Development of Downscaled Urban Land Surface Temperature for New York City

Land surface temperature (LST) is a crucial climate change indicator, and it is also used to evaluate the land-atmosphere energy budget. One of the advantages of remote sensing is its ability to monitor the variation of LST at high spatial and temporal resolutions. However, there are no available satellite LST products with both high spatial and temporal resolutions. This paper, therefore, proposes a method to obtain high spatial and temporal resolutions by combining Landsat 8's Thermal Infrared Sensor and the Geostationary Operational Environmental Satellite-R Series (GOES-R) LST data for urban regions. The obtained combined satellite product gives promising results as the model seems to perform well. The downscaled LST were validated with the Landsat 8 and in-situ LST observations. Differences between the predicted and the observed LSTs ranged from −0.09 to 3.30 K.