Optimization of Urban Greenery with Consideration of Biodiversity, Air Quality, and the Impact on the Microclimate

Urban greenery is a key urban planning feature of a sustainable city with a wide array of ecological and social benefits such as enhanced biodiversity, improved air quality, and stabilized urban microclimates. The present research aims to develop a mathematical model for optimization for the strategic design and spatial planning of urban greenery based on ecological, environmental, and thermal performance considerations. The proposed framework combines species richness indicators, particulate matter absorption ratios, and land surface temperature data into a multi-objective optimization model through linear programming and spatial analysis. The model is then utilized in a case study of an Iranian mid-sized city, using satellite imagery, urban GIS data, and climate records to simulate various green space configurations. Optimization is constrained by land use patterns in the urban environment, available space, and socio-demographic patterns for pragmatic implementation and adherence to urban master plans. Outcomes highlight the trade-offs between air purification/cooling capacity versus biodiversity maximization, indicating the importance of plant species selection, canopy form, and spatial connectivity. Sensitivity analysis indicates that climate-resilient and native species significantly enhance ecosystem service supply and reduce maintenance cost. The prognostic power of the model helps urban planners and environmental managers make informed investment choices on green infrastructure, especially in the second phase of the Islamic Revolution statement. This integrative mathematical model provides a replicable model for achieving ecologically balanced and climatically adaptable urban space.

کلیدواژه ها:

Urban green space ، Mathematical optimization ، Biodiversity ، Air quality ، Microclimate ، Sustainable urban planning