Consideration of spatial heterogeneity in landslide susceptibility mapping using geographical random forest model

Worldwide Research Trends in Landslide Science

(2021) Paúl Carrión-Mero et al.   International Journal of Environmental Research and Public Health

Exploring spatial non-stationarity in the relationships between landslide susceptibility and conditioning factors: a local modeling approach using geographically weighted regression

(2020) Christos Chalkias et al.   Bulletin of Engineering Geology and the Environment

Geographically neural network weighted regression for the accurate estimation of spatial non-stationarity

(2020) Zhenhong Du et al.   INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE

Assessment of landslide susceptibility at a local spatial scale applying the multi-criteria analysis and GIS: a case study from Slovakia

(2020) Jana Vojteková et al.   Geomatics Natural Hazards & Risk

A hybrid model considering spatial heterogeneity for landslide susceptibility mapping in Zhejiang Province, China

(2020) Yumiao Wang et al.   CATENA

Comparisons of heuristic, general statistical and machine learning models for landslide susceptibility prediction and mapping

(2020) Faming Huang et al.   CATENA

Machine learning methods for landslide susceptibility studies: A comparative overview of algorithm performance

(2020) Abdelaziz Merghadi et al.   EARTH-SCIENCE REVIEWS

A random forest model of landslide susceptibility mapping based on hyperparameter optimization using Bayes algorithm

(2020) Deliang Sun et al.   GEOMORPHOLOGY

Landslide Susceptibility Mapping Using Machine Learning Algorithms and Remote Sensing Data in a Tropical Environment

(2020) Viet-Ha Nhu et al.   International Journal of Environmental Research and Public Health

Improving Spatial Agreement in Machine Learning-Based Landslide Susceptibility Mapping

(2020) Mohammed Sarfaraz Gani Adnan et al.   Remote Sensing

GIS-Based Landslide Susceptibility Modeling: A Comparison between Fuzzy Multi-Criteria and Machine Learning Algorithms

(2020) Sk Ajim Ali et al.   Geoscience Frontiers

GIS-based evaluation of landslide susceptibility using a novel hybrid computational intelligence model on different mapping units

(2020) Ting-yu Zhang et al.   Journal of Mountain Science

Landslide susceptibility mapping in three Upazilas of Rangamati hill district Bangladesh: application and comparison of GIS-based machine learning methods

(2020) Yasin Wahid Rabby et al.   Geocarto International

Landslide-susceptibility mapping in Gangwon-do, South Korea, using logistic regression and decision tree models

(2019) Prima Riza Kadavi et al.   Environmental Earth Sciences

Geographical Random Forests: A Spatial Extension of the Random Forest Algorithm to Address Spatial Heterogeneity in Remote Sensing and Population Modelling

(2019) Stefanos Georganos et al.   Geocarto International

Spatial prediction of landslide susceptibility in Taleghan basin, Iran

(2019) Maryam Mokhtari et al.   STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT

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

Landslide susceptibility hazard map in southwest Sweden using artificial neural network

(2019) Abbas Abbaszadeh Shahri et al.   CATENA

Spatial prediction of landslide susceptibility using data mining-based kernel logistic regression, naive Bayes and RBFNetwork models for the Long County area (China)

(2018) Wei Chen et al.   Bulletin of Engineering Geology and the Environment

Review on landslide susceptibility mapping using support vector machines

(2018) Yu Huang et al.   CATENA

A review of statistically-based landslide susceptibility models

(2018) Paola Reichenbach et al.   EARTH-SCIENCE REVIEWS

Is the ROC curve a reliable tool to compare the validity of landslide susceptibility maps?

(2018) V. Vakhshoori et al.   Geomatics Natural Hazards & Risk

A comparative analysis of statistical landslide susceptibility mapping in the southeast region of Minas Gerais state, Brazil

(2018) Cesar Falcão Barella et al.   Bulletin of Engineering Geology and the Environment

Landslide Susceptibility Mapping and Comparison Using Decision Tree Models: A Case Study of Jumunjin Area, Korea

(2018) Sung-Jae Park et al.   Remote Sensing

Random forest as a generic framework for predictive modeling of spatial and spatio-temporal variables

(2018) Tomislav Hengl et al.   PeerJ

Comparison of expert, deterministic and Machine Learning approach for landslide susceptibility assessment in Ljubovija Municipality, Serbia

(2017) Jelka Krušić et al.   Geofizika

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

(2017) Deepak Kumar et al.   GEOMORPHOLOGY

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

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

Spatial prediction of rotational landslide using geographically weighted regression, logistic regression, and support vector machine models in Xing Guo area (China)

(2017) Haoyuan Hong et al.   Geomatics Natural Hazards & Risk

Different landslide sampling strategies in a grid-based bi-variate statistical susceptibility model

(2016) Haydar Y. Hussin et al.   GEOMORPHOLOGY

Rotation forest fuzzy rule-based classifier ensemble for spatial prediction of landslides using GIS

(2016) Binh Thai Pham et al.   NATURAL HAZARDS

Landslide susceptibility mapping using a modified decision tree classifier in the Xanthi Perfection, Greece

(2015) Paraskevas Tsangaratos et al.   Landslides

Spatial prediction models for shallow landslide hazards: a comparative assessment of the efficacy of support vector machines, artificial neural networks, kernel logistic regression, and logistic model tree

(2015) Dieu Tien Bui et al.   Landslides

An uncertainty and sensitivity analysis approach for GIS-based multicriteria landslide susceptibility mapping

(2014) Bakhtiar Feizizadeh et al.   INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE

Focusing on the spatial non-stationarity of landslide predisposing factors in northern Iceland

(2014) Thierry Feuillet et al.   PROGRESS IN PHYSICAL GEOGRAPHY

Landslide inventory maps: New tools for an old problem

(2012) Fausto Guzzetti et al.   EARTH-SCIENCE REVIEWS

Global patterns of loss of life from landslides

(2012) David Petley   GEOLOGY

Spatial agreement of predicted patterns in landslide susceptibility maps

(2010) S. Sterlacchini et al.   GEOMORPHOLOGY

Improvement of statistical landslide susceptibility mapping by using spatial and global regression methods in the case of More and Romsdal (Norway)

(2010) Arzu Erener et al.   Landslides

Optimal landslide susceptibility zonation based on multiple forecasts

(2009) Mauro Rossi et al.   GEOMORPHOLOGY

Probabilistic description of topographic slope and aspect

(2009) G. Vico et al.   JOURNAL OF GEOPHYSICAL RESEARCH

An approach to computing topographic wetness index based on maximum downslope gradient

(2009) Cheng-Zhi Qin et al.   PRECISION AGRICULTURE