Enhancing Ecosystem Service Value Through Land Use Optimization: A Multi-Objective Particle Swarm Optimization (PSO) Approach in Wuhan, China

Integrating ecosystem service value (ESV) into land use optimization is crucial for achieving sustainable development goals. Unlike traditional “post-evaluation” approaches that assess ESV after generating land use plans, this study pioneers a “goal-oriented” method by embedding ESV as an objective to guide land use optimization. A multi-objective particle swarm optimization (PSO) framework, which incorporates ESV with land quantity error, spatial aggregation of farmland and construction land, and economic benefits, was constructed for the research study. Applied to Wuhan, China, for the periods of 2005–2015 and 2010–2020, the results demonstrate the feasibility of the proposed framework in: (1) reducing construction land area while increasing farmland and ecological land; (2) spatially aggregating construction land towards urban functional areas while protecting farmland and ecological land in peri-urban and outer suburban areas; (3) improving spatial aggregation of farmland, construction land, and ecological land; and (4) slightly increasing ESV, particularly in peri-urban and outer suburban areas. The proposed PSO framework provides a valuable tool for optimizing land use layout, enhancing ecosystem service provision, and promoting balanced socio-ecological development.