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Geocarto International Volume 37, 2022 - Issue 25
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Research Articles

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

Renata Pacheco Quevedoa Earth Observation and Geoinformatics Division, National Institute for Space Research (INPE), São Paulo, BrazilORCID Iconhttps://orcid.org/0000-0002-7528-9166View further author information
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Daniel Andrade Maciela Earth Observation and Geoinformatics Division, National Institute for Space Research (INPE), São Paulo, BrazilORCID Iconhttps://orcid.org/0000-0003-4543-5908View further author information
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Tatiana Dias Tardelli Ueharaa Earth Observation and Geoinformatics Division, National Institute for Space Research (INPE), São Paulo, BrazilORCID Iconhttps://orcid.org/0000-0003-1861-8848View further author information
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Matej Vojtekb Department of Geography and Regional Development, Faculty of Natural Sciences, Constantine the Philosopher University in Nitra, Nitra, SlovakiaORCID Iconhttps://orcid.org/0000-0001-9369-3173View further author information
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Camilo Daleles Rennóa Earth Observation and Geoinformatics Division, National Institute for Space Research (INPE), São Paulo, BrazilORCID Iconhttps://orcid.org/0000-0001-9920-4473View further author information
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Biswajeet Pradhanc Centre for Advanced Modelling and Geospatial Information Systems, Faculty of Engineering and IT, University of Technology Sydney, Ultimo, NSW, Australia;d Department of Energy and Mineral Resources Engineering, Sejong University, Seoul, South Korea;e Center of Excellence for Climate Change Research, King Abdulaziz University, Jeddah, Saudi Arabia;f Earth Observation Center, Institute of Climate Change, Universiti Kebangsaan Malaysia, Bangi, MalaysiaORCID Iconhttps://orcid.org/0000-0001-9863-2054View further author information
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Jana Vojtekováb Department of Geography and Regional Development, Faculty of Natural Sciences, Constantine the Philosopher University in Nitra, Nitra, SlovakiaORCID Iconhttps://orcid.org/0000-0002-8904-9673View further author information
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Quoc Bao Phamg Institute of Applied Technology, Thu Dau Mot University, Thu Dau Mot City, Vietnam;h Faculty of Natural Sciences, Institute of Earth Sciences, University of Silesia in Katowice, Sosnowiec, PolandCorrespondence[email protected] [email protected]
ORCID Iconhttps://orcid.org/0000-0002-0468-5962View further author information
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Pages 8190-8213 | Received 23 May 2021, Accepted 15 Oct 2021, Published online: 25 Nov 2021

Citations (11)

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Read on this site (2)

Xinzhi Zhou, Haijia Wen, Ziwei Li, Hui Zhang & Wengang Zhang. (2022) An interpretable model for the susceptibility of rainfall-induced shallow landslides based on SHAP and XGBoost. Geocarto International 37:26, pages 13419-13450.
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Nawaz Ikram, Muhammad Basharat, Asghar Ali, Nadeem Ahmad Usmani, Syed Ahsan Hussain Gardezi, Mian Luqman Hussain & Muhammad Tayyib Riaz. (2022) Comparison of landslide susceptibility models and their robustness analysis: a case study from the NW Himalayas, Pakistan. Geocarto International 37:25, pages 9204-9241.
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Articles from other publishers (9)

Wengang Zhang, Yuwei He, Luqi Wang, Songlin Liu & Xuanyu Meng. (2023) Landslide Susceptibility mapping using random forest and extreme gradient boosting: A case study of Fengjie, Chongqing. Geological Journal 58:6, pages 2372-2387.
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Renata Pacheco Quevedo, Andrés Velastegui-Montoya, Néstor Montalván-Burbano, Fernando Morante-Carballo, Oliver Korup & Camilo Daleles Rennó. (2023) Land use and land cover as a conditioning factor in landslide susceptibility: a literature review. Landslides 20:5, pages 967-982.
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Yangsong Gu, Diyi Liu, Ramin Arvin, Asad J. Khattak & Lee D. Han. (2023) Predicting intersection crash frequency using connected vehicle data: A framework for geographical random forest. Accident Analysis & Prevention 179, pages 106880.
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Sima Pourhashemi, Mohammad Ali Zangane Asadi, Mahdi Boroughani & Hossein Azadi. (2022) Mapping of dust source susceptibility by remote sensing and machine learning techniques (case study: Iran-Iraq border). Environmental Science and Pollution Research 30:10, pages 27965-27979.
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Bohao Li, Kai Liu, Ming Wang, Qian He, Ziyu Jiang, Weihua Zhu & Ningning Qiao. (2022) Global Dynamic Rainfall-Induced Landslide Susceptibility Mapping Using Machine Learning. Remote Sensing 14:22, pages 5795.
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Hicham Cherifi, Abdel-Ali Chaouni, Imad Raini & Abdelaziz Htitiou. (2022) Landslide susceptibility assessment along the Expressway Taza-El Hoceima, North-East Morocco, using machine learning algorithm. Arabian Journal of Geosciences 15:22.
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Stefanos Georganos & Stamatis Kalogirou. (2022) A Forest of Forests: A Spatially Weighted and Computationally Efficient Formulation of Geographical Random Forests. ISPRS International Journal of Geo-Information 11:9, pages 471.
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Junying Cheng, Xiaoai Dai, Zekun Wang, Jingzhong Li, Ge Qu, Weile Li, Jinxing She & Youlin Wang. (2022) Landslide Susceptibility Assessment Model Construction Using Typical Machine Learning for the Three Gorges Reservoir Area in China. Remote Sensing 14:9, pages 2257.
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Tingyu Zhang, Renata Pacheco Quevedo, Huanyuan Wang, Quan Fu, Dan Luo, Tao Wang, Guilherme Garcia de Oliveira, Laurindo Antonio Guasselli & Camilo Daleles Renno. (2022) Improved tree-based machine learning algorithms combining with bagging strategy for landslide susceptibility modeling. Arabian Journal of Geosciences 15:2.
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