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A Study on Identification of the Heat Vulnerability Area Considering Spatial Autocorrelation - Case Study in Daegu

공간적 자기상관성을 고려한 폭염취약지역 도출에 관한 연구 - 대구광역시를 중심으로

  • Seong, Ji Hoon (Dept. of Spatial Information, Kyungpook National University) ;
  • Lee, Ki Rim (Dept. of Spatial Information, Kyungpook National University) ;
  • Kwon, Yong Seok (Daegu Gyeongbuk Development Institute) ;
  • Han, You Kyung (School of Convergence & Fusion System Engineering, Kyungpook National University) ;
  • Lee, Won Hee (School of Convergence & Fusion System Engineering, Kyungpook National University)
  • Received : 2020.06.08
  • Accepted : 2020.08.23
  • Published : 2020.08.31

Abstract

The IPCC (Intergovernmental Panel on Climate Change) recommended the importance of preventive measures against extreme weather, and heat waves are one of the main themes for establishing preventive measures. In this study, we tried to analyze the heat vulnerable areas by considering not only spatial characteristics but also social characteristics. Energy consumption, popu lation density, normalized difference vegetation index, waterfront distance, solar radiation, and road distribution were examined as variables. Then, by selecting a suitable model, SLM (Spatial Lag Model), available variables were extracted. Then, based on the Fuzzy theory, the degree of vulnerability to heat waves was analyzed for each variable, and six variables were superimposed to finally derive the heat vulnerable area. The study site was selected as the Daegu area where the effects of the heat wave were high. In the case of vulnerable areas, it was confirmed that the existing urban areas are mainly distributed in Seogu, Namgu, and Dalseogu of Daegu, which are less affected by waterside and vegetation. It was confirmed that both spatial and social characteristics should be considered in policy support for reducing heat waves in Daegu.

IPCC는 기상이변의 예방 대책의 중요성을 권고하였으며 폭염은 주요 예방대책수립 주제 중 하나이다. 일반적으로 예방대책수립을 위한 기존 연구는 지형적 특성과 사회적 특성을 따로 구분하여 폭염취약지역을 도출하였으나 본 연구에서는 공간, 지형적 특성뿐만 아니라 사회적 특성을 함께 고려하여 폭염취약지역을 분석하고자 하였다. 에너지 사용량, 인구밀도, 정규식생지수, 수변이격거리, 태양복사량, 도로분포를 변수로 하여 점검하고, 여러 회귀모형 중 가장 적합한 모형인 Spatial Lag Model을 선택하여 사용가능한 변수를 추출하였다. 그리고 Fuzzy 이론에 기초하여 각 변수에 대한 폭염 취약정도를 분석하고, 6개의 변수를 중첩분석하여 최종적으로 폭염취약지역을 도출하였다. 연구 대상지는 폭염의 영향이 큰 대구광역시를 선정하였으며, 취약지역의 경우 기존 도심지이며 수변 및 식생에 영향을 적게 받은 대구 서구, 남구, 달서구에 주로 분포되어있음을 확인하였다. 이를 통해 대구광역시의 폭염 저감을 위한 정책적 지원에 있어 공간적, 사회적 특성을 모두 고려해야 함을 확인하였다.

Keywords

References

  1. Ahn, J.S. and Kim, H.D. (2006), On the seasonal variation of urban heat island intensity according to meteorological condition in Daegu, J. Environ. Science, Vol. 15, No. 6, pp. 527-532. (in Korean with English abstract)
  2. Anselin, L. (1995), SpaceStat Version 1.80 User's Guide, Regional Research Institute, West Virginia University.
  3. Choi, Y.S., Kim, J.W. and Lim. U. (2018), An analysis on the spatial patterns of heat wave vulnerable areas and adaptive capacity vulnerable areas in Seoul, Journal of Korea Planning Association, Vol. 53, NO. 7, pp. 87-107. (in Korean with English abstract) https://doi.org/10.17208/jkpa.2018.12.53.7.87
  4. Cho, H.M., Ha, J.H. and Lee, S.G. (2019), Exploring physical environments, demographic and socioeconomic characteristics of urban heat island effect areas in Seoul, Korea, Journal of the Korean Regional Science Association, Vol. 35, No. 4, pp. 61-73. (in Korean with English abstract) https://doi.org/10.22669/KRSA.2019.35.4.061
  5. Giridharan, R., Ganesan, S., and Lau, S. S. Y. (2004), Daytime urban heat island effect in high-rise and highdensity residential developments in Hong Kong, Energy and Buildings, Vol. 36, No.6, pp. 525-534. https://doi.org/10.1016/j.enbuild.2003.12.016
  6. Kim, E.Y., Jeon, S.W., Lee, J.W., Park, Y.H. and Lee, D.K. (2012), Local adaptation plan to climate change impact in Seoul: focused on heat wave effects, Journal of Environmental Impact Assessment, Vol. 21, No. 1, pp. 71-80. (in Korean with English abstract) https://doi.org/10.14249/EIA.2012.21.1.071
  7. Kim, J.H. and Kim, H.D. (2017), Spatial distribution of air temperature during an extreme heat period in Daegu metropolitan area in 2016, Journal of Environmental Science International, Vol. 26, No. 9, pp. 1023-1029. (in Korean with English abstract) https://doi.org/10.5322/JESI.2017.26.9.1023
  8. Kim, J.S., Lee, D.K., Sung, S.Y., Jeong, S.G. and Park, J.H. (2015), Study of vulnerable district characteristics on urban heat island according to land use using normalized index - focused on Daegu Metropolitan City residential district -, Journal of Korea Planning Association, Vol. 50, No. 5, pp. 59-72. (in Korean with English abstract) https://doi.org/10.17208/jkpa.2015.08.50.5.59
  9. Kim, K.K. (2003), Detecting spatial autocorrelation and using spatial regression, Korean Journal of Policy Analysis and Evaluation, Vol. 13, No. 1, pp. 273-294.(in Korean)
  10. Korea Meteorological Administration. (2018), Newsletter Abnormal Climate Monitoring, No. 11-1360000-000072-08, Korea Meteorological Administration, Seoul, pp. 1-2
  11. Kwon, Y.S. (2015), Consideration for a Environment-Friendly City by Reducing the Urban Heat Effect, ISBN 978-89-8288-482-5, Daegu Gyeongbuk Development Institute Daegu, pp. 1-122.
  12. Kwon, Y.S. (2018), Estimation and countermeasure of the heat wave cause of Daegu Metropolitan basin from the urban structural dimension, The Korea Spatial Planning Review, pp. 23-35. (in Korean with English abstract)
  13. Kwon, Y.S., Jeong, K.W. and Choi, Y.J. (2017), Strategy Against Heat Wave in Urban Area of Metropolitan Region of Daegu, Report 2017-25, ISBN 978-89-8288-579-2 Daegu Gyeongbuk Development Institute, Daegu, pp. 1-128.
  14. Lee, G.G. and Cha, J.W. (2019), A study on identification of the heat vulnerability area - Case study in Chungcheongnamdo -, Journal Of The Korean Society Of Rural Planning, Vol. 25, No. 1, pp. 67-74. (in Korean with English abstract)
  15. Lee, D.G., Byon, J.Y., Choi, Y.J. and Kim, K.R. (2010), Relationship between summer heat stress(perceived temperature) and daily excess mortality in Seoul during 1991-2005, Journal of Korean Society for Atmospheric Environment, Vol. 26, No. 3, pp. 253-264. (in Korean with English abstract) https://doi.org/10.5572/KOSAE.2010.26.3.253
  16. Lim, S.H. and Cho, G.S. (1999), The application of fuzzy spatial overlay method to the site selection using GSIS, Korea Society of Surveying, Geodesy, Photogrammetry, and Cartography, Vol. 17, No. 2, pp. 177-187. (in Korean with English abstract)
  17. Parry, M., Canziani, O., Palutikof, J., Linden, P and Hanson, C. (2007), Contribution of Working Group II to the Fifth Assessment Report of The Intergovernmental Panel on Climate Change, ISBN 978-0521-70597-4, Climate change, New York, pp. 1-976.
  18. Robitu, M., Musy, M., Inard, C., and Groleau, D. (2006), Modeling the influence of vegetation and water pond on urban microclimate, Solar Energy, Vol. 80, No. 4, pp. 435-447. https://doi.org/10.1016/j.solener.2005.06.015
  19. Yun, S.G., Choi, B.S. and Jeon, E.C. (2013), A study on vulnerability assessment to climate change in Siheung-si, Journal of Climate Change Research, Vol. 4, No. 1, pp. 1-10. (in Korean with English abstract)