U.S. Department of Agriculture: Agricultural Research Service, Lincoln, Nebraska


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Environmental factors such as urban landscape patterns, local climate, topography, and socioeconomic conditions have significant impacts on land surface temperature (LST), especially through the urban heat island effect. At present, in-depth studies on the mechanisms determining LST in different seasons in winter cities are lacking. In this study, we used structural equation modeling for 12 environmental factors to characterize how these factors affect the temporal and spatial heterogeneity of the LST in the winter city of Shenyang, China. We found that the most critical factors affecting LST varied with season. Specifically, the distances from the nearest water body and nearest green space had the largest impacts on the LST in spring and summer, with path coefficients of 0.51 and 0.19 for spring and 0.42 and 0.21 for summer, respectively. In winter, the main factors affecting LST were elevation, slope, and population density, with respective path coefficients of -0.5, -0.41, and 0.29. Our findings suggest that the urban thermal environment in this winter city can be improved by: optimizing the landscape pattern of green spaces and water bodies; and reducing the population density by establishing satellite cities. This study highlights how landscape pattern can be used to regulate the urban thermal environment and mitigate predicted climate change impacts on the quality, health, and safety of urban living.

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