Changes in the Urban Surface Thermal Environment of a Chinese Coastal City Revealed by Downscaling MODIS LST with Random Forest Algorithm

Analysis of the formation and evolution of urban surface thermal environment is crucial for urban planning and improving the environment of a settlement. Qingdao was selected in this study as a typical coastal city undergoing rapid urbanization, and the spatiotemporal dynamic characteristics of its urban surface thermal environment from 2010 to 2019 were evaluated. The random forest (RF) algorithm was adopted to obtain its land surface temperature (LST) map with 30-m resolution by downscaling the Moderate Resolution Imaging Spectroradiometer (MODIS) LST product; the remote sensing indices emphasizing different land cover types, LST calculated by the radiative transfer equation, and elevation were used as input variables in the algorithm. The heat island intensity (HII), urban heat island (UHI) volume, and UHI grade were used to analyze the spatiotemporal dynamic characteristics of the urban surface thermal environment in Qingdao. The results show an increasing trend in average HII between 1.1 and 2.52°C in the study area over the past 10 years. The northern city appeared to have the highest UHI volume, while change of the UHI volume in Huangdao District of southwestern Qingdao was the most significant. The areas with high HII have gradually expanded during the last 10 years, and the areas with a 10-yr persistently high HII are distributed mainly in old urban areas with high building density and a dense population. Different factors may influence UHI, such as artificial heat sources, surface heat sources, and hybrid heat sources. Finally, adjusting the urban structure, increasing the vegetated area, and changing building colors are proposed to mitigate UHI in the areas with continuously high HII.