A New Framework for Studying Urban Heat Island and Surface Energy Budget Using Remote Sensing and Ground Observations

The urban heat island (UHI) is among the major environmental issues encountered in urban regions. To better predict the dynamics of the UHI and its impact on extreme heat events, accurate characterization of the surface energy balance in urban regions is required. However, the ability to accurately understand the climate processes in urban areas due to heterogeneity of the surfaces is limited due to incomplete knowledge of the urban surface energy balance. This study aims to enhance the understanding of the urban surface energy budget and land surface temperature from satellite observations. Here, a multisensor LST data with 5-min temporal and 30 m spatial resolution is developed by downscaling the Geostationary Operational Environmental Satellites-R series (GOES-R) LST data over New York City. In situ LST data are used to evaluate the accuracy of the downscaled LST. Differences between the predicted and the observed LSTs ranged from -0.09 to 3.30 degrees C.