Multi-objective Optimization Model for 3D Urban Green Space to Reduce Urban Heat Island

Abstract

With rapid urbanization, the type of land cover and spatial composition of cities have changed dramatically. These changes have had significant impacts on the urban environment, such as the urban heat island (UHI) effect. UHI has a significant impact on greenhouse gas emissions, energy consumption, and the health of residents. Urban Green Spaces (UGS) are an effective way to address the urban heat island effect. UGS can reduce temperatures by providing shade and evapotranspiration. There are several types of UGS, with the most popular methods currently being green roofs, green walls and street trees. They can be effective in providing heat reduction benefits to cities without taking up too much space for urban development. The location, type, size and number of UGS have a significant impact on their thermal effect. With limited construction cost of urban green space, the selection of green space and the right size of installation area are key factors to achieve high cooling efficiency. However, in previous studies, UGS planning was carried out using 2D methods, which are unable to evaluate wall greenery and mainly use statistical methods to evaluate the cooling effect of greenery due to the limitations of 2D. In this study, we intend to build a 3D Multi-objective Optimization Model to optimize the layout of green spaces in the city. The spatial optimization algorithm NSGA II evaluates the trade-off between cost and cooling effectiveness by considering various parameters of UGS (type, size, location, cost, etc.) and derives the solution set of the optimal layout solution. The model is expected to provide urban planners with accurate and rational construction planning.