Predicting susceptibility to landslides under climate change impacts in metropolitan areas of South Korea using machine learning-Reference-Cited by-同舟云学术

Predicting susceptibility to landslides under climate change impacts in metropolitan areas of South Korea using machine learning

Published:2021-01-01 Issue:1 Volume:12 Page:2462-2476
ISSN:1947-5705
Container-title:Geomatics, Natural Hazards and Risk
language:en
Short-container-title:Geomatics, Natural Hazards and Risk

Author:

Park Sang-Jin¹,Lee Dong-kun¹²

Affiliation:

1. Interdisciplinary Program in Landscape Architecture & Integrated Major in Smart City Global Convergence, Seoul National University, Seoul, Republic of Korea

2. College of Agriculture and Life Science, Seoul National University, Seoul, Republic of Korea

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences,General Environmental Science

Link

https://www.tandfonline.com/doi/pdf/10.1080/19475705.2021.1963328

Reference52 articles.

1. A comparison of landslide susceptibility maps produced by logistic regression, multi-criteria decision, and likelihood ratio methods: a case study at İzmir, Turkey

2. From Multi-Risk Evaluation to Resilience Planning: The Case of Central Chilean Coastal Cities

3. New Ensemble Models for Shallow Landslide Susceptibility Modeling in a Semi-Arid Watershed

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