An Analysis of Typhoon Damage Pattern Type and Development of Typhoon Damage Forecasting Function

김, 정환; 김, 태균; 이, 보림

doi:10.9798/kosham.2017.17.2.339

Cited by 9 publications

(7 citation statements)

References 8 publications

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“…Figure 4 presents the 230 spatial units of weather data. The weather data used in this study were reproduced from 73 automatic weather stations using objective analysis and interpolation [49] (p. 525). Since climate change scenarios use atmospheric model grid systems of regional climate models, their grid systems, such as Lambert conformal or Mercator projection [50] (p. 519), are unique; however, it is more efficient to use a GIS lattice system of administrative districts in studies related to natural disasters [50] (p. 526).…”

Section: Weathermentioning

confidence: 99%

“…The single disaster index consisted of 26 indices, including precipitation, temperature, gale speed, and snowfall, to predict damage from natural disasters. Korea is particularly vulnerable to typhoons accompanied by heavy flooding and gales [49]. The complex disaster index is based on the precipitation and gale speed on the day of a typhoon and consists of seven indices.…”

Section: Weathermentioning

confidence: 99%

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

Kim

Yoon

2018

Sustainability

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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.

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Section: Weathermentioning

confidence: 99%

Section: Weathermentioning

confidence: 99%

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

Kim

Yoon

2018

Sustainability

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“…Korea is particular vulnerable to typhoons accompanied by heavy flooding and gales [44]. The complex disaster index is based on the precipitation and gale speed on the day of the typhoon, and consists of seven indices.…”

Section: Case Study Areamentioning

confidence: 99%

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

Kim¹,

Yoon²

2018

Preprint

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Changes in extreme weather patterns are expected under climate change. In this study, a risk assessment was conducted using 4 building damage history datasets and 33 weather datasets (precipitation, wind speed, snow, and temperature) from 230 regions in South Korea to quantitatively analyze and predict building damage caused by potential future natural disasters. Decision tree analysis was used to evaluate building damage risk in 230 regions. The decision tree model to determine the risk of flood, gale, and typhoon was generated, which excluded gales, with less damage. The weight (variable importance) and limit value (damage limit) of the weather variables ware derived using the decision tree model. Using these two factors, we assessed the building damage risk in 230 regions in South Korea until 2100. The number of regions at risk of flood damage increased by more than 30% in average. Conversely, regions at risk of snowfall damage decreased by more than 90%. The regions at risk of typhoons decreased by 57.5% on average, and the number of regions at high risk of typhoon damage increased by up to 62.5% in RCP 8.5. These results can be used as objective data to minimize future building damage throughout South Korea, representing the first step towards sustainable development in the region with respect to disaster response.

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“…풍수해 피해예측을 위한 연구는 손실⋅손상함수를 구하여 피해를 예측하는 방법 (Kim, Kim, Lee, and Chung, 2014;Kim, Kim, Lee, and Park, 2014;Lee et al, 2017)과 재해통계를 이용하여 (Choi, Bak, et al, 2016;Song et al, 2016;Choo, Kwon, et al, 2017;Choo, Yun, et al, 2017;Kim et al, 2017; Seo, 2013, Shim andKim, 2012)를 이용한 하거나, 수문기상인자와 하천특성을 관계를 이용한 피해액 산정 방법 (Kim, Lee, et al, 2016), 수문기상인자 와 피해액 관계를 직접 유도 (Choi, Bak, et al, 2016;Kim, Choi, et al, 2016) 하였다. 태풍, 호우 이외에도 강풍에 의한 피해 (Song et al, 2016), 대설에 의한 피해 Oh and Chung, 2017), 풍랑에 의한 피해 (Ko et al, 2006;Choo, Kwon et al, 2017;Choo, Yun, et al, 2017) 등 다른 자연재해 유형에 대한 연구도 이루어졌다.…”

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“…수문기상학적 인자, 사회경제적 인자, 유역특성 인자와 피해액 관계는 추정하는 통계학적 방법으로는 비선형 단순 회귀분석을 이용하는 경우가 대부분을 차지하며 (Kim, Kim, Lee, and Chung, 2014;Song et al, 2016;Choo, Kwon, et al, 2017;Choo, Yun, et al, 2017;Kim et al, 2017;Lee et al, 2017;Oh and Chung, 2017), Choi and Seo (2013)…”

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Development of Typhoon Damage Prediction Function using Tukey's Ladder of Power Transformation

Kim¹,

Kim²,

Lee³

2018

J. Korean Soc. Hazard Mitig

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In this study, we use multiple linear regression to develop a function for predicting damage caused by typhoons. The number of explanatory independent variables constituting the damage prediction function is large and varied because typhoon damage is attributed to a combination of factors such as heavy rain, strong wind, and waves. However, existing data of typhoon damage are insufficient for developing a damage prediction function. To resolve this problem, a model for prediction power only was developed, and the leave-one-out-cross-validation (LOOCV)-forward selection method was applied to select the variables. In addition, the power transformation of Tukey's Ladder of Powers was adopted to create linearity in the dependent and independent variables. The typhoon damage prediction function was developed for 22 districts with more than 16 datasets. The transformation factor λ, representing these 22 districts, was shown to vary according to the regional characteristics of each city and district. The best results occurred when λ = 0.2 and λ = 0.3 for the normalized root-mean-square error (NRMSE) and coefficient of determination ( ) standards, respectively.

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An Analysis of Typhoon Damage Pattern Type and Development of Typhoon Damage Forecasting Function

Cited by 9 publications

References 8 publications

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

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

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

Development of Typhoon Damage Prediction Function using Tukey's Ladder of Power Transformation

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An Analysis of Typhoon Damage Pattern Type and Development of Typhoon Damage Forecasting Function

Cited by 9 publications

References 8 publications

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

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

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

Development of Typhoon Damage Prediction Function using Tukey&apos;s Ladder of Power Transformation

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Product

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Development of Typhoon Damage Prediction Function using Tukey's Ladder of Power Transformation