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The Estimation of a Remote Sensing Model of Three-Dimensional Green Space Quantity and Research into Its Cooling Effect in Hohhot, China

Author

Listed:
  • Qian Dong

    (The Forestry College, Inner Mongolia Agriculture University, Hohhot 010019, China
    The Geological Science College, Inner Mongolia Normal University, Hohhot 010010, China)

  • Qiuliang Zhang

    (The Forestry College, Inner Mongolia Agriculture University, Hohhot 010019, China)

Abstract

With the continuous advancement of urbanization, the urban heat island effect has become increasingly prominent. Studying the cooling effect of urban green space can provide direction for improving the comfort of urban residents and reducing the harm caused by the urban heat island. In this paper, the band information was extracted from remote sensing images, and eight vegetation indices were calculated for Hohhot, such as normalized differential vegetation index (NDVI) and vegetation coverage (VC). The land surface temperature (LST) was calculated using the split-window algorithm, and the total 3D-GSQ, the three-dimensional green space quantity per unit area (3D-GSQP), and the single plant 3D-GSQ of different tree species were measured on the spot. The relationships between 3D-GSQP and eight vegetation indexes were processed by correlation analysis and regression analysis, and the remote sensing estimation model of 3D-GSQP was established. The correlation between 3D-GSQP and LST was established, and the cooling effect was analyzed in depth. The results indicate that: (1) The contributions to 3D-GSQ types of common tree in the built-up area of Hohhot are (from large to small): Salix babylonica , Populus hopeiensis , Gleditsia sinensis Lam , Salix matsudana , and Saphora japonica ; and the 3D-GSQ of single types of shrubs are (from large to small): Amygdalus triloba , syringa oblata , Sorbaria sorbifolia , ligustrum lucidum , and Euonymus alatus . (2) The linear equation with the chlorophyll vegetation index (CVI) as the independent variable is suitable for the parameters of an inversion model for the 3D-GSQP (R 2 = 0.72), and the regression model of the two is: 3D-GSQP = −30.412 + 35.842 × CVI. (3) The 3D-GSQP in the study area is mainly in the range of 0–15.78 m 3 /m 2 , and in such range it has an obvious negative relationship (R 2 = −0.73) with LST to the level of 0.01 (unilateral). When the 3D-GSQP increases by 1 m 3 /m 2 , the LST decreases by 0.55 °C, and this result sufficiently indicates that the urban green has an obvious cooling effect. In the future, in order to improve the living environment of urban residents, in addition to considering the green space area, we should pay more attention to the requirements of the 3D-GSQP index.

Suggested Citation

  • Qian Dong & Qiuliang Zhang, 2022. "The Estimation of a Remote Sensing Model of Three-Dimensional Green Space Quantity and Research into Its Cooling Effect in Hohhot, China," Land, MDPI, vol. 11(9), pages 1-21, August.
    • Handle: RePEc:gam:jlands:v:11:y:2022:i:9:p:1437-:d:902653
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    References listed on IDEAS

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    1. Abdullah Addas & Ran Goldblatt & Steven Rubinyi, 2020. "Utilizing Remotely Sensed Observations to Estimate the Urban Heat Island Effect at a Local Scale: Case Study of a University Campus," Land, MDPI, vol. 9(6), pages 1-26, June.
    2. Yunfang Jiang & Jing Huang & Tiemao Shi & Hongxiang Wang, 2021. "Interaction of Urban Rivers and Green Space Morphology to Mitigate the Urban Heat Island Effect: Case-Based Comparative Analysis," IJERPH, MDPI, vol. 18(21), pages 1-29, October.
    3. Shanshan Chen & Dagmar Haase & Bing Xue & Thilo Wellmann & Salman Qureshi, 2021. "Integrating Quantity and Quality to Assess Urban Green Space Improvement in the Compact City," Land, MDPI, vol. 10(12), pages 1-14, December.
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    1. Shengyu Guan & Shuang Liu & Xin Zhang & Xinlei Du & Zhifang Lv & Haihui Hu, 2023. "Analysis of Supply–Demand Relationship of Cooling Capacity of Blue–Green Landscape under the Direction of Mitigating Urban Heat Island," Sustainability, MDPI, vol. 15(14), pages 1-22, July.

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