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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Online Access: | http://www.mdpi.com/2071-1050/10/4/1072 |
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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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