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Geocarto International Volume 37, 2022 - Issue 18
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Original Articles

Landslide susceptibility mapping using state-of-the-art machine learning ensembles

Binh Thai Phama University of Transport Technology, Hanoi, VietnamCorrespondence[email protected] [email protected]
ORCID Iconhttps://orcid.org/0000-0001-9707-840XView further author information
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Vinh Duy Vub Institute of Marine Environment and Resources, Vietnam Academy of Science and Technology, Hanoi, VietnamView further author information
,
Romulus Costachec Department of Civil Engineering, Transilvania University of Brasov, Brasov, RomaniaCorrespondence[email protected] [email protected]
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,
Tran Van Phongd Institute of Geological Sciences, Vietnam Academy of Sciences and Technology, Hanoi, VietnamView further author information
,
Trinh Quoc Ngoa University of Transport Technology, Hanoi, VietnamView further author information
,
Trung-Hieu Trana University of Transport Technology, Hanoi, VietnamView further author information
,
Huu Duy Nguyene Faculty of Geography, VNU University of Science, Vietnam National University, Hanoi, VietnamView further author information
,
Mahdis Amirif Department of Watershed & Arid Zone Management, Gorgan University of Agricultural Sciences & Natural Resources, Gorgan, IranView further author information
,
Mai Thanh Tand Institute of Geological Sciences, Vietnam Academy of Sciences and Technology, Hanoi, VietnamView further author information
,
Phan Trong Trinhd Institute of Geological Sciences, Vietnam Academy of Sciences and Technology, Hanoi, VietnamView further author information
,
Hiep Van Lea University of Transport Technology, Hanoi, VietnamView further author information
&
Indra Prakashg DDG (R) Geological Survey of India, Gandhinagar, IndiaORCID Iconhttps://orcid.org/0000-0002-4309-0187View further author information
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Pages 5175-5200 | Received 05 Nov 2020, Accepted 17 Mar 2021, Published online: 03 May 2021

Citations (10)

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Mubeen ul Basharat, Junaid Ali Khan, Hazem Ghassan Abdo & Hussein Almohamad. (2023) An integrated approach based landslide susceptibility mapping: case of Muzaffarabad region, Pakistan. Geomatics, Natural Hazards and Risk 14:1.
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Rui Liu, YueKai Ding, Deliang Sun, Haijia Wen, Qingyu Gu, Shuxian Shi & Mingyong Liao. (2023) Insights into spatial differential characteristics of landslide susceptibility from sub-region to whole-region cased by northeast Chongqing, China. Geomatics, Natural Hazards and Risk 14:1.
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Haijia Wen, Jiwei Hu, Jialan Zhang, Xuekun Xiang & Mingyong Liao. (2022) Rockfall susceptibility mapping using XGBoost model by hybrid optimized factor screening and hyperparameter. Geocarto International 37:27, pages 16872-16899.
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Articles from other publishers (7)

Sumon Dey & Swarup Das. (2023) Performance Assessment of Multivariate Statistical and Bagging Ensembles in Landslide Susceptibility Mapping: Case Study of National Highway-10. Performance Assessment of Multivariate Statistical and Bagging Ensembles in Landslide Susceptibility Mapping: Case Study of National Highway-10.
Zakaria Matougui, Lynda Djerbal & Ramdane Bahar. (2023) A comparative study of heterogeneous and homogeneous ensemble approaches for landslide susceptibility assessment in the Djebahia region, Algeria. Environmental Science and Pollution Research.
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Nurwatik Nurwatik, Muhammad Hidayatul Ummah, Agung Budi Cahyono, Mohammad Rohmaneo Darminto & Jung-Hong Hong. (2022) A Comparison Study of Landslide Susceptibility Spatial Modeling Using Machine Learning. ISPRS International Journal of Geo-Information 11:12, pages 602.
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Uzodigwe Emmanuel Nnanwuba, Shengwu Qin, Oluwafemi Adewole Adeyeye, Ndichie Chinemelu Cosmas, Jingyu Yao, Shuangshuang Qiao, Sun Jingbo & Ekene Mathew Egwuonwu. (2022) Prediction of Spatial Likelihood of Shallow Landslide Using GIS-Based Machine Learning in Awgu, Southeast/Nigeria. Sustainability 14:19, pages 12000.
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Moziihrii Ado, Khwairakpam Amitab, Arnab Kumar Maji, Elżbieta Jasińska, Radomir Gono, Zbigniew Leonowicz & Michał Jasiński. (2022) Landslide Susceptibility Mapping Using Machine Learning: A Literature Survey. Remote Sensing 14:13, pages 3029.
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Junpeng Huang, Sixiang Ling, Xiyong Wu & Rui Deng. (2022) GIS-Based Comparative Study of the Bayesian Network, Decision Table, Radial Basis Function Network and Stochastic Gradient Descent for the Spatial Prediction of Landslide Susceptibility. Land 11:3, pages 436.
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Taskin Kavzoglu, Alihan Teke & Elif Ozlem Yilmaz. (2021) Shared Blocks-Based Ensemble Deep Learning for Shallow Landslide Susceptibility Mapping. Remote Sensing 13:23, pages 4776.
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