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

约束(计算机辅助设计) 马尔可夫链 生态系统服务 细胞自动机 娱乐 计算机科学 细分 环境资源管理 生态系统 环境经济学 数学优化 生态学 环境科学 数学 经济 工程类 土木工程 人工智能 生物 几何学 机器学习
作者
Yan Zhang,Chang Xia,Yanfang Liu,Yanchi Lu,Yiheng Wang,Yaolin Liu
出处
期刊:Land Use Policy [Elsevier BV]
卷期号:108: 105667-105667 被引量:59
标识
DOI:10.1016/j.landusepol.2021.105667
摘要

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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