Examining the Impact of Greenspace Patterns on Land Surface Temperature by Coupling LiDAR Data with a CFD Model

Understanding the link between greenspace patterns and land surface temperature is very important for mitigating the urban heat island (UHI) effect and is also useful for planners and decision-makers for providing a sustainable design for urban greenspace. Although coupling remote sensing data with...

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Main Authors: Weizhong Su, Yong Zhang, Yingbao Yang, Gaobin Ye
Format: Article
Language:English
Published: MDPI AG 2014-09-01
Series:Sustainability
Subjects:
Online Access:http://www.mdpi.com/2071-1050/6/10/6799
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spelling doaj-a1593f0eb0a047da8abc46a9a8dec0292020-11-24T20:59:11ZengMDPI AGSustainability2071-10502014-09-016106799681410.3390/su6106799su6106799Examining the Impact of Greenspace Patterns on Land Surface Temperature by Coupling LiDAR Data with a CFD ModelWeizhong Su0Yong Zhang1Yingbao Yang2Gaobin Ye3State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, No. 73 East Beijing Road, Nanjing 210008, ChinaSchool of Earth Sciences and Engineering, Hohai University, No. 1 Xikang Road, Nanjing 210098, ChinaSchool of Earth Sciences and Engineering, Hohai University, No. 1 Xikang Road, Nanjing 210098, ChinaState Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, No. 73 East Beijing Road, Nanjing 210008, ChinaUnderstanding the link between greenspace patterns and land surface temperature is very important for mitigating the urban heat island (UHI) effect and is also useful for planners and decision-makers for providing a sustainable design for urban greenspace. Although coupling remote sensing data with a computational fluid dynamics (CFD) model has widely been used to examine interactions between UHI and greenspace patterns, the paper aims to examine the impact of five theoretical models of greenspace patterns on land surface temperature based on the improvement of the accuracy of CFD modeling by the combination of LiDAR data with remote sensing images to build a 3D urban model. The simulated results demonstrated that the zonal pattern always had the obvious cooling effects when there are no large buildings or terrain obstacles. For ambient environments, the building or terrain obstacles and the type of greenspace have the hugest influence on mitigating the UHI, but the greenspace area behaves as having the least cooling effect. A dotted greenspace pattern shows the best cooling effect in the central area or residential district within a city, while a radial and a wedge pattern may result in a “cold source” for the urban thermal environment.http://www.mdpi.com/2071-1050/6/10/6799greenspace patternsland surface temperatureurban heat island (UHI)computational fluid dynamics (CFD) modelLiDAR data
collection DOAJ
language English
format Article
sources DOAJ
author Weizhong Su
Yong Zhang
Yingbao Yang
Gaobin Ye
spellingShingle Weizhong Su
Yong Zhang
Yingbao Yang
Gaobin Ye
Examining the Impact of Greenspace Patterns on Land Surface Temperature by Coupling LiDAR Data with a CFD Model
Sustainability
greenspace patterns
land surface temperature
urban heat island (UHI)
computational fluid dynamics (CFD) model
LiDAR data
author_facet Weizhong Su
Yong Zhang
Yingbao Yang
Gaobin Ye
author_sort Weizhong Su
title Examining the Impact of Greenspace Patterns on Land Surface Temperature by Coupling LiDAR Data with a CFD Model
title_short Examining the Impact of Greenspace Patterns on Land Surface Temperature by Coupling LiDAR Data with a CFD Model
title_full Examining the Impact of Greenspace Patterns on Land Surface Temperature by Coupling LiDAR Data with a CFD Model
title_fullStr Examining the Impact of Greenspace Patterns on Land Surface Temperature by Coupling LiDAR Data with a CFD Model
title_full_unstemmed Examining the Impact of Greenspace Patterns on Land Surface Temperature by Coupling LiDAR Data with a CFD Model
title_sort examining the impact of greenspace patterns on land surface temperature by coupling lidar data with a cfd model
publisher MDPI AG
series Sustainability
issn 2071-1050
publishDate 2014-09-01
description Understanding the link between greenspace patterns and land surface temperature is very important for mitigating the urban heat island (UHI) effect and is also useful for planners and decision-makers for providing a sustainable design for urban greenspace. Although coupling remote sensing data with a computational fluid dynamics (CFD) model has widely been used to examine interactions between UHI and greenspace patterns, the paper aims to examine the impact of five theoretical models of greenspace patterns on land surface temperature based on the improvement of the accuracy of CFD modeling by the combination of LiDAR data with remote sensing images to build a 3D urban model. The simulated results demonstrated that the zonal pattern always had the obvious cooling effects when there are no large buildings or terrain obstacles. For ambient environments, the building or terrain obstacles and the type of greenspace have the hugest influence on mitigating the UHI, but the greenspace area behaves as having the least cooling effect. A dotted greenspace pattern shows the best cooling effect in the central area or residential district within a city, while a radial and a wedge pattern may result in a “cold source” for the urban thermal environment.
topic greenspace patterns
land surface temperature
urban heat island (UHI)
computational fluid dynamics (CFD) model
LiDAR data
url http://www.mdpi.com/2071-1050/6/10/6799
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AT yingbaoyang examiningtheimpactofgreenspacepatternsonlandsurfacetemperaturebycouplinglidardatawithacfdmodel
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