Fuzzy TOPSIS Approach to Flood Vulnerability Assessment in Korea

Kim, Yeong-Kyu; Chung, Eun‐Sung; Lee, Kil-Seong

doi:10.3741/jkwra.2012.45.9.901

Cited by 10 publications

(7 citation statements)

References 10 publications

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“…The membership function A is Step 4 is the normalization of the TFN. To apply a TFN to TOPSIS, the values of each variable must be normalized in relation to each other [21]. The normalized fuzzy matrix R signifies the normalized TFN r i indicates each Si-Gun-Gu area, and j indicates the number of each variable.…”

Section: Methodsmentioning

confidence: 99%

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Assessing the Health Vulnerability Caused by Climate and Air Pollution in Korea Using the Fuzzy TOPSIS

2019

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The effects of climate change and air pollution on health have become major topics of discussion and conducting an assessment on the vulnerabilities of climate change is essential to providing a solution for it. This study assesses human vulnerability to the health effects of climate change and ozone. We classified 27 detailed vulnerability indicators into eight categories and assessed the vulnerability of 249 jurisdictions in South Korea by applying the Fuzzy Technique for Order Preference by Similarity to Ideal Situation method. The results indicated that metropolitan and major urban areas were more vulnerable than other areas. Furthermore, factors such as air pollution, meteorological conditions, a vulnerable environment, the distribution of disease, health/medical capacities, and air pollution control had a significant impact on vulnerability. A validity analysis was on the vulnerability assessment results and the number of new patients diagnosed with diseases associated with the cardiovascular system; the results indicated a 66.9% correlation, signifying a considerably high validity. The proposed method for assessing vulnerabilities in terms of the health effects of air pollution is objective and based on data; thus, it is expected to present a high degree of applicability. The results can also be a critical foundation upon which to establish health policies.

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Section: Methodsmentioning

confidence: 99%

“…Step 5 is the Fuzzy TOPSIS process. The TFN normalized according to the weighted normalized fuzzy decision matrix V i.e., the Fuzzy Positive Ideal Solution (FPIS) and the Fuzzy Negative Ideal Solution (FNIS), are defined as given in Equation 9 [21]:…”

Section: Methodsmentioning

confidence: 99%

Assessing the Health Vulnerability Caused by Climate and Air Pollution in Korea Using the Fuzzy TOPSIS

2019

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“…지 영역으로 주요 인자들을 구분하고, 각 인자들에 대한 가중 치를 고려하여 취약성을 분석하였다 (Kim et al, 2012a). 각 인자들의 가중치를 구하는 방법 또한 여러 가지가 적용되었 는데, 엔트로피 방법 이나, Fuzzy TOPSIS 기법 (Kim et al, 2012b), 다기준 의사결정기법 (Chung et al, 2007 (2)와 같이 취약성을 민감도(Sensitivity)와 적응능력(Adaptation Capacity)의 함수로 정의하였다. …”

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Evaluation of Inherent Flood Vulnerability in Seoul Administrative Districts Using Flood Protection Capacity and Damage Matrix

Kim¹,

Choi²,

Choi³

et al. 2014

Journal of Korean Society of Hazard Mitigation

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Due to the rapid urbanization rate and extreme rainfall as a form of the abnormal climate, the urban flood frequency has been increased. Therefore, it is very important for the policy makers to evaluate the urban flood vulnerability and propose the corresponding flood mitigation policies. Since the interests on the urban flood mitigation is increased, many structural flood measures has been constructed. If a city has many structural flood measures, the city is considered as the flood safe city. In this study, inherent flood vulnerability is proposed using Flood Protection Capacity and Damage(PCD) matrix with the flood damage cost and constructed structural flood mitigation measures. The proposed inherent flood vulnerability method was applied in Seoul. The results are categorized by four areas such as relatively flood safe area, flood risk area, inherent flood vulnerable area, and the area where more structural flood measures are needed. Calculated inherent flood vulnerabilities were compared to the conventional flood vulnerability-resilience indices. The proposed inherent flood vulnerability showed more reasonable results. For example, Songpa and Mapo were considered as the flood safe districts because of its high financial independence rate and many constructed flood mitigation measures. However, their inherent flood vulnerability is relatively high. There results could show the comprehensive aspect on the flood mitigation policies.

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“…이 같은 홍수는 재해 발생으로 인한 직접적인 인명피해와 재산피해 이외에도 지속적으로 사회 를 유지하기 위한 다양한 기능들에 광범위하게 영향을 미친 다. 따라서 최근에는 홍수와 복잡하게 연관되는 사회적, 경 제적, 환경적인 요소들을 종합적으로 고려하는 홍수취약성 평가에 대한 관심이 증가되고 있다 (Messner and Meyer, 2006;Merz et al, 2007;Adger, 2006;Green, 2004;Meyer et al, 2009;Kienberger et al, 2009;Scheuer et al, 2011;Jun et al, 2011;Son et al, 2011;Kim et al, 2012).…”

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“…설문참여자는 델파이 패널(Delphi panel) 즉, 델파이 토론의 참여자가 된다 (Lee, 2006). 델파이 패널 은 델파이 절차가 반복되는 동안 피드백된 이전 회의 조 사결과, 즉 통계적 집단 반응과 소수의견에 대한 보고서 를 참고하여 자신의 판단을 수정 보완할 수 있다 (Richey et al, 1985;Adler and Ziglio, 1996;Angus et al, 2003;Jun et al, 2011;Son et al, 2011;Kim et al, 2012 (Lai et al, 1994;Chu, 2002;Jun et al, 2011). 또한 다속성 관점에서 모든 대안들에 대한 평가결과를 쉽게 계 산해서 나타낼 수 있다 (Kim et al, 1997;Shih et al, 2007;Lee and Chung, 2007;Chung and Lee, 2009 퍼지수 의 α-cut은 다음 Eq.…”

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MCDM Approach for Flood Vulnerability Assessment using TOPSIS Method with α Cut Level Sets

Lee¹,

Chung²,

Jun³

2013

Journal of Korea Water Resources Association

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This study aims to develop a multiple criteria decision making (MCDM) approach for flood vulnerability assessment which considers uncertainty. The flood vulnerability assessment procedure consists of three steps: (1) use the Delphi process to determine the criteria and their corresponding weights-the adopted criteria represent the social, economic, and environmental circumstances related to floods, (2) construct a fuzzy data matrix for the flood vulnerability criteria using fuzzification and standardization, and (3) set priorities based on the number of assessed vulnerabilities. This study uses a modified fuzzy TOPSIS method based on α-level sets which considers various uncertainties related to weight derivation and crisp data aggregation. Further, Spearman's rank correlation analysis is used to compare the rankings obtained using the proposed method with those obtained using fuzzy TOPSIS with fuzzy data, TOPSIS, and WSM methods with crisp data. The fuzzy TOPSIS method based on α-cut level sets is found to have a higher correlation rate than the other methods, and thus, it can reduce the difference of the rankings which uses crisp and fuzzy data. Thus, the proposed flood vulnerability assessment method can effectively support flood management policies.

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Fuzzy TOPSIS Approach to Flood Vulnerability Assessment in Korea

Cited by 10 publications

References 10 publications

Assessing the Health Vulnerability Caused by Climate and Air Pollution in Korea Using the Fuzzy TOPSIS

Assessing the Health Vulnerability Caused by Climate and Air Pollution in Korea Using the Fuzzy TOPSIS

Evaluation of Inherent Flood Vulnerability in Seoul Administrative Districts Using Flood Protection Capacity and Damage Matrix

MCDM Approach for Flood Vulnerability Assessment using TOPSIS Method with α Cut Level Sets

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