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Optimization of the Territorial Spatial Patterns Based on MOP and PLUS Models: A Case Study from Hefei City, China

Author

Listed:
  • Ran Yu

    (School of Economics and Management, Anhui Agricultural University, Hefei 230036, China
    Institute of Land and Resources, Anhui Agricultural University, Hefei 230036, China)

  • Hongsheng Cheng

    (School of Economics and Management, Anhui Agricultural University, Hefei 230036, China)

  • Yun Ye

    (School of Economics and Management, Anhui Agricultural University, Hefei 230036, China)

  • Qin Wang

    (School of Economics and Management, Anhui Agricultural University, Hefei 230036, China)

  • Shuping Fan

    (School of Economics and Management, Anhui Agricultural University, Hefei 230036, China
    Institute of Land and Resources, Anhui Agricultural University, Hefei 230036, China)

  • Tan Li

    (School of Economics and Management, Anhui Agricultural University, Hefei 230036, China)

  • Cheng Wang

    (School of Economics and Management, Anhui Agricultural University, Hefei 230036, China
    Institute of Land and Resources, Anhui Agricultural University, Hefei 230036, China)

  • Yue Su

    (School of Economics and Management, Anhui Agricultural University, Hefei 230036, China
    Institute of Land and Resources, Anhui Agricultural University, Hefei 230036, China)

  • Xingyu Zhang

    (Wuxi Forestry Station, Wuxi 214000, China)

Abstract

Optimization of the territorial spatial patterns can promote the functional balance and utilization efficiency of space, which is influenced by economic, social, ecological, and environmental factors. Consequently, the final implementation of spatial planning should address the issue of sustainable optimization of territorial spatial patterns, driven by multiple objectives. It has two components—the territorial spatial scale prediction and its layout simulation. Because a one-sided study of scale or layout is divisive, it is necessary to combine the two to form complete territorial spatial patterns. This paper took Hefei city as an example and optimized its territorial spatial scale using the multiple objective programming (MOP) model, with four objective functions. A computer simulation of the territorial spatial layout was created, using the patch-generating land use simulation (PLUS) model, with spatial driving factors, conversion rules, and the scale optimization result. To do this, statistical, empirical, land utilization, and spatially driven data were used. The function results showed that carbon accumulation and economic and ecological benefits would be ever-increasing, and carbon emissions would reach their peak in 2030. The year 2030 was a vital node for the two most important land use types in the spatial scale—construction land and farmland. It was projected that construction land would commence its transition from reduced to negative growth after that time, and farmland would start to rebound. The simulation results indicated that construction land in the main urban area would expand primarily to the west, with supplemental expansion to the east and north. In contrast, construction land in the counties would experience a nominal increase, and a future ecological corridor would develop along the route south of Chaohu County–Chaohu Waters–Lujiang County–south of Feixi County.

Suggested Citation

  • Ran Yu & Hongsheng Cheng & Yun Ye & Qin Wang & Shuping Fan & Tan Li & Cheng Wang & Yue Su & Xingyu Zhang, 2023. "Optimization of the Territorial Spatial Patterns Based on MOP and PLUS Models: A Case Study from Hefei City, China," IJERPH, MDPI, vol. 20(3), pages 1-15, January.
  • Handle: RePEc:gam:jijerp:v:20:y:2023:i:3:p:1804-:d:1040386
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    References listed on IDEAS

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    1. Lopes, André Soares & Cavalcante, Camila Bandeira & Vale, David Sousa & Loureiro, Carlos Felipe Grangeiro, 2020. "Convergence of planning practices towards LUT integration: Seeking evidences in a developing country," Land Use Policy, Elsevier, vol. 99(C).
    2. Wu, Xutong & Wang, Shuai & Fu, Bojie & Liu, Yu & Zhu, Yuan, 2018. "Land use optimization based on ecosystem service assessment: A case study in the Yanhe watershed," Land Use Policy, Elsevier, vol. 72(C), pages 303-312.
    3. Robert Pontius & Wideke Boersma & Jean-Christophe Castella & Keith Clarke & Ton Nijs & Charles Dietzel & Zengqiang Duan & Eric Fotsing & Noah Goldstein & Kasper Kok & Eric Koomen & Christopher Lippitt, 2008. "Comparing the input, output, and validation maps for several models of land change," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 42(1), pages 11-37, March.
    4. Dingrao Feng & Wenkai Bao & Meichen Fu & Min Zhang & Yiyu Sun, 2021. "Current and Future Land Use Characters of a National Central City in Eco-Fragile Region—A Case Study in Xi’an City Based on FLUS Model," Land, MDPI, vol. 10(3), pages 1-25, March.
    5. Maleki, Jamshid & Masoumi, Zohreh & Hakimpour, Farshad & Coello Coello, Carlos A., 2020. "A spatial land-use planning support system based on game theory," Land Use Policy, Elsevier, vol. 99(C).
    6. Cattivelli, Valentina, 2021. "Planning peri-urban areas at regional level: The experience of Lombardy and Emilia-Romagna (Italy)," Land Use Policy, Elsevier, vol. 103(C).
    7. Zhang, Zuo & Li, Jiaming, 2022. "Spatial suitability and multi-scenarios for land use: Simulation and policy insights from the production-living-ecological perspective," Land Use Policy, Elsevier, vol. 119(C).
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