Abstract
Urban green space (UGS) is important in urban systems, as it benefits economic development, ecological conservation, and living conditions. Many studies have evaluated the economic, ecological, and social value of UGS worldwide, and spatial optimization for UGS has been carried out to maximize its value. However, few studies have simultaneously examined these three values of UGS in one optimization system. To fill this gap, this study evaluated the economic value of UGS in terms of promoting housing prices, its ecological value through the relief of high land surface temperature (LST), and its social value through the provision of recreation spaces for residents within a 255 m distance. Subsequently, these three values were set as objectives in a genetic algorithm (GA)-based multi-objective optimization (MOP) system. Shenzhen was taken as the case study area. The results showed that the influencing distance of UGS in Shenzhen for house prices was 345 m, and the influencing distance of UGS for LST was 135 m. Using MOP, the Pareto solutions for increasing UGS were identified and presented. The results indicate that MOP can simultaneously optimize UGS’s economic, ecological, and social value.
Highlights
Urban residents are expected to constitute two-thirds of the world’s population by the year 2050
This study evaluates the social, economic, and ecological value of Urban green space (UGS) in Shenzhen and uses the most popular genetic algorithm (GA)-based multi-objective optimization (MOP) model to optimize the spatial distribution of UGS, to simultaneously maximize its social, economic, and ecological value
OCobn3:stMraainxitm: Tiozitnagl isnoccrieaalsveadlugereoefngsrpeeancesmpaucset be less than ConP ∗ AreaUGS, where NDGSdx is the density of UGS after optimization, and a1 and a2 are the coefficients determined by Equation (1) andOEbq3ua=tio(Nn D(2G).SH51D0 −isDthGeSd5e10n)s∗iAtycocMf haopusing rental price sample poin(t7s); LST is the land surface temperature of Shenzhen; and AccMap is the spatial distribution of accesCsiobnilsitrya.iCnto:nTPoitsalthinecrraetaiose, dangdreAenresapUaGcSe ims tuhset abreelaeossf tUhGanS CinoSnhPe∗nAzrheaeUnG
Summary
Urban residents are expected to constitute two-thirds of the world’s population by the year 2050. A large body of literature has shown that UGS has high social value, as it improves urban residents’ quality of life [6,7]. It has a beneficial impact on the physical and mental health of human beings by providing spaces for leisure and physical activity [3,5,8,9,10]. Few studies have considered the full value of UGS in social, economic, and ecological terms simultaneously in the optimization process. GA-based MOP is used to carry out the optimization for UGS to simultaneously maximize its economic, social, and ecological value. The second section introduces the study area and data sources; the third section details the methods used in this study; and the fourth and fifth sections present the results, conclusions, and discussion
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
