Journal of the Korean Institute of Landscape Architecture (한국조경학회지)

The Korean Institute of Landscape Architecture (한국조경학회)
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Testing Non-Stationary Relationship between the Proportion of Green Areas in Watersheds and Water Quality using Geographically Weighted Regression Model

공간지리 가중회귀모형(GWR)을 이용한 유역 녹지비율과 하천수질의 비균질적 관계 검증

  • 이상우 (건국대학교 녹지환경계획학과)
  • Received : 2013.08.20
  • Accepted : 2013.11.21
  • Published : 2013.12.31
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Abstract

This study aims to examine the presence of non-stationary relationship between water quality and land use in watersheds. In investigating the relationships between land use and water quality, most previous studies adopted OLS method which is assumed stationarity. However, this approach is difficult to capture the local variation of the relationships. We used 146 sampling data and land cover data of Korean Ministry of Environment to build conventional regressions and GWR models for BOD, TN and TP. Regression model and GWR models of BOD, TN, TP were compared with $R^2$, AICc and Moran's I. The results of comparisons and descriptive statistics of GWR models strongly indicated the presence of Non-Stationarity between water quality and land use.

본 연구는 낙동강 대권역에서 공간지리 가중회귀모형을 이용하여 녹지지역과 BOD, TN, TP를 포함하는 수질과의 지역적 비균질적 관계를 검증하고자 수행되었다. 대부분 기존의 상관분석 혹은 회귀분석은 OLS (Ordinary Least Square)기법에 기초한 균질적 관계의 분석에 초점을 두어 왔다. 이러한 녹지지역과 수질의 균질적 관계에 기초한 분석은 지역적으로 변화를 고려하지 않는 단점이 있다. 연구대상지는 낙동강 대권역내 146개 지점이며, 수질자료와 토지피복 자료는 환경부 자료를 활용하였다. BOD, TN, TP에 대하여 일반 회귀모형과 모델과 GWR 모델을 추정하여 비교하였다. 비교결과, BOD와 TN의 GWR 모델이 OLS 모델에 비하여 우수한 것으로 나타났다. GWR 모델의 $R^2$와 녹지지역의 계수 값의 기초통계량을 분석한 결과, 지역적으로 큰 변동이 확인되었다. 이러한 결과는 유역 토지이용과 수질과의 관계가 공간적으로 비균절적이라는 것을 입증하여 주었다.

Keywords

References

  1. Brunsdon, C., A. S. Fotheringham and M. E. Charlton(1996) Geographically weighted regression: Amethod for exploring spatial nonstationarity. Geographical Analysis 28(4): 281-298.
  2. Charlton, M., S. Fotheringham and C. Brunsdon(2005) Geographically Weighted Regression, ESRC National Center for Research Methods (NCRM/006).
  3. Choi, Youn-Hee, Yae-Jun Chun and Jin-Hyoung Jon(2012) A study on the physical changes of streams due to urbanization, Proceedings 2012 Korean Association of Landscape Architects Spring Conferences, pp. 211-215.
  4. Foster, S. A. and W. L. Gorr(1986) An adaptive filter for estimating spatially varying parameters: Application to modeling police hours spent in response to calls for service. Management Science 32: 878-889. https://doi.org/10.1287/mnsc.32.7.878
  5. Fotheringham, A. S., C. Brunsdon and M. E. Charlton(2002) Geographically Weighted Regression: The Analysis of Spatially Varying Relationships, Wiley.
  6. Gao, J. and S. Li(2011) Detecting spatially non-stationary and scaledependent relationships between urban landscape fragmentation and related factors using Geographically Weighted Regression. Applied Geography 31: 292-302. https://doi.org/10.1016/j.apgeog.2010.06.003
  7. Goldstein, H.(1987) Multilevel Models in Educational and Social Research. New York: Oxford University Press.
  8. Gorr, W. L. and A. M. Olligschlaeger(1994) Weighted spatial adaptive filtering: Monte Carlo studies and application to illicit drug market modeling. Geographical Analysis 26: 67-87.
  9. Kamarianakis, Y., H. Feidas, G. Kokolatos, N. Chrysoulakis and V. Karatzias(2008) Evaluating remotely sensed rainfall estimates using nonlinear mixed models and geographically weighted regression. Environmental Modelling & Software 23: 1438-1447. https://doi.org/10.1016/j.envsoft.2008.04.007
  10. Korean ministry of Environments, Master plan for Water Environments -Master Plan for Water Quality Management ('06-'15)
  11. Lee, S. W., S. J. Hwang, J. K. Lee, D. I. Jung, Y. J. Park and J. T. Kim(2011) Overview and application of the National Aquatic Ecological Monitoring Program(NAEMP) in Korea. International Journal of Limnology 47: S3-S14. https://doi.org/10.1051/limn/2011016
  12. Lee, S. W., S. J. Hwang, S. B. Lee, H. S. Hwang and H. C. Sung (2009) Landscape ecological approach to the relationships of land use patterns in watersheds to water quality characteristics. Landscape Urban Planning 92: 80-89. https://doi.org/10.1016/j.landurbplan.2009.02.008
  13. Lu, B., M. Charlton and A. S. Fortheringham(2011) Geographically weighted regression using a non-euclidean distance metric with a study on London house price data. Procedia Environmental Sciences 7: 92-97. https://doi.org/10.1016/j.proenv.2011.07.017
  14. Meador, M. R., J. F. Coles and H. Zappia(2005) Fish assemblage responses to urban intensity gradients in contrasting metropolitan areas: Birmingham, Alabama, and Boston, Massachusetts. In: Brown, L. R., R. H. Gray, R. M. Hughes, M. R. Meador(Eds.), Effects of Urbanization on Stream Ecosystems. American Fisheries Society, Bethesda, pp. 409-422.
  15. Mehaffey, M. H.(2005) Linking land cover and water quality in New York City’s water supply watersheds. Environmental Monitoring and Assessment 107: 29-44. https://doi.org/10.1007/s10661-005-2018-5
  16. Park, S. R., H. J. Lee, S. W. Lee, S. J. Hwang, M. S. Byeon, G. J. Joo, K. S. Jeong, D. S. Kong and M. C. Kim(2011) Relationships between land use and multi-dimensional characteristics of streams and rivers at two different scales. Annales de Limnologie - International Journal of Limnology 47: 107-116. https://doi.org/10.1051/limn/2011023
  17. Propastin, P.(2012) Modifying geographically weighted regression for estimating aboveground biomass in tropical rainforests by multispectral remote sensing data. International Journal of Applied Earth Observation and Geoinformation 18: 82-90. https://doi.org/10.1016/j.jag.2011.12.013
  18. Saphores, J.-D. and W. Li(2012) Estimating the value of urban green areas: A hedonic pricing analysis of the single family housing market in Los Angeles, CA. Landscape and Urban Planning 104: 373-387. https://doi.org/10.1016/j.landurbplan.2011.11.012
  19. Szymanowski, M. and M. Kryza(2011) Application of geographically weighted regression for modelling the spatial structure of urban heat island in the city of Wroclaw (SW Poland). Procedia Environmental Sciences 3: 87-92. https://doi.org/10.1016/j.proenv.2011.02.016
  20. Tong, S. andW. Chen(2002) Modeling the relationship between land use and surface water quality. Environmental Management 66: 377-393.
  21. Tu, J. and Z. Xia(2008) Examining spatially varying relationships between land use and water quality using geographically weighted regression I: model design and evaluation. Science of the Total Environment 407: 358-378. https://doi.org/10.1016/j.scitotenv.2008.09.031
  22. Tu, J.(2011) Spatially varying relationships between land use and water quality across an urbanization gradient explored by geographically weighted regression. Applied Geography 31: 376-392. https://doi.org/10.1016/j.apgeog.2010.08.001
  23. Wang, L., J. Lyons, P. Kanehl and R. Gatti(1997) Influences of watershed land use on habitat quality and biotic integrity in Wisconsin streams. Fisheries 22: 6-12.
  24. Weaver, A. L. and G. Garman(1994) Urbanization of a watershed and historical changes in a streamfish. Transactions of the American Fisheries Society 123: 162-172. https://doi.org/10.1577/1548-8659(1994)123<0162:UOAWAH>2.3.CO;2
  25. Zhang, H., J. Zhang, S. Lu, S. Cheng and J. Zhang(2011) Modeling hotel room price with geographically weighted regression. International Journal of Hospitality Management 30: 1036-1043. https://doi.org/10.1016/j.ijhm.2011.03.010
  26. http://www.kma.go.kr/weather/climate/average_30years.jsp