The Machine Learning-Based Mapping of Urban Pluvial Flood Susceptibility in Seoul Integrating Flood Conditioning Factors and Drainage-Related Data

The Machine Learning-Based Mapping of Urban Pluvial Flood Susceptibility in Seoul Integrating Flood Conditioning Factors and Drainage-Related Data

In the last two decades, South Korea has seen an increase in extreme rainfall coinciding with the proliferation of impermeable surfaces due to urban development. When underground drainage systems are overwhelmed, pluvial flooding can occur. Therefore, recognizing drainage systems as key flood-condit...

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Bibliographic Details
Main Authors: Julieber T. Bersabe, Byong-Woon Jun
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:ISPRS International Journal of Geo-Information
Subjects:
urban flood susceptibility
drainage-related data
machine learning
random forest
support vector machines
logistic regression
Online Access:https://www.mdpi.com/2220-9964/14/2/57
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