Multi-objective optimization of urban blue-green space configuration using NSGA-II for enhanced ecosystem services

The exacerbation of global climate change has led to the continuous deterioration of the urban ecological environment. Scientifically planning blue-green spaces can mitigate ecological crises and promote sustainable urban development. There exists a close relationship between the ecological benefits of blue-green spaces and their spatial characteristics, and synergistically enhancing the ecological service efficiency of blue-green spaces through these two aspects is an urgent research topic. This study integrates four ecological benefit objectives—carbon sink, cooling, stormwater resilience, and biodiversity—and applies a multi-objective optimization framework based on grid-based spatial decision units to optimize blue-green space configurations. By establishing a multi-ecological benefit evaluation framework, this study combines ecological benefit assessment models with the NSGA-II multi-objective optimization algorithm and the entropy weight method for weight allocation. Ultimately, an optimal scenario and four preference-oriented scenarios for blue-green space layouts are derived. A case study in Nanjing, China, demonstrates the applicability of the integrated optimization framework in generating urban blue-green spatial layouts that balance multiple ecological benefit objectives. The results indicate that carbon sink and cooling show a positive synergy, while biodiversity and stormwater resilience exhibit trade-off tendencies, and the comprehensive scenario achieves a relatively balanced performance across objectives. The spatial layout characteristics of blue-green spaces vary distinctively across different ecological benefit objectives, with the multi-objective comprehensive optimal under the given proxies, constraints and algorithm settings demonstrating relative balance. The proposed multi-objective optimization methodology for blue-green spatial configuration provides scientifically quantifiable decision-making support for urban blue-green space planning.