Assessment of Building Damage Risk by Natural Disasters in South Korea Using Decision Tree Analysis

The purpose of this study is to identify the relationship between weather variables and buildings damaged in natural disasters. We used four datasets on building damage history and 33 weather datasets from 230 regions in South Korea in a decision tree analysis to evaluate the risk of building damage...

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Main Authors: KeumJi Kim, SeongHwan Yoon
Format: Article
Language:English
Published: MDPI AG 2018-04-01
Series:Sustainability
Subjects:
Online Access:http://www.mdpi.com/2071-1050/10/4/1072
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spelling doaj-ec63c7ae4ff54d38be4f20ac030fe0332020-11-24T23:56:11ZengMDPI AGSustainability2071-10502018-04-01104107210.3390/su10041072su10041072Assessment of Building Damage Risk by Natural Disasters in South Korea Using Decision Tree AnalysisKeumJi Kim0SeongHwan Yoon1Department of Architecture, Pusan National University, Pusan 46241, KoreaDepartment of Architecture, Pusan National University, Pusan 46241, KoreaThe purpose of this study is to identify the relationship between weather variables and buildings damaged in natural disasters. We used four datasets on building damage history and 33 weather datasets from 230 regions in South Korea in a decision tree analysis to evaluate the risk of building damage. We generated the decision tree model to determine the risk of rain, gale, and typhoon (excluding gale with less damage). Using the weight and limit values of the weather variables derived using the decision tree model, the risk of building damage was assessed for 230 regions in South Korea until 2100. The number of regions at risk of rain damage increased by more than 30% on average. Conversely, regions at risk of damage from snowfall decreased by more than 90%. The regions at risk of typhoons decreased by 57.5% on average, while those at high risk of the same increased by up to 62.5% under RCP 8.5. The results of this study are highly fluid since they are based on the uncertainty of future climate change. However, the study is meaningful because it suggests a new method for assessing disaster risk using weather indices.http://www.mdpi.com/2071-1050/10/4/1072building damageclimate change scenariodecision tree analysisnatural disasterrisk assessment process
collection DOAJ
language English
format Article
sources DOAJ
author KeumJi Kim
SeongHwan Yoon
spellingShingle KeumJi Kim
SeongHwan Yoon
Assessment of Building Damage Risk by Natural Disasters in South Korea Using Decision Tree Analysis
Sustainability
building damage
climate change scenario
decision tree analysis
natural disaster
risk assessment process
author_facet KeumJi Kim
SeongHwan Yoon
author_sort KeumJi Kim
title Assessment of Building Damage Risk by Natural Disasters in South Korea Using Decision Tree Analysis
title_short Assessment of Building Damage Risk by Natural Disasters in South Korea Using Decision Tree Analysis
title_full Assessment of Building Damage Risk by Natural Disasters in South Korea Using Decision Tree Analysis
title_fullStr Assessment of Building Damage Risk by Natural Disasters in South Korea Using Decision Tree Analysis
title_full_unstemmed Assessment of Building Damage Risk by Natural Disasters in South Korea Using Decision Tree Analysis
title_sort assessment of building damage risk by natural disasters in south korea using decision tree analysis
publisher MDPI AG
series Sustainability
issn 2071-1050
publishDate 2018-04-01
description The purpose of this study is to identify the relationship between weather variables and buildings damaged in natural disasters. We used four datasets on building damage history and 33 weather datasets from 230 regions in South Korea in a decision tree analysis to evaluate the risk of building damage. We generated the decision tree model to determine the risk of rain, gale, and typhoon (excluding gale with less damage). Using the weight and limit values of the weather variables derived using the decision tree model, the risk of building damage was assessed for 230 regions in South Korea until 2100. The number of regions at risk of rain damage increased by more than 30% on average. Conversely, regions at risk of damage from snowfall decreased by more than 90%. The regions at risk of typhoons decreased by 57.5% on average, while those at high risk of the same increased by up to 62.5% under RCP 8.5. The results of this study are highly fluid since they are based on the uncertainty of future climate change. However, the study is meaningful because it suggests a new method for assessing disaster risk using weather indices.
topic building damage
climate change scenario
decision tree analysis
natural disaster
risk assessment process
url http://www.mdpi.com/2071-1050/10/4/1072
work_keys_str_mv AT keumjikim assessmentofbuildingdamageriskbynaturaldisastersinsouthkoreausingdecisiontreeanalysis
AT seonghwanyoon assessmentofbuildingdamageriskbynaturaldisastersinsouthkoreausingdecisiontreeanalysis
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