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This article aims to study the intensity of park cooling effect on temperature reduction in urban areas. In this study, the Landsat-8 images (2015-2020) during the summer season were used to assess the Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI) data and the correlation of green area characteristics and Park Cooling Intensity (PCI) by utilizing the remote sensing and Google Earth Engine (GEE). The results of this study showed that the 3 Public Parks (i.e. Wachirabenchathat Park, Lumphini Park, and Makut Rommayasaran Park) have the average LST (average + standard deviation; S.D.) were 27.34 + 1.23, 27.62 +1.59 add 27.86 + 1.36 °C and the average NDVI were 0.55 + 0.03, 0.53 + 0.02 and 0.42 + 0.05, respectively. In case of the correlation of LST and NDVI, they were negative correlation with a coefficient (R2) of 0.8929 at a significance level of 0.01. In case of PCI analysis on green urban area, we found that the large public parks, low complexity area (shape uncertainty) and complicated shape the optimal proportion of pervious, canopy, and water area were related to the PCI of surrounding area. Therefore, the expansion of urban public parks and increasing of proportion of vegetation, pervious and water source inside the public park would be the important way to increase the cooling intensity. Moreover, another cooling sources in surrounding area can enhance the efficiency of cooling intensity and temperature reduction inside the urban area. Lastly, this study would be the important reference for future urban planning and urban public park design to mitigate the urban heat island.
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