Abstract
Urban areas are generally several degrees hotter than surrounding rural areas, which is referred to as the urban heat island effect. Understanding the spatial pattern of land surface temperature (LST) in cities is important for urban planning, heat mitigation, and air pollution studies. This study developed five models to compare how land cover classes, normalized difference vegetation index (NDVI), social factors, and the combinations of social factors with land cover classes and NDVI perform in estimating LST at the census block group level. We found that all three groups of variables contribute significantly to understanding the spatial heterogeneity in LST. Land cover and NDVI explained LST to a similar extent (approx. 70%). Social factors alone explained 53% of LST's variance. Adding social factors in the combined models added little to the explanatory power (4.0%) compared to using land cover classes or NDVI along as independent variables.
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