4.7 Article

The Cooling Effect of Urban Parks and Its Monthly Variations in a Snow Climate City

Journal

REMOTE SENSING
Volume 9, Issue 10, Pages -

Publisher

MDPI
DOI: 10.3390/rs9101066

Keywords

urban parks; cooling effect; land surface temperature; monthly variations

Funding

  1. project of Multidisciplinary Scientific Investigation in the boundary of China [2017FY101301]
  2. project of Multidisciplinary Scientific Investigation in the boundary of Russia [2017FY101301]
  3. project of Multidisciplinary Scientific Investigation in the boundary of Mongolia [2017FY101301]
  4. National Natural Science Foundation of China [41301466]
  5. China Scholarship Council

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Urban parks have been shown to form park cool islands (PCIs), which can effectively alleviate the negative influences of urban heat islands (UHI). However, few studies have examined the detailed characteristics of PCIs, the effect of urban park features on their individual temperatures, and monthly variation in PCIs. Land surface temperature (LST) retrieved from Landsat 8 TIR images between May and October were used to represent the thermal environment. Urban park characteristics were extracted from high-resolution GF-2 images. Using these datasets, the relationships between urban park characteristics and PCIs were explored in this study using Changchun, which has a snow climate, as a case study. The results showed the following: (1) the urban parks exhibited a cooling island effect, and the PCIs showed significant monthly variations with the highest intensities in the hot months; (2) the effects of composition (e.g., park size and the percentage of water area) on LSTs and PCIs showed significant monthly variability and were stronger than the configuration effects. Furthermore, an unexpected, negative correlation between PCIs and the area of park grass was also found; and (3) larger parks tended to have stronger PCI intensities and extents of influence. For parks larger than 30 ha, the cooling effects extended approximately 480 m from the park edge between June and August. For all of parks during the study duration, the rate of temperature increase was highest within 60 m from the park edge. The PCI we employ specifically in this study is characterized by LST.

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