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Geocarto International Volume 38, 2023 - Issue 1

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Research Article

The influence of sampling on landslide susceptibility mapping using artificial neural networks

Samuel GameiroFederal University of Rio Grande do Sul, Porto Alegre, RS, BrazilCorrespondence[email protected]

https://orcid.org/0000-0002-4339-6725 View further author information

Guilherme Garcia de OliveiraFederal University of Rio Grande do Sul, Porto Alegre, RS, Brazil

https://orcid.org/0000-0003-4197-5704 View further author information

Laurindo Antonio GuasselliFederal University of Rio Grande do Sul, Porto Alegre, RS, Brazil

https://orcid.org/0000-0001-8300-846X View further author information

Pages 1-23 | Received 18 Apr 2022, Accepted 28 Oct 2022, Published online: 17 Nov 2022

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https://doi.org/10.1080/10106049.2022.2144475
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Articles from other publishers (5)

Saeid Janizadeh, Sayed M. Bateni, Changhyun Jun, Subodh Chandra Pal, Shahab S. Band, Indrajit Chowdhuri, Asish Saha, John P. Tiefenbacher & Amirhosein Mosavi. (2023) Potential impacts of future climate on the spatio-temporal variability of landslide susceptibility in Iran using machine learning algorithms and CMIP6 climate-change scenarios. Gondwana Research 124, pages 1-17.
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Thanh Trinh, Binh Thanh Luu, Duong Huy Nguyen, Trang Ha Thi Le, Son Van Pham & Nhung VuongThi. (2023) A study of non-landslide samples and weights for mapping landslide susceptibility using regression and clustering methods. Earth Science Informatics 16:4, pages 4009-4034.
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Dingying Yang, Xi Jiang, Alireza Arabameri, M. Santosh & Johnbosco C. Egbueri. (2023) Landslide risk assessment and management using hybrid machine learning‐based empirical models. Geological Journal.
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Md. Sharafat Chowdhury. (2023) A review on landslide susceptibility mapping research in Bangladesh. Heliyon 9:7, pages e17972.
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S. U. Sathya, M. Mahmoodian, C. S. Bandara, N. Naderpajouh & P. B. R. Dissanayake. 2023. ICSBE 2022. ICSBE 2022 519 535 .

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