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Urban expansion simulation under constraint of multiple ecosystem services (MESs) based on cellular automata (CA)-Markov model: Scenario analysis and policy implications

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  • Zhang, Yan
  • Chang, Xia
  • Liu, Yanfang
  • Lu, Yanchi
  • Wang, Yiheng
  • Liu, Yaolin

Abstract

Ecologically constrained urban expansion simulation (EC-UES) is an effective means to plan sustainable urban landscapes. Current studies typically set ecological constraints using Boolean logic while dismissing the spatially continuous and gradual features of ecological substrates. They also overlook the multiple ecosystem services (MESs) that an ecosystem provides and correlations among MESs. This study aggregated MESs (i.e., food productivity, water yield, carbon storage, biodiversity potential, erosion prevention, and outdoor recreation), based on an ordered weighted averaging (OWA) operator. An EC-UES was conducted for Wuhan, China by integrating the aggregation result as a constraint into a cellular automata (CA)-Markov chain model. By varying the β coefficient of the OWA, multiple scenarios of MESs constraint were designed and used to generate urban land patterns in different scenarios. We compared spatial patterns, quantities, and ecological effects of urban expansion in four typical scenarios. The results show that the incorporation of MESs constraint is beneficial for ecological conservation. However, the intensity of the constraint is not linearly proportional to benefit; very strong constraints from MESs may lead to the excessive loss of farmland and the irregularity and fragmentation of urban patterns. Compared to the conventional constraint strategy, a relatively soft constraint strategy was considered optimal. This study provides a reference for a win–win simulation between urban expansion and ecological conservation.

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  • Zhang, Yan & Chang, Xia & Liu, Yanfang & Lu, Yanchi & Wang, Yiheng & Liu, Yaolin, 2021. "Urban expansion simulation under constraint of multiple ecosystem services (MESs) based on cellular automata (CA)-Markov model: Scenario analysis and policy implications," Land Use Policy, Elsevier, vol. 108(C).
    • Handle: RePEc:eee:lauspo:v:108:y:2021:i:c:s0264837721003902
    DOI: 10.1016/j.landusepol.2021.105667
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    3. Hadj Ali, Célia & Roy, Damien & Amireche, Louisa & Antoni, Jean-Philipe, 2023. "Development of a Cellular Automata-based model approach for sustainable planning of affordable housing projects: an application case study in Algiers," Land Use Policy, Elsevier, vol. 125(C).
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    5. Fatemeh Mohammadyari & Ardavan Zarandian & Mir Mehrdad Mirsanjari & Jurate Suziedelyte Visockiene & Egle Tumeliene, 2023. "Modelling Impact of Urban Expansion on Ecosystem Services: A Scenario-Based Approach in a Mixed Natural/Urbanised Landscape," Land, MDPI, vol. 12(2), pages 1-24, January.
    6. Mohammadyari, Fatemeh & Tavakoli, Mohsen & Zarandian, Ardavan & Abdollahi, Sedighe, 2023. "Optimization land use based on multi-scenario simulation of ecosystem service for sustainable landscape planning in a mixed urban - Forest watershed," Ecological Modelling, Elsevier, vol. 483(C).
    7. Jinsen Mou & Zhaofang Chen & Junda Huang, 2023. "Predicting Urban Expansion to Assess the Change of Landscape Character Types and Its Driving Factors in the Mountain City," Land, MDPI, vol. 12(4), pages 1-20, April.
    8. Canying Zeng & Shaohua Wu & Hua Zhou & Min Cheng, 2022. "The Impact of Urbanization Growth Patterns on Carbon Dioxide Emissions: Evidence from Guizhou, West of China," Land, MDPI, vol. 11(8), pages 1-18, August.
    9. Fan, Yunfei & He, Liuyue & Liu, Yi & Wang, Sufen, 2022. "Optimal cropping patterns can be conducive to sustainable irrigation: Evidence from the drylands of Northwest China," Agricultural Water Management, Elsevier, vol. 274(C).

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