대한토목학회논문집 (KSCE Journal of Civil and Environmental Engineering Research)

  • 제28권6D호
  • /
  • Pages.915-922
  • /
  • 2008
  • /
  • 1015-6348(pISSN)
  • /
  • 2799-9629(eISSN)
대한토목학회 (Korean Society of Civil Engeneers)
권호 표지
DOI QR코드

DOI QR Code

위성원격탐사와 분류 및 회귀트리를 이용한 중랑천 유역의 불투수층 추정

Impervious Surface Estimation of Jungnangcheon Basin Using Satellite Remote Sensing and Classification and Regression Tree

  • 김수영 (연세대학교 사회환경시스템공학부) ;
  • 허준행 (연세대학교 사회환경시스템공학부) ;
  • 허준 (연세대학교 사회환경시스템공학부) ;
  • 김성훈 (연세대학교 사회환경시스템공학부)
  • 투고 : 2008.03.27
  • 심사 : 2008.10.17
  • 발행 : 2008.11.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

불투수층은 자연적인 침투를 허용하지 않는 인위적인 토지피복상태로, 도시화율을 추정하거나 도시의 환경변화 정도를 분석하기 위한 척도로 사용되어 왔다. 수문학적인 관점에서 불투수층은 단기 유출현상에 큰 영향을 끼치는 요소로 급속한 도시화로 인해 불투수층의 영향이 더욱 커짐에 따라 불투수층의 추정에 대한 필요성이 증가하고 있다. 따라서 본 연구에서는 불투수층을 추정하기 위해 중랑천 유역을 대상지역으로 선정하고, $30m{\times}30m$ 공간해상도의 Landsat-7 ETM+ 영상과 $1m{\times}1m$의 고해상도 위성영상을 구축하였으며 tasselled cap 변환과 식생지수(NDVI) 변환을 수행하여 다양한 예측변수를 고려하였다. 수집된 학습자료에 분류 및 회귀트리를 적용하여 불투수층 추정모델을 구성하였고, 이를 지도화하여 중랑천 유역의 불투수층을 나타냈다.

Impervious surface is an important index for the estimation of urbanization and the assessment of environmental change. In addition, impervious surface influences on short-term rainfall-runoff model during rainy season in hydrology. Recently, the necessity of impervious surface estimation is increased because the effect of impervious surface is increased by rapid urbanization. In this study, impervious surface estimation is performed by using remote sensing image such as Landsat-7 ETM+image with $30m{\times}30m$ spatial resolution and satellite image with $1m{\times}1m$ spatial resolution based on Jungnangcheon basin. A tasseled cap transformation and NDVI(normalized difference vegetation index) transformation are applied to Landsat-7 ETM+ image to collect various predict variables. Moreover, the training data sets are collected by overlaying between Landsat-7 ETM+ image and satellite image, and CART(classification and regression tree) is applied to the training data sets. As a result, impervious surface prediction model is consisted and the impervious surface map is generated for Jungnangcheon basin.

키워드

참고문헌

  1. 건설교통부(2003) 중랑천 하천정비기본계획.
  2. 김성훈, 허준, 윤공현, 손홍규(2007) Landsat-7 ETM+영상을 이용한 안성지역의 불투수도 추정. 대한원격탐사학회 논문집, 대한원격탐사학회, 제23권 제6호, pp. 529-536. https://doi.org/10.7780/kjrs.2007.23.6.529
  3. 사공호상(2003) IKONOS 위성영상을 이용한 불투수지표면 분석방법에 관한 실증연구. 한국GIS학회 논문집, 한국GIS학회, 제11권 제4호, pp. 509-518.
  4. 조홍래, 정종철(2005) 분광혼합분석 기법을 이용한 탄천유역 불투수율 평가. 대한원격탐사학회 논문집, 대한원격탐사학회, 제21권 제6호, pp. 457-468. https://doi.org/10.7780/kjrs.2005.21.6.457
  5. Breiman, L., Friedman, J.H., Olshen, R.A., and Stone, C.J. (1984) Classification and regression trees. The Wadsworth Statistics/Probability Series. Wadsworth International group, California, USA.
  6. Herold, N.D., Koeln, G., and Cunnigham, D. (2003) Mapping impervious surfaces and forest canopy using classification and regression tree analysis. ASPRS 2003 Annual Conference Proceedings, Alaska, USA.
  7. Hodgson, M.E., Jenson, J.R., Tullis, J.A., Riordan, K.D., and Archer, C.M. (2003) Synergistic Use of Lidar and Color Aerial Photography for Mapping Urban Parcel Imperviousness. Photogrammetric Engineering & Remote Sensing, Vol. 69, No. 9, pp. 973-980. https://doi.org/10.14358/PERS.69.9.973
  8. Huang, C., Yang, L., Wylie, B.K., and Homer, C.G. (2001) A strategy for estimating tree canopy density using LANDSAT 7 ETM+ and high resolution images over large areas. The Proceedings of the 3rd International Conference on Geospatial Information in Agriculture and Forestry, Colorado, USA.
  9. Huang, C., Wylie, B.K., Yang, L., Homer, C.G., and Zylstra, G. (2002) Derivation of a tasselled cap transformation based on Landsat-7 at satellite reflectance. International Journal of Remote Sensing, Vol. 23, No. 8, pp. 1741-1748. https://doi.org/10.1080/01431160110106113
  10. Huang, C. and Townshend, J.R.G. (2003) A stepwise regression tree for nonlinear approximation : applications to estimating subpixel land cover. International Journal of Remote Sensing, Vol. 24, No. 1, pp. 75-90. https://doi.org/10.1080/01431160305001
  11. Hurd, J.D. and Civeo, D.L. (2004) Temporal characterization of impervious surfaces for the state of connecticut. ASPRS 2004 Annual Conference Proceedings, Colorado, USA.
  12. Lee, S. (2006) Landsat ETM+ sub-pixel annalysis of urban landscape using Fuzzy C-means clustering and differentiated impervious surface classed. ASPRS 2006 Annual Conference Proceedings, Reno, Nevada, USA.
  13. Lewis, R.J. (2000) An Introduction to Classification and Regression Tree (CART) Analysis. The 2000 Annual Meeting of the Society for Academic Emergency Medicine, San Francisco, California.
  14. Lu, D. and Weng, Q. (2006) Use of impervious surface in urban land-use classification. Remote Sensing of Environment, Vol. 102, pp. 146-160. https://doi.org/10.1016/j.rse.2006.02.010
  15. Vikhamar, D. and Kastdalen, L. (2005) Impervious surface mapping in Southern Norway. 31st International Symposium on Remote Sensing of Environment, St. Petersburg, Russia.
  16. Wu, C. and Murray, A.T. (2003) Estimating impervious surface distribution by spectral mixture analysis. Remote Sensing of Environment, Vol. 84, pp. 493-505. https://doi.org/10.1016/S0034-4257(02)00136-0
  17. Yang, L., Huang, C., Homer, C.G., Wylie, B.K., and Coan, M.J. (2003) An approach for mapping large-area impervious surfaces synergistic use of Landsat-7 ETM+ and high spatial resolution imagery. Canadian Journal of Remote Sensing, Vol. 29, No. 2, pp. 230-240. https://doi.org/10.5589/m02-098
  18. Yang, X. and Liu, Z. (2005) Use of satellite-derived landscape imperviousness index to characterize urban spatial growth. Computers, Environment and Urban Systems, Vol. 29, pp. 524-540. https://doi.org/10.1016/j.compenvurbsys.2005.01.005