven Methods on Landslide Susceptibility Mapping: A Case Study in the Changbai Mountain Area, Northeast China

(2019) Zhongjun Ma et al.   Entropy

Landslide Susceptibility Mapping Based on Random Forest and Boosted Regression Tree Models, and a Comparison of Their Performance

(2019) Soyoung Park et al.   Applied Sciences-Basel

Development of a Novel Hybrid Intelligence Approach for Landslide Spatial Prediction

(2019) Nguyen et al.   Applied Sciences-Basel

Remote Sensing Big Data Classification with High Performance Distributed Deep Learning

(2019) Rocco Sedona et al.   Remote Sensing

A Novel Ensemble Approach for Landslide Susceptibility Mapping (LSM) in Darjeeling and Kalimpong Districts, West Bengal, India

(2019) Jagabandhu Roy et al.   Remote Sensing

A novel hybrid intelligent model of support vector machines and the MultiBoost ensemble for landslide susceptibility modeling

(2018) Binh Thai Pham et al.   Bulletin of Engineering Geology and the Environment

Groundwater potential mapping using a novel data-mining ensemble model

(2018) Mojtaba Dolat Kordestani et al.   HYDROGEOLOGY JOURNAL

Novel GIS Based Machine Learning Algorithms for Shallow Landslide Susceptibility Mapping

(2018) Ataollah Shirzadi et al.   SENSORS

Identifying the essential flood conditioning factors for flood prone area mapping using machine learning techniques

(2018) Mahyat Shafapour Tehrany et al.   CATENA

A comparative assessment of GIS-based data mining models and a novel ensemble model in groundwater well potential mapping

(2017) Seyed Amir Naghibi et al.   JOURNAL OF HYDROLOGY

A comparison between ten advanced and soft computing models for groundwater qanat potential assessment in Iran using R and GIS

(2017) Seyed Amir Naghibi et al.   THEORETICAL AND APPLIED CLIMATOLOGY

Landslide susceptibility mapping using random forest and boosted tree models in Pyeong-Chang, Korea

(2017) Jeong-Cheol Kim et al.   Geocarto International

Assessment of the effects of training data selection on the landslide susceptibility mapping: a comparison between support vector machine (SVM), logistic regression (LR) and artificial neural networks (ANN)

(2017) Bahareh Kalantar et al.   Geomatics Natural Hazards & Risk

Data Mining Approaches for Landslide Susceptibility Mapping in Umyeonsan, Seoul, South Korea

(2017) Sunmin Lee et al.   Applied Sciences-Basel

Comparison of a logistic regression and Naïve Bayes classifier in landslide susceptibility assessments: The influence of models complexity and training dataset size

(2016) Paraskevas Tsangaratos et al.   CATENA

Valley and channel networks extraction based on local topographic curvature and k -means clustering of contours

(2016) Milad Hooshyar et al.   WATER RESOURCES RESEARCH

A GIS-based comparative study of Dempster-Shafer, logistic regression and artificial neural network models for landslide susceptibility mapping

(2016) Wei Chen et al.   Geocarto International

Evaluation of landslide susceptibility mapping techniques using lidar-derived conditioning factors (Oregon case study)

(2016) Rubini Mahalingam et al.   Geomatics Natural Hazards & Risk

Evaluating machine learning and statistical prediction techniques for landslide susceptibility modeling

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

GIS-based groundwater potential mapping using boosted regression tree, classification and regression tree, and random forest machine learning models in Iran

(2015) Seyed Amir Naghibi et al.   ENVIRONMENTAL MONITORING AND ASSESSMENT

Land cover mapping based on random forest classification of multitemporal spectral and thermal images

(2015) Vahid Eisavi et al.   ENVIRONMENTAL MONITORING AND ASSESSMENT

Landslide susceptibility analysis in central Vietnam based on an incomplete landslide inventory: Comparison of a new method to calculate weighting factors by means of bivariate statistics

(2015) Markus Meinhardt et al.   GEOMORPHOLOGY

Landslide susceptibility assessment at Wadi Jawrah Basin, Jizan region, Saudi Arabia using two bivariate models in GIS

(2015) Ahmed Mohamed Youssef et al.   GEOSCIENCES JOURNAL

Erratum to: Landslide susceptibility mapping using random forest, boosted regression tree, classification and regression tree, and general linear models and comparison of their performance at Wadi Tayyah Basin, Asir Region, Saudi Arabia

(2015) Ahmed Mohamed Youssef et al.   Landslides

A Comparative Assessment Between Three Machine Learning Models and Their Performance Comparison by Bivariate and Multivariate Statistical Methods in Groundwater Potential Mapping

(2015) Seyed Amir Naghibi et al.   WATER RESOURCES MANAGEMENT

Landslide susceptibility mapping using GIS-based statistical models and Remote sensing data in tropical environment

(2015) Himan Shahabi et al.   Scientific Reports

Optimization of Causative Factors for Landslide Susceptibility Evaluation Using Remote Sensing and GIS Data in Parts of Niigata, Japan

(2015) Jie Dou et al.   PLoS One

Earthquake induced landslide susceptibility mapping using an integrated ensemble frequency ratio and logistic regression models in West Sumatera Province, Indonesia

(2014) Zahrul Umar et al.   CATENA

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

An evaluation of SVM using polygon-based random sampling in landslide susceptibility mapping: The Candir catchment area (western Antalya, Turkey)

(2013) B. Taner San   International Journal of Applied Earth Observation and Geoinformation

Determination of Important Topographic Factors for Landslide Mapping Analysis Using MLP Network

(2013) Mutasem Sh. Alkhasawneh et al.   TheScientificWorldJOURNAL

Integrating physical and empirical landslide susceptibility models using generalized additive models

(2011) Jason N. Goetz et al.   GEOMORPHOLOGY

GIS-based spatial prediction of landslide susceptibility using logistic regression model

(2011) Seyedeh Zohreh Mousavi et al.   Geomatics Natural Hazards & Risk

AIC model selection and multimodel inference in behavioral ecology: some background, observations, and comparisons

(2010) Kenneth P. Burnham et al.   BEHAVIORAL ECOLOGY AND SOCIOBIOLOGY

Manifestation of an adaptive neuro-fuzzy model on landslide susceptibility mapping: Klang valley, Malaysia

(2010) Ebru Akcapinar Sezer et al.   EXPERT SYSTEMS WITH APPLICATIONS