Landscape Ecology

, Volume 34, Issue 12, pp 2949–2961 | Cite as

Impact of urban greenspace spatial pattern on land surface temperature: a case study in Beijing metropolitan area, China

  • Jie Yin
  • Xiaoxu WuEmail author
  • Miaogen Shen
  • Xiaoli Zhang
  • Chenghao Zhu
  • Hongxu Xiang
  • Chunming ShiEmail author
  • Zhiyi Guo
  • Chenlu Li
Research Article



Urban greenspace can significantly decrease the land surface temperature (LST). The spatial characteristics and vegetation composition of urban greenspace have a great influence on its cooling capacity.


We sought to distinguish the cooling effect by different spatial pattern factors of greenspace and by the interaction of these factors, which may be useful in understanding cooling effect and designing urban greenspace.


Both the greenspace derived from SPOT6 and LST retrieved from Landsat-8 images are employed to identify the dominant factors influencing LST and investigate the interaction between any two dominant factors in the Beijing metropolitan area.


The results indicate that the dominant spatial factors affecting LST vary by greenspace type, i.e., for grass, the number of patches (NP) and patch density (PD) have a significant effect on LST while for coniferous forest, the landscape shape index (LSI) is the dominant spatial factor. And the NP and percentage of landscape are the dominant spatial factors for broad-leaved forest and mixed forest, respectively. The interaction of any two dominant factors is larger than their individual effects, and the interaction between the NP and LSI of greenspace is not as strong as the interaction between the NP and PD.


Urban greenspace design and planning need to consider the spatial pattern of different types of greenspace. On this basis, we proposed a pattern effective in cooling LST in cities climatically similar to Beijing, which could provide theoretical reference for the design and planning of urban greenspace.


Urban greenspace Land surface temperature Spatial pattern Geo-detector Interactive effect 



This work was funded by the National Key Research and Development Program of China (Nos. 2018YFC1406906, and 2016YFA0600104) and Top-Notch Young Talents Program of China (to Shen).

Compliance with ethical standards

Conflict of interest

The authors declare no conflict of interest.

Supplementary material

10980_2019_932_MOESM1_ESM.docx (2.4 mb)
Electronic supplementary material 1 (DOCX 2413 kb)


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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  • Jie Yin
    • 1
    • 2
  • Xiaoxu Wu
    • 1
    Email author
  • Miaogen Shen
    • 3
  • Xiaoli Zhang
    • 2
  • Chenghao Zhu
    • 4
  • Hongxu Xiang
    • 1
  • Chunming Shi
    • 1
    Email author
  • Zhiyi Guo
    • 1
  • Chenlu Li
    • 1
  1. 1.State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System ScienceBeijing Normal UniversityBeijingChina
  2. 2.Beijing Key Laboratory of Precision Forestry, Forestry CollegeBeijing Forestry UniversityBeijingChina
  3. 3.Key Laboratory of Alpine Ecology and Biodiversity, CAS Center for Excellence in Tibetan Plateau Earth Sciences, Institute of Tibetan Plateau ResearchChinese Academy of SciencesBeijingChina
  4. 4.Satellite Environment CenterMinistry of Environmental ProtectionBeijingChina

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