Assessing and mapping landslide susceptibility using different machine learning methods-Reference-Cited by-同舟云学术

Assessing and mapping landslide susceptibility using different machine learning methods

Published:2020-10-30 Issue: Volume: Page:1-26
ISSN:1010-6049
Container-title:Geocarto International
language:en
Short-container-title:Geocarto International

Author:

Orhan Osman¹^ORCID,Bilgilioglu Suleyman Sefa²^ORCID,Kaya Zehra³^ORCID,Ozcan Adem Kursat³^ORCID,Bilgilioglu Hacer⁴^ORCID

Affiliation:

1. Department of Geomatics, Engineering Faculty, Mersin University, Mersin, Turkey

2. Department of Geomatics, Engineering Faculty, Aksaray University, Aksaray, Turkey

3. Republic of Turkey Ministry of Agriculture and Forestry, General Directorate of Combating Desertification and Erosion, Ankara, Turkey

4. Department of Geology, Engineering Faculty, Aksaray University, Aksaray, Turkey

Publisher

Informa UK Limited

Subject

Water Science and Technology,Geography, Planning and Development

Link

https://www.tandfonline.com/doi/pdf/10.1080/10106049.2020.1837258

Reference120 articles.

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2. An easy-to-use MATLAB program (MamLand) for the assessment of landslide susceptibility using a Mamdani fuzzy algorithm

3. Landslide identification and classification by object-based image analysis and fuzzy logic: An example from the Azdavay region (Kastamonu, Turkey)

4. Aksoy G. 2011. Landslide susceptibility analysis of Arhavi (Artvin) and its environment [master’s thesis]. Trabzon (Turkey): Institute of Science and Technology/Karadeniz Technical University. (in Turkish)

5. Estimation of rainfall-induced landslides using ANN and fuzzy clustering methods: A case study in Saeen Slope, Azerbaijan province, Iran

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