The influence of the spatial characteristics of urban green space on the urban heat island effect in Suzhou Industrial Park

Xiao, Xiang; Dong, Li; Yan, Hainan; Yang, Nan; Xiong, Yimei

doi:10.1016/j.scs.2018.04.002

Cited by 173 publications

(70 citation statements)

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“…The ability of green space to relieve LST or UHIs has been widely proven in existing studies [2,16,17,47]. In this study, we attempted to identify the impact of green space on LST and its impact distance for use in the UGS optimization system.…”

Section: Ecological Value Evaluationmentioning

confidence: 99%

“…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.Sustainability 2020, 12, 1844 2 of 18 effects [16,17], absorbing particle air pollutants, improving air quality, infiltrating storms [18][19][20], reducing noise levels [13], and sequestering carbon [21].The social and ecological value of UGS is widely accepted, while its economic value is not as immediately recognizable, because the services it provides are public goods without market prices [22]. However, real estate markets in developed countries and regions with good environmental quality indicate that many people are willing to pay more for urban properties that are close to UGS [23,24].…”

mentioning

confidence: 99%

“…Sustainability 2020, 12, 1844 2 of 18 effects [16,17], absorbing particle air pollutants, improving air quality, infiltrating storms [18][19][20], reducing noise levels [13], and sequestering carbon [21].…”

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The Spatial Optimization and Evaluation of the Economic, Ecological, and Social Value of Urban Green Space in Shenzhen

Zhang

et al. 2020

Sustainability

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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.Sustainability 2020, 12, 1844 2 of 18 effects [16,17], absorbing particle air pollutants, improving air quality, infiltrating storms [18][19][20], reducing noise levels [13], and sequestering carbon [21].The social and ecological value of UGS is widely accepted, while its economic value is not as immediately recognizable, because the services it provides are public goods without market prices [22]. However, real estate markets in developed countries and regions with good environmental quality indicate that many people are willing to pay more for urban properties that are close to UGS [23,24]. Many studies have estimated the economic value or amenity benefits of urban parks and public open spaces [22,25,26].In summary, UGS has high social, ecological, and economic value. A comparative plan for UGS is essential for increasing the ecological and socioeconomic benefits of urban development [27]. To date, many studies have examined the spatial optimization of UGS to maximize its value. Huang et al. [27] used a space optimization strategy to improve the quality and accessibility of green spaces and proposed that this optimization method should be used in UGS planning and management. Zhang et al. [28] developed a multi-objective model to evaluate the diurnal cooling of UGS and identify the best locations and configurations for new UGSs. Unal and Uslu [29] attempted to minimize the distances between people and UGS service areas to optimize UGS. Yoon [30] used a multi-objective model to maximize the cooling effect and connectivity of UGS.Even though the spatial optimization of UGS has often been considered in urban planning research, existing studies typically consider only one function of UGS in their spatial optimization processes, such as its social function (through maximizing accessibility) or ecological function (through maximizing...

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Section: Ecological Value Evaluationmentioning

confidence: 99%

mentioning

confidence: 99%

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The Spatial Optimization and Evaluation of the Economic, Ecological, and Social Value of Urban Green Space in Shenzhen

Zhang

et al. 2020

Sustainability

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“…La dotación, la definimos como la cantidad de área verde mínima (de acceso público), por habitante (m 2 hab -1 ), presente en una determinada demarcación urbana. Estas propuestas descansan en los beneficios (servicios ecosistémicos) que estos espacios verdes tienen para la ciudad (Vásquez, 2016;Morales-Cerdas et al, 2018;Xiao et al, 2018;Vugcic et al, 2019). Flores-Xolocotzi (2017) hace una extensa revisión de estos indicadores.…”

Section: Introductionunclassified

Áreas verdes urbanas en Córdoba, Veracruz, cantidad, ubicación y acceso: un análisis ortogonal

Kuk

Trujillo

García-Albarado

et al. 2019

Remexca

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Los objetivos de este trabajo fueron registrar las áreas verdes, su localización, superficie y distribución, con respecto de las zonas de alta densidad poblacional, las distancias necesarias para acceder a ellas y la dotación por persona en la ciudad de Córdoba, Veracruz, México. Esto con respecto de los estándares que establece la Organización Mundial de la Salud. Se aplicó un análisis ortogonal, basado en la interpretación de imagen de satélite Google Earth y Sistemas de Información Geográfica. Se hizo además un análisis de distancias a partir de áreas de influencia de cada área verde. Los resultados muestran que las áreas verdes de la ciudad de Córdoba están localizadas sin una aparente relación con las ubicaciones de las zonas de mayor densidad de población, la superficie de áreas verdes es muy heterogénea, la distancia promedio hacia ellas es la recomendada; sin embargo, no hay certeza de que ese destino satisfaga las necesidades de los usuarios, la proporción de área verde por habitante fue de 4.02 m2. Se concluye que la aproximación metodológica utilizada es adecuada para la gestión de área verdeAV a escala urbana. Se concluye también que su superficie y distribución en la ciudad es muy heterogénea; las distancias al área verde más cercana desde cualquier punto, aunque aceptables, no son indicador de tener alcance a un área que satisfaga las necesidades del usuario; la dotación de área verde por habitante en la ciudad está por debajo de la mitad que la OMS recomienda.

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“…Negative correlations are observed in the pedestrian air temperature with trees and ground albedo; (2) the effects of cooling factors vary among different LCZ classes, with the increased 60% more trees leading to lower outdoor temperatures for LCZ-4 (0.28 • C), LCZ-5 (0.39 • C), and LCZ-6 (0.54 • C), while higher albedo of asphalt surface (increased by 0.4) is more effective in LCZ-4 (reaches to 0.68 • C) 14:00, compare to LCZ-5 (0.49 • C) and LCZ-6 (0.38 • C); (3) applying combined cooling methods can provoke air temperature reduction (up to 0.96 • C), especially when higher levels of tree quantities (increased by 60%) are coupled with cool ground materials (albedo increased by 0.4). The results can contribute useful information for improving thermal environment in existing residential regions and future residential planning.Sustainability 2020, 12, 2752 2 of 23 vegetation ratio [23], applying appropriate plant layout [24][25][26], and choosing the right vegetation species [27,28], the urban heat load can be alleviated efficiently. The cooling effect of green space is also closely related to tree canopy coverage and size [29].…”

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confidence: 99%

Numerical Simulation of Local Climate Zone Cooling Achieved through Modification of Trees, Albedo and Green Roofs—A Case Study of Changsha, China

Chen

Zheng

2020

Sustainability

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By exploring the cooling potential of tree quantity, ground albedo, green roofs and their combinations in local climate zone (LCZ)-4, LCZ-5, and LCZ-6, this study focuses on the optimum cooling level that can be achieved in open residential regions in Changsha. It designs and models 39 scenarios by integrating in situ measurement and ENVI-met numerical simulation and further compares cooling effects of various combinations of the cooling factors. The results show that (1) an increased number of trees and higher albedo are more effective compared to green roofs in reducing summer potential temperatures at street level (2 m high) in three LCZs. Negative correlations are observed in the pedestrian air temperature with trees and ground albedo; (2) the effects of cooling factors vary among different LCZ classes, with the increased 60% more trees leading to lower outdoor temperatures for LCZ-4 (0.28 °C), LCZ-5 (0.39 °C), and LCZ-6 (0.54 °C), while higher albedo of asphalt surface (increased by 0.4) is more effective in LCZ-4 (reaches to 0.68 °C) 14:00, compare to LCZ-5 (0.49 °C) and LCZ-6 (0.38 °C); (3) applying combined cooling methods can provoke air temperature reduction (up to 0.96 °C), especially when higher levels of tree quantities (increased by 60%) are coupled with cool ground materials (albedo increased by 0.4). The results can contribute useful information for improving thermal environment in existing residential regions and future residential planning.

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The influence of the spatial characteristics of urban green space on the urban heat island effect in Suzhou Industrial Park

Cited by 173 publications

References 9 publications

The Spatial Optimization and Evaluation of the Economic, Ecological, and Social Value of Urban Green Space in Shenzhen

The Spatial Optimization and Evaluation of the Economic, Ecological, and Social Value of Urban Green Space in Shenzhen

Áreas verdes urbanas en Córdoba, Veracruz, cantidad, ubicación y acceso: un análisis ortogonal

Numerical Simulation of Local Climate Zone Cooling Achieved through Modification of Trees, Albedo and Green Roofs—A Case Study of Changsha, China

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