한국환경복원기술학회지 (Journal of the Korean Society of Environmental Restoration Technology)

  • 제23권4호
  • /
  • Pages.13-30
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  • 2020
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  • 1229-3032(pISSN)
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  • 2733-5011(eISSN)
한국환경복원기술학회 (The Korea Society of Environmental Restoration Technology)
권호 표지
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로지스틱 회귀모형을 이용한 환경정책 효과 분석: 울산광역시 녹지변화 분석을 중심으로

An Analysis of Environmental Policy Effect on Green Space Change using Logistic Regression Model : The Case of Ulsan Metropolitan City

  • 이성주 (고려대학교 대학원 환경생태공학과) ;
  • 류지은 (인천연구원 인천기후환경연구센터) ;
  • 전성우 (고려대학교 환경생태공학부)
  • Lee, Sung-Joo (Environmental Science & Ecological Engineering, Graduate School of Korea University) ;
  • Ryu, Ji-Eun (Incheon climate & Environmental research center, the Incheon Institute) ;
  • Jeon, Seong-Woo (Dept. of Environmental Science & Ecological Engineering, Korea University)
  • 투고 : 2020.04.03
  • 심사 : 2020.08.21
  • 발행 : 2020.08.31
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초록

This study aims to analyze the qualitative and quantitative effects of environmental policies in terms of green space management using logistic regression model(LRM). Landsat satellite imageries in 1985, 1992, 2000, 2008, and 2015 are classified using a hybrid-classification method. Based on these classified maps, logistic regression model having a deforestation tendency of the past is built. Binary green space change map is used for the dependent variable and four explanatory variables are used: distance from green space, distance from settlements, elevation, and slope. The green space map of 2008 and 2015 is predicted using the constructed model. The conservation effect of Ulsan's environmental policies is quantified through the numerical comparison of green area between the predicted and real data. Time-series analysis of green space showed that restoration and destruction of green space are highly related to human activities rather than natural land transition. The effect of green space management policy was spatially-explicit and brought a significant increase in green space. Furthermore, as a result of quantitative analysis, Ulsan's environmental policy had effects of conserving and restoring 111.75㎢ and 175.45㎢ respectively for the periods of eight and fifteen years. Among four variables, slope was the most determinant factor that accounts for the destruction of green space in the city. This study presents logistic regression model as a way of evaluating the effect of environmental policies that have been practiced in the city. It has its significance in that it allows us a comprehensive understanding of the effect by considering every direct and indirect effect from other domains, such as air and water, on green space. We conclude discussing practicability of implementing environmental policy in terms of green space management with the focus on a non-statutory plan.

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참고문헌

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