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

Analysis on the Characteristics of Heat Wave Vulnerable Areas Using Landsat 8 Data and Vulnerability Assessment Analysis

Landsat 8 영상과 취약성 분석을 활용한 폭염재해 취약지역의 특성분석

  • KIM, Ji-Sook (Dept. of Urban Planning and Engineering, Dong-A University) ;
  • KIM, Ho-Yong (Dept. of Urban Planning and Engineering, Dong-A University)
  • 김지숙 (동아대학교 도시계획공학과) ;
  • 김호용 (동아대학교 도시계획공학과)
  • Received : 2020.02.14
  • Accepted : 2020.02.28
  • Published : 2020.03.31
Download PDF
⟨ Previous Next ⟩

Abstract

Cities are highly susceptible to disasters due to concentration of population and infrastructure and intensive land use, and there are various factors that affect vulnerability according to regional characteristics. This study analyzed the vulnerability of the heat wave and the surface temperature extracted from Landsat 8 satellite data. Areas with high surface temperature and with high vulnerability did not match. This study overlaid the results of vulnerability analysis and the land surface temperature(LST) in order to identify causes of vulnerability. The results showed that some areas within high-density commercial and semi-residential areas were the most vulnerable, with climate exposure factors, the ratio of the vulnerable populations and residential defective areas being the main causes. Accordingly, alternatives such as green space and residential environmental improvement could be suggested. Various policies for reducing and adapting to heat wave have been established and implemented. However, it is necessary to examine the regional and spatial characteristics of the city, to accurately diagnose the cause of the heat wave, and to prepare appropriate long-term alternatives accordingly.

도시는 인구 및 기반시설의 집중과 집약적 토지이용으로 인해 재해 취약성이 높으며 이들 지역이 가진 지역적, 공간적 특성에 따라 취약성에 영향을 주는 요인들도 다양하다. 본 연구는 폭염지역의 취약원인을 살펴보기 위한 방법으로 Landsat 8 위성자료에서 추출한 지표온도와 폭염 재해 취약성 분석을 수행하였다. 지표온도가 높은 지역과 재해취약성이 높은 지역이 일치하지는 않았으나 두 분석에서 공통으로 취약한 지역의 특성을 분석하기 위하여 중첩분석을 수행한 결과, 고밀도로 개발된 상업지역과 준주거지역의 비중이 높은 대상지 내 일부 지역이 가장 취약한 것으로 나타났다. 이는 기후노출요인과 취약인구, 주거불량지역 비율이 주요 원인인 것으로 나타났다. 이에 따라 녹지확충과 주거환경정비와 같은 대안들이 제시될 수 있을 것이다. 폭염피해 저감과 적응을 위한 다양한 정책들이 수립되어 시행되고 있으나, 도시 내부의 지역적, 공간적 특성을 살펴보고 폭염 원인의 정확한 진단과 그에 맞는 적절한 대책을 마련하여 향후 그에 맞는 중장기적 대안들을 마련해야 할 필요가 있을 것으로 판단된다.

Keywords

References

  1. Ahn, J.S., Hwang, J.D., Park, M.H.,and Suh, Y.S. 2012. Estimation of urban heat island potential based on land cover type in Busan using Landsat-7 ETM+ and AWS data. Journal of the Korean Association of Geographic Information Studies 15(4):65-77 https://doi.org/10.11108/kagis.2012.15.4.065
  2. 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 53(7):87-107 https://doi.org/10.17208/jkpa.2018.12.53.7.87
  3. Eum, J.H. 2016. Vulnerability assessment to urban thermal environment for spatial planning: a case study of Seoul, Korea. Journal of Korean Institute of Landscape Architecture 44(4):109-120 https://doi.org/10.9715/KILA.2016.44.4.109
  4. Jee, J.B., Kim, B.Y., Zo, I.S., Lee, K.T., and Choi, Y.J. 2016. Retrieval of land surface temperature based on high resolution Landsat 8 satellite data. Korean Journal of Remote Sensing. 32(2):171-183 https://doi.org/10.7780/kjrs.2016.32.2.9
  5. Jee, J.B., Lee, K.T., and Choi, Y.J. 2014. Analysis of land surface temperature from MODIS and Landsat satellites using by AWS temperature in Capital area. Korean Journal of Remote Sensing. 30(2):315-329 https://doi.org/10.7780/kjrs.2014.30.2.13
  6. Jeong, J.J. 2001. Cellular automata modeling for analysis and prediction of urban growth in capital area. Ph.D. Thesis. Univ. of Seoul, Seoul, Korea
  7. Kim, G.H., Y.G. Lee, J.H. Kim, H.W. Choi and B.J. Kim. 2018. Analysis of the Cooling Effects in Urban Green Areas using the Landsat 8 Satellite Data. Korean Journal of Remote Sensing 34(2-1):167-178 https://doi.org/10.7780/KJRS.2018.34.2.1.1
  8. Kim, H.O. and Yeom, J.M. 2012. Effect of the urban land cover types on the surface temperature: Case study of Ilsan new city. Korean Journal of Remote Sensing 28(2):203-214 https://doi.org/10.7780/kjrs.2012.28.2.203
  9. Kim, J.S., Kim, H.Y. and Lee, S.H. 2014. A review on improvements of climate change vulnerability analysis methods: Focusing on sea level rise disasters. Journal of the Korean Association of Geographic Information Studies. 17(1):50-60 https://doi.org/10.11108/kagis.2014.17.1.050
  10. Koo, Y.S., Kim,, J.E.., Kim, J.S. and Lee S.H. 2015. Study on the improvement of adaptation ability by vulnerability analysis of heat wave: the case of Busan Metropolitan city. Journal of the Korean Regional Development Association. 27(5):331-348
  11. Lee, H.J., Lee, K.O., Won, G.M., and Lee, H.W. 2009. Application of the latest land use data for numerical simulation of urban thermal environment in the Daegu. Journal of Korean Society for Atmospheric Environment. 25(3):196-210 https://doi.org/10.5572/KOSAE.2009.25.3.196
  12. Lee, T.K. 2017. A study on improvement of climate change vulnerability index focused on heat wave. Master degree thesis. The graduate school of Sejong university. Seoul. Korea.
  13. Lee, W.J., Kang, J.E. and Kim, Y.K. 2013. The impact of environmental health factors in extreme-heat vulnerability assessment in a metropolitan city. Journal of Environmental Health Science 39(6):492-504
  14. Mattew, M., L. Allen, T. Zelalem, W. Brian and R. Dennis. 2014. Radiometric Calibration Methodology of the Landsat 8 Thermal Infrared Sensor. Remote Sensing 6(9):8803-8821. https://doi.org/10.3390/rs6098803
  15. Nayak, S.G., Shrestha, S., Kinney, P.L., Ross, Z., Sheridan, S.C., Pantea, C.I., Hsu, W.H., Muscatiello, N., and Hwang, S.A. 2018. Development of a heat vulnerability index for New York State. Public Health. 161:127-137. https://doi.org/10.1016/j.puhe.2017.09.006
  16. 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 https://doi.org/10.17208/jkpa.2016.10.51.5.247
  17. Park, K.H., Song, B.G., and Park, J.E. 2016. Analysis on the effects of land cover types and topographic features on heat wave days. Journal of the Korean Association of Geographic Information Studies. 19(4):76-91 https://doi.org/10.11108/kagis.2016.19.4.076
  18. Rinner, C. and Hussain, M. 2011. Toronto's urban heat island: Exploring the relationship between land use and surface temperature. Remote Sensing 3(6):1251-1265. https://doi.org/10.3390/rs3061251
  19. USGS. 2015. Landsat 8(L8) Data Users Handbook. Department of the Interior US Geological Survey, v1. https://www.usgs.gov/land-resources/nli/landsat/landsat-8-data-users-handbook.. (Accessed August 15, 2019)
  20. Yoon, M.H. and Ahn, T.M. 2009. An application of satellite image analysis to visualize the effects of urban green areas on temperature. Journal of the Korean Institute of Landscape Architecture. 37(3):46-53