Journal of the Korean Association of Geographic Information Studies (한국지리정보학회지)

The Korean Association of Geographic Information Studies (한국지리정보학회)
권호 표지
DOI QR코드

DOI QR Code

Development of a Prediction Model for Personal Thermal Sensation on Logistic Regression Considering Urban Spatial Factors

도시공간적 요인을 고려한 로지스틱 회귀분석 기반 체감더위 예측 모형 개발

  • Uk-Je SUNG (Dept. of Landscape Architecture Graduate School, Kyungpook National, University) ;
  • Hyeong-Min PARK (Department of Statistics Graduate School, Kyungpook National, University) ;
  • Jae-Yeon LIM (Dept. of Landscape Architecture Graduate School, Kyungpook National, University) ;
  • Yu-Jin SEO (Department of Statistics Graduate School, Kyungpook National, University) ;
  • Jeong-Min SON (Dept. of Landscape Architecture Graduate School, Kyungpook National, University) ;
  • Jin-Kyu MIN (Urban Forests Division, National Institute of Forest Science) ;
  • Jeong-Hee EUM (Dept. of Landscape Architecture, Kyungpook National University)
  • 성욱제 (경북대학교 조경학과) ;
  • 박형민 (경북대학교 통계학과) ;
  • 임재연 (경북대학교 조경학과) ;
  • 서유진 (경북대학교 통계학과) ;
  • 손정민 (경북대학교 조경학과) ;
  • 민진규 (국립산림과학원 도시숲연구과) ;
  • 엄정희 (경북대학교 산림과학.조경학부 조경학전공)
  • Received : 2024.03.07
  • Accepted : 2024.03.15
  • Published : 2024.03.31
Download PDF
⟨ Previous Next ⟩

Abstract

This study analyzed the impact of urban spatial factors on the thermal environment. The personal thermal sensation was set as the unit of thermal environment to analyze its correlation with environmental factors. To collect data on personal thermal sensation, Living Lab was applied, allowing citizens to record their thermal sensation and measure the temperature. Based on the input points of the collected personal thermal sensation, nearby urban spatial elements were collected to build a dataset for statistical analysis. Logistic regression analysis was conducted to analyze the impact of each factor on personal thermal sensation. The analysis results indicate that the temperature is influenced by the surrounding spatial environment, showing a negative correlation with building height, greenery rate, and road rate, and a positive correlation with sky view factor. Furthermore, the road rate, sky view factor, and greenery rate, in that order, had a strong impact on perceived heat. The results of this study are expected to be utilized as basic data for assessing the thermal environment to prepare local thermal environment measures in response to climate change.

본 연구는 시민들이 직접 체감하는 더위인 체감더위를 열환경 단위로 설정하여 공간적 요인과의 상관관계를 분석하고 체감더위 예측 모형을 개발하였다. 체감더위를 수집하기 위해 리빙랩이라는 시민 참여형 연구방법론을 적용하여 시민들이 직접 체감더위를 기록하고 주변의 온도를 측정하도록 하였다. 수집한 체감더위 정보의 입력지점에 기반하여 주변 도시공간적 요소를 수집하여 통계 분석을 위한 데이터셋을 구축하였다. 구축한 데이터를 활용하여 로지스틱 회귀분석을 수행하였다. 분석 결과, 기온은 주변 공간환경에 영향을 받으며, 건물 높이, 녹지율, 도로율과 음의 상관관계를 가지고, 기온과 천공률과 양의 상관관계를 가진다고 분석되었다. 또한 도로율, 천공률, 녹지율 순으로 체감더위에 강한 영향을 미치는 것으로 나타났다. 본 연구의 결과는 기후변화 대응을 위한 국지적인 열환경 대책을 마련하기 위한 열환경 평가의 기초자료로 활용될 수 있을 것으로 기대된다.

Keywords

Acknowledgement

이 논문은 한국연구재단(NRF-2019R1A2C1011042)의 지원과 한국연구재단(4단계 두뇌한국(BK)21 대학원혁신지원사업)의 지원을 받아 연구되었음.

References

  1. Agresti. 2006. An introduction to categorical data analysis. Willey Publishing.
  2. Bottyan, Z. and J. Unger. 2003. A multiple linear statistical model for estimating the mean maximum urban heat island. Theoretical and applied climatology 75:233-243.
  3. Dimoudi, A. and M. Nikolopoulou. 2003. Vegetation in the urban environment. microclimatic analysis and benefits. Energy and buildings 35(1):69-76.
  4. Georgi, J.N. and D. Dimitriou. 2010. The contribution of urban green spaces to the improvement of environment in cities. Case study of Chania, Greece. Building and environment 45(6):1401-1414.
  5. Ren, Y., Deng, Y.Z., Zuo, S.D., Song, X.D., Liao, Y.L., Xu, C.D. and Z.W. Li. 2016. Quantifying the influences of various ecological factors on land surface temperature of urban forests. Environmental pollution 216:519-529.
  6. Ryu, N.H. and C.S. Lee. 2014. Effects for the thermal comfort index improvement of park woodlands and lawns in summer. Journal of the Korean Institute of Landscape Architecture 42(6):21-30.
  7. Ryu, J.W., Jung, E.H., H. Akira. 2011. A study of evaluation of thermal environment following the alleviation of the limit on number of floors of apartment complexes. Journal of the Korean Housing Association 22(3):93-100.
  8. Kim, B.C., Kang, J.W., Park, C. and H.J. Kim. 2020. Analysis of urban heat island alleviating effect of urban parks and green space in Seoul using deep neural network model. Journal of the Korean Institute of Landscape Architecture 48(4):19-28.
  9. Kim, D.W., Kim, J.K. and E.H. Jung. 2010. An analysis of micro-climate environmental changes followed by establishment of an urban park -Focused on the Junggu in Daegu City. Journal of The Urban Design Institute of Korea 11(2):77-94.
  10. Kim, G.A., Choi, J.M. and K.H. Park. 2016. Analysis of thermal environment in buildings according to color change of roof and applicability of cool roof. Journal of Korean Institute of Architectural Sustainable Environment and Building Systems 10(6):409-415.
  11. Kim, M.K., Kim, S.P., Kim, N.H. and H.G. Sohn. 2014. Urbanization and urban heat island analysis using LANDSAT imagery: Sejong City as a case study. Journal of Civil and Environmental Engineering Research 34(3):1033-1041.
  12. Korea Disease Control and Prevention Agency(KDCA). 2023.
  13. Kolokotroni, M. and R. Giridharan. 2008. Urban heat island intensity in London: An investigation of the impact of physical characteristics on changes in outdoor air temperature during summer. Solarenergy 82(11):986-998.
  14. Joh, H.D. and T.K. Kwon. 2022. Effect of urban park on thermal comfort in summer -An analysis of micromclimate data of Seoul Forest Park-. Journal of the Korean Institute of Landscape Architecture 50(6):30-41.
  15. Jonsson, P. 2004. Vegetation as an urban climate control in the subtropical city of Gaborone, Botswana. International Journal of Climatology; A Journal of the Royal Meteorological Society 24(10):1307-1322.
  16. Lee, S.H., Lee, K.S., Jin W.C. and H.K. Song. 2009. Effect of an urban park on air temperature differences in a central business district area. Landscape and Ecological Engineering 5(2):183-191.
  17. Lee, S.M., Kweon, I. and Y.J. Kim. 2019. A study on the Influence of urban environment on the generation of thermal disease. The Korea Contents Association 19(12):84-92.
  18. Lee, J.A., Jung, D.Y., Chon, J.H., Lee, S.M. and Y.B. Song. 2010. An Evaluation of human thermal comfort and improvement of thermal environment by spatial structure. Journal of the Korean Institute of Landscape Architecture 38(5):12-20.
  19. Lehmann, I., Mathey, J., Rossler, S., Brauer, A. and V. Goldberg. 2014. Urban vegetation structure types as a methodological approach for identifying ecosystem services-Application to the analysis of micro-climatic effects. Ecological indicators 42:58-72.
  20. Min, J.K., Eum, J.H., Sung, U.J. and J.M. Son. 2023. Collecting and mapping information on personal thermal sensation through the living lab program. 11th International Conference on Urban Climate.
  21. Oliveira, S., Andrade, H. and T. Vaz. 2011. The cooling effect of green spaces as a contribution to the mitigation of urban heat: A case study in Lisbon. Building and Environment 46(11):2186-2194.
  22. Park, C., Ha, J. and S. Lee. 2017. Association between three-dimensional built environment and urban air temperature: Seasonal and temporal differences.Sustainability 9(8):1338.
  23. Park, J.H., and G.H. Cho. 2016. Influence of park size on the park cooling effect: Focused on Ilsan new town in Korea. Journal of Korea Planning Association 51(5):247-261.
  24. Park, S.K., Jo, S.M., Hyun, C.J., Kong, H.Y., Kim, S.H. and Y.K. Shin. 2017. Air temperature modification of an urban neighborhood park in summer - Hyowon Park, Suwon-si, Gyeonggi-do, Journal of Environment Science society 26(9):1057-1072.
  25. Santamouris, M. 2015. Regulating the damaged thermostat of the cities-Status, impacts and mitigation challenges.Energy and Buildings 91:43-56.
  26. Sung, U.J., Min, J.K., Jung, H.H., Son, J.M. and J.H. Eum. 2023. Construction of a thermal environment prediction map based on perceived heat using machine learning. Proceedings of 2023 Fall conference of the Korean Association of Geographic Information Studies. pp.204-205.
  27. Yin, C., Yuan, M., Lu, Y., Huang, Y. and Y. Liu. 2018. Effects of urban form on the urban heat island effect based on spatial regression model. Science of the Total Environment 634:696-704.
  28. Yoon, S.H. and I.A. Yeo. 2007. An analysis of the urban structure and the evaluation of thermal environment of a coastal city. Journal of the Architectural Institute of Korea Planning & Design 23(12):285-294.