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

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 beta 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.

Automated summary

The study implemented an ecologically constrained urban expansion simulation model in Wuhan, China, based on an ordered weighted averaging operator aggregating multiple ecosystem services. Results indicate that incorporating constraints from ecosystem services is beneficial for ecological conservation, but excessive constraint intensity may lead to unintended consequences such as excessive loss of farmland and irregular urban patterns. A relatively softer constraint strategy was considered optimal for a win-win scenario between urban expansion and ecological conservation.