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A Hybrid Inexact Optimization Method for Land-Use Allocation in Association with Environmental/Ecological Requirements at a Watershed Level

Author

Listed:
  • Bingkui Qiu

    (College of Public Administration, Jinzhong University, Jinzhong 030619, China
    Jinzhong Culture Ecological Research Center, Jinzhong 030619, China
    College of Public Administration, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Shasha Lu

    (School of Economics and Management, Beijing Forestry University, Beijing 100083, China)

  • Min Zhou

    (College of Public Administration, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Lu Zhang

    (College of Public Administration, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Yu Deng

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing100101, China)

  • Ci Song

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing100101, China)

  • Zuo Zhang

    (College of Public Administration, Huazhong University of Science and Technology, Wuhan 430074, China
    School of Business, Hubei University, Wuhan 430062, China)

Abstract

In this study, an inexact stochastic fuzzy programming (ISFP) model is proposed for land-use allocation (LUA) and environmental/ecological planning at a watershed level, where uncertainties associated with land-use parameters, benefit functions, and environmental/ecological requirements are described as discrete intervals, probabilities and fuzzy sets. In this model, an interval stochastic fuzzy programming model is used to support quantitative optimization under uncertainty. Complexities in land-use planning systems can be systematically reflected, thus applicability of the modeling process can be highly enhanced. The proposed method is applied to planning land use/ecological balance in Poyang Lake watershed, China. The objective of the ISFP is maximizing net benefit from the LUA system and the constraints including economic constraints, social constraints, land suitability constraints, environmental constraints, ecological constraints and technical constraints. Modeling results indicate that the desired system benefit will be between [15.17, 18.29] × 10 12 yuan under the minimum violating probabilities; the optimized areas of commercial land, industrial land, agricultural land, transportation land, residential land, water land, green land, landfill land and unused land will be optimized cultivated land, forest land, grass land, water land, urban land, unused land and landfill will be [228234, 237844] ha, [47228, 58451] ha, [20982, 23718] ha, [33897, 35280] ha, [15215, 15907] ha, [528, 879] ha and [1023, 1260] ha. These data can be used for generating decision alternatives under different scenarios and thus help decision makers identify desired policies under various system-reliability constraints of ecological requirement and environmental capacity. Tradeoffs between system benefits and constraint-violation risks can be tackled. They are helpful for supporting (a) decision of land-use allocation and government investment; (b) formulation of local policies regarding ecological protection, environment protection and economic development; (c) analysis of interactions among economic benefits, system reliability and ecological requirements.

Suggested Citation

  • Bingkui Qiu & Shasha Lu & Min Zhou & Lu Zhang & Yu Deng & Ci Song & Zuo Zhang, 2015. "A Hybrid Inexact Optimization Method for Land-Use Allocation in Association with Environmental/Ecological Requirements at a Watershed Level," Sustainability, MDPI, vol. 7(4), pages 1-25, April.
    • Handle: RePEc:gam:jsusta:v:7:y:2015:i:4:p:4643-4667:d:48451
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    References listed on IDEAS

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    1. Xiaoya Ma & Xiang Zhao, 2015. "Land Use Allocation Based on a Multi-Objective Artificial Immune Optimization Model: An Application in Anlu County, China," Sustainability, MDPI, vol. 7(11), pages 1-20, November.

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