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Driving Forces in Archetypical Land-Use Changes in a Mountainous Watershed in East Asia

Author

Listed:
  • Ilkwon Kim

    (Professorship of Ecological Services (PES), Faculty of Biology, Chemistry and Geosciences, BayCEER, University of Bayreuth, Bayreuth 95440, Germany)

  • Quang Bao Le

    (Natural and Social Science Interface (NSSI), Institute for Environmental Decisions (IED), ETH Zurich, 8092 Zurich, Switzerland)

  • Soo Jin Park

    (Department of Geography, Seoul National University, Shilim-Dong, Kwanak-Gu, Seoul 151-742, Korea)

  • John Tenhunen

    (Department of Plant Ecology, University of Bayreuth, Bayreuth 95440, Germany)

  • Thomas Koellner

    (Professorship of Ecological Services (PES), Faculty of Biology, Chemistry and Geosciences, BayCEER, University of Bayreuth, Bayreuth 95440, Germany)

Abstract

Identifying patterns and drivers of regional land use changes is crucial for supporting land management and planning. Doing so for mountain ecosystems in East Asia, such as the So-yang River Basin in South Korea, has until now been a challenge because of extreme social and ecological complexities. Applying the techniques of geographic information systems (GIS) and statistical modeling via multinomial logistic regression (MNL), we attempted to examine various hypothesized drivers of land use changes, over the period 1980 to 2000. The hypothesized drivers included variables of topography, accessibility, spatial zoning policies and neighboring land use. Before the inferential statistic analyses, we identified the optimal neighborhood extents for each land use type. The two archetypical sub-periods, i.e. , 1980–1990 with agricultural expansions and 1990–2000 with reforestation, have similar causal drivers, such as topographic factors, which are related to characteristics of mountainous areas, neighborhood land use, and spatial zoning policies, of land use changes. Since the statistical models robustly capture the mutual effects of biophysical heterogeneity, neighborhood characteristics and spatial zoning regulation on long-term land use changes, they are valuable for developing coupled models of social-ecological systems to simulate land use and dependent ecosystem services, and to support sustainable land management.

Suggested Citation

  • Ilkwon Kim & Quang Bao Le & Soo Jin Park & John Tenhunen & Thomas Koellner, 2014. "Driving Forces in Archetypical Land-Use Changes in a Mountainous Watershed in East Asia," Land, MDPI, vol. 3(3), pages 1-24, August.
  • Handle: RePEc:gam:jlands:v:3:y:2014:i:3:p:957-980:d:39179
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    References listed on IDEAS

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    Cited by:

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    3. Wenjie Wang & Chuanrong Zhang & Jenica M. Allen & Weidong Li & Mark A. Boyer & Kathleen Segerson & John A. Silander, 2016. "Analysis and Prediction of Land Use Changes Related to Invasive Species and Major Driving Forces in the State of Connecticut," Land, MDPI, vol. 5(3), pages 1-22, July.
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    5. Tahmineh Ladi & Shaghayegh Jabalameli & Ayyoob Sharifi, 2022. "Applications of machine learning and deep learning methods for climate change mitigation and adaptation," Environment and Planning B, , vol. 49(4), pages 1314-1330, May.

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