DOI QR코드

DOI QR Code

A Study on Monitoring the Land Surface Temperature Changes Caused by Constructions of Rainwater Villages Using the Multi-temporal Landsat-8 Satellite Images

다중시기 Landsat-8 위성영상을 활용한 빗물마을 조성 사업에 의한 지표면 온도 변화 모니터링에 관한 연구

  • CHOUNG, Yun-Jae (Geospatial Research Center, Geo C&I Co., Ltd.) ;
  • YU, Ki-Kwang (Geospatial Information Division, Seoul Metropolitan Government) ;
  • LEE, Yong Ik (Geospatial Information Division, Seoul Metropolitan Government)
  • 정윤재 ((주)지오씨엔아이 공간정보기술연구소) ;
  • 유기광 (서울시청 공간정보담당관) ;
  • 이용익 (서울시청 공간정보담당관)
  • Received : 2019.11.28
  • Accepted : 2020.03.06
  • Published : 2020.03.31

Abstract

Monitoring the urban environmental changes caused by the urban regeneration project is necessary for evaluating the effect of the various types of urban regeneration projects that have been carried out in Seoul, South Korea. However, there is few available data and professional expert for evaluating the effect of these urban regeneration projects. This research evaluated the effect of the construction of rainwater village in Jangwi-dong area, constructed through the Seoul urban regeneration project, by utilizing the land surface temperatures derived from the multi-temporal Landsat-8 satellite images through the following steps. In the first step, the land surface temperature images were generated using the multispectral bands of the Landsat-8 satellite images. In the final step, the effect of constructing the rainwater villages was assessed by calculating the seasonal LST statistics for Jangwi-dong area, its neighbor area and entire Seoul area. The experimental results led the following conclusion: the construction of rainwater villages did not have the significant effect on the land surface temperature changes in Jangwi-dong area.

서울시 도시재생 사업에 의한 도시환경 변화 파악은 서울시에서 다양한 방법으로 진행되고 있는 도시재생 사업으로 인한 도시환경 변화 탐지를 위해 매우 중요하다. 그러나 도시재생 사업으로 인한 도시환경 변화를 주기적으로 파악할 수 있는 자료가 절대적으로 부족할 뿐만 아니라 자료를 처리하고 분석할 수 있는 인력 또한 현저히 부족하다. 본 연구에서는 다중시기 Landsat 위성영상을 활용하여 도시재생 사업을 통해 조성된 성북구 장위동 빗물마을 지역의 지표온도 변화를 분석함으로써 서울시 빗물마을 조성에 의해 발생한 도시 환경 변화를 다음 과정을 통하여 파악하였다. 우선, 빗물마을 조성 기간 동안 연구대상 지역에서 획득한 Landsat-8 위성영상의 가시광선 및 적외선 밴드를 활용하여 장위동 지역, 장위동 주변 지역 및 서울시 전체 지역의 시계열 지표온도 지도를 제작하였다. 최종적으로 3개 지역의 시계열 지표온도 변화를 측정함으로써, 빗물마을 조성으로 인한 주변지역의 도시환경 변화를 파악하였다. 본 연구에서 도출된 결과의 분석을 통해 장위동 지역에서 진행된 빗물마을 조성사업으로 인해 장위동 지역의 지표온도에 유의미한 변화가 발생했다고 보기는 힘들다는 결론을 내렸다.

Keywords

References

  1. Choung, Y.J., Y.I. Chung and S.Y. Choi. 2018. Assessment of the Relationship between Air Temperature and TOA Brightness Temperature in Different Seasons Using Landsat-8 TIRS. Journal of the Korean Association of Geographic Information Studies 21(2):68-79 https://doi.org/10.11108/KAGIS.2018.21.2.068
  2. Choung, Y.J., E.J. Lee and M.H. Jo. 2019. A Study on the Evaluation of the Different Thresholds for Detecting Urban Areas Using Remote-Sensing Index Images: A Case Study for Daegu, South Korea. Journal of the Korean Association of Geographic Information Studies 22(1):129-139 https://doi.org/10.11108/KAGIS.2019.22.1.129
  3. Choung, Y.J. and J.M. Kim. 2019. Study of the Relationship between Urban Expansion and PM10 Concentration Using Multi-Temporal Spatial Datasets and the Machine Learning Technique: Case Study for Daegu, South Korea. Applied Sciences 9(6):1098. https://doi.org/10.3390/app9061098
  4. Gao, Z., M. Kii, A. Nonomura and K. Nakamura. 2017. Urban Expansion Using Remote-Sensing Data and a Monocentric Urban Model. Computers, Environment and Urban Systems 77:101152.
  5. Garouani, A.E., D.J. Mulla, S.E. Garouani and J. Knight. 2017. Analysis of Urban Growth and Sprawl from Remote Sensing Data: Case of Fez, Morocco. International Journal of Sustainable Built Environment 6(1):160-169. https://doi.org/10.1016/j.ijsbe.2017.02.003
  6. Guri City. 2019. Urban regeneration. http://www.guri.go.kr/cms/content/view/4672 (Assessed December 30, 2019)
  7. Kim, M.K., S.P. Kim, N.H. Kim and H.G. Sohn. 2014. Urbanization and Urban Heat Island Analysis Using LANDSAT Imagery: Sejong City As a Case Study. Journal of the Korean Society of Civil Engineering 34(3):1033-1041 https://doi.org/10.12652/Ksce.2014.34.3.1033
  8. Lee, K.I., J. Ryu, S.W. Jeon, H.C. Jung and J.Y. Kang, 2017. Analysis of the Effect of Heat Island on the Administrative District Unit in Seoul Using LANDSAT Image. Korean Journal of Remote Sensing 33(5):821-834
  9. Lee, J.S. and M.K. Oh. 2019. Distribution Analysis of Land Surface Temperature about Seoul Using Landsat 8 Satellite Images and AWS Data. Journal of the Korea Academia-Industrial cooperation Society 20(1):434-439 https://doi.org/10.5762/KAIS.2019.20.1.434
  10. Maeil Business News Korea. 2019. https://www.mk.co.kr/news/society/view/2017/04/275557/(Assessed December 30, 2019)
  11. National Institute of Meteorological Sciences (NIMS). 2016. Generation of Land Surface Temperature and Analysis of the Effects in Urban Green Areas Using Landsat-8 Satellite Data. Technical Notes, NIMS, Seogui-po, Korea, 53pp
  12. News Trust. 2019. http://www.newstrust.tv/news/articleView.html?idxno=10947 (Assessed December 30, 2019)
  13. Oh, C.Y., S.Y. Park, H.S. Kim, Y.W. Lee and C.U. Choi. 2010. Comparison of Landcover Map Accuracy Using High Resolution Satellite Imagery. Journal of the Korean Association of Geographic Information Studies 13(1):89-100 https://doi.org/10.11108/KAGIS.2010.13.1.089
  14. Park, M.H. 2001. A Study on the Urban Hear Island Phenomenon Using LANDSAT TM Thermal Infrared Data -In the Case of Seoul-. Journal of the Korean Society of Civil Engineering 21(6D):861-874
  15. Seo, K.H. and K.H. Park. 2017. Analysis of Urban Heat Island Intensity Among Administrative Districts Using GIS and MODIS Imagery. Journal of the Korean Association of Geographic Information Studies 20(2):1-16 https://doi.org/10.11108/kagis.2017.20.2.001
  16. Seoul Metropolitan Government. 2018. Seoul Regeneration Strategic Plan Until 2025. Official Document, Seoul Metropolitan Government, Seoul, Korea, 365pp
  17. The Seoul Institute. 2004. Study on Change Detections in Seoul Using Satellite Imagery. Official Document, The Seoul Institute, Seoul, Korea, 67pp
  18. United States Geological Survey(USGS). 2019. Landsat Missions. https://www.usgs.gov/land-resources/nli/landsat/landsat-8?qt-science_support_page_related_con=0#qt-science_support_page_related_con (Assessed December 30, 2019)