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

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  • Weizhong Su

    (State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, No. 73 East Beijing Road, Nanjing 210008, China)

  • Yong Zhang

    (School of Earth Sciences and Engineering, Hohai University, No. 1 Xikang Road, Nanjing 210098, China
    These authors contributed equally to this work.)

  • Yingbao Yang

    (School of Earth Sciences and Engineering, Hohai University, No. 1 Xikang Road, Nanjing 210098, China
    These authors contributed equally to this work.)

  • Gaobin Ye

    (State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, No. 73 East Beijing Road, Nanjing 210008, China
    University of Chinese Academy of Sciences, No. 19A Yuquan Road, Beijing 100049, China)

Abstract

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.

Suggested Citation

  • Weizhong Su & Yong Zhang & Yingbao Yang & Gaobin Ye, 2014. "Examining the Impact of Greenspace Patterns on Land Surface Temperature by Coupling LiDAR Data with a CFD Model," Sustainability, MDPI, vol. 6(10), pages 1-16, September.
    • Handle: RePEc:gam:jsusta:v:6:y:2014:i:10:p:6799-6814:d:40832
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    References listed on IDEAS

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    1. Poudyal, Neelam C. & Hodges, Donald G. & Tonn, Bruce & Cho, Seong-Hoon, 2009. "Valuing diversity and spatial pattern of open space plots in urban neighborhoods," Forest Policy and Economics, Elsevier, vol. 11(3), pages 194-201, May.
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    Cited by:

    1. Yingbao Yang & Xize Zhang & Xi Lu & Jia Hu & Xin Pan & Qin Zhu & Weizhong Su, 2017. "Effects of Building Design Elements on Residential Thermal Environment," Sustainability, MDPI, vol. 10(1), pages 1-15, December.
    2. Chong Peng & Chu Li & Zuyu Zou & Suwan Shen & Dongqi Sun, 2015. "Improvement of Air Quality and Thermal Environment in an Old City District by Constructing Wind Passages," Sustainability, MDPI, vol. 7(9), pages 1-21, September.
    3. Toparlar, Y. & Blocken, B. & Maiheu, B. & van Heijst, G.J.F., 2017. "A review on the CFD analysis of urban microclimate," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 1613-1640.
    4. Chong Peng & Tingzhen Ming & Jianquan Cheng & Yongjia Wu & Zhong-Ren Peng, 2015. "Modeling Thermal Comfort and Optimizing Local Renewal Strategies—A Case Study of Dazhimen Neighborhood in Wuhan City," Sustainability, MDPI, vol. 7(3), pages 1-20, March.
    5. Karol Kostúr & Marek Laciak & Milan Durdan, 2018. "Some Influences of Underground Coal Gasification on the Environment," Sustainability, MDPI, vol. 10(5), pages 1-31, May.

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