The spatial optimization and evaluation of the economic, ecological, and social value of urban green space in Shenzhen

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 v...

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Main Authors: YU, Yuhan, ZHANG, Wenting, FU, Peihong, HUANG, Wei, LI, Keke, CAO, Kai
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Language:English
Published: Institutional Knowledge at Singapore Management University 2020
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Online Access:https://ink.library.smu.edu.sg/sis_research/5130
https://ink.library.smu.edu.sg/context/sis_research/article/6133/viewcontent/sustainability_12_01844_pv_oa.pdf
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spelling sg-smu-ink.sis_research-61332023-10-30T02:43:47Z The spatial optimization and evaluation of the economic, ecological, and social value of urban green space in Shenzhen YU, Yuhan ZHANG, Wenting FU, Peihong HUANG, Wei LI, Keke CAO, Kai 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. 2020-03-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/5130 info:doi/10.3390/su12051844 https://ink.library.smu.edu.sg/context/sis_research/article/6133/viewcontent/sustainability_12_01844_pv_oa.pdf http://creativecommons.org/licenses/by/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University green space multi-objective optimization Shenzhen sustainable development house prices Asian Studies Databases and Information Systems Urban Studies and Planning
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic green space
multi-objective optimization
Shenzhen
sustainable development
house prices
Asian Studies
Databases and Information Systems
Urban Studies and Planning
spellingShingle green space
multi-objective optimization
Shenzhen
sustainable development
house prices
Asian Studies
Databases and Information Systems
Urban Studies and Planning
YU, Yuhan
ZHANG, Wenting
FU, Peihong
HUANG, Wei
LI, Keke
CAO, Kai
The spatial optimization and evaluation of the economic, ecological, and social value of urban green space in Shenzhen
description 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.
format text
author YU, Yuhan
ZHANG, Wenting
FU, Peihong
HUANG, Wei
LI, Keke
CAO, Kai
author_facet YU, Yuhan
ZHANG, Wenting
FU, Peihong
HUANG, Wei
LI, Keke
CAO, Kai
author_sort YU, Yuhan
title The spatial optimization and evaluation of the economic, ecological, and social value of urban green space in Shenzhen
title_short The spatial optimization and evaluation of the economic, ecological, and social value of urban green space in Shenzhen
title_full The spatial optimization and evaluation of the economic, ecological, and social value of urban green space in Shenzhen
title_fullStr The spatial optimization and evaluation of the economic, ecological, and social value of urban green space in Shenzhen
title_full_unstemmed The spatial optimization and evaluation of the economic, ecological, and social value of urban green space in Shenzhen
title_sort spatial optimization and evaluation of the economic, ecological, and social value of urban green space in shenzhen
publisher Institutional Knowledge at Singapore Management University
publishDate 2020
url https://ink.library.smu.edu.sg/sis_research/5130
https://ink.library.smu.edu.sg/context/sis_research/article/6133/viewcontent/sustainability_12_01844_pv_oa.pdf
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