Work

Enhancing Our View from Above: A Downscaling Technique to Reveal Finer-Scale Urban Heat Patterns

Year: 2026

Type: article

Abstract: Remotely sensed surface temperature data are widely used by researchers and municipal practitioners to characterize urban thermal patterns and assess the impacts of increasing urban heat. While satellite-derived land surface temperature (LST) data effectively identify broad-scale patterns, their 30 m spatial resolution limits their ability to resolve fine-scale thermal variability. Downscaling approaches have been developed to generate higher-resolution LST products; however, in the absence of independent, high-resolution surface temperature observations, it remains difficult to determine whether the additional spatial variation introduced by downscaling reflects meaningful landscape-related thermal structure or model-generated variability. Our objective was to evaluate whether the additional spatial variation introduced by downscaling LST from 30 to 10 m was statistically consistent with independently derived land cover composition and landscape compositional heterogeneity. Using an open-source random forest model, we downscaled Landsat 8/9 LST to 10 m resolution using Sentinel-2-derived predictors over a summer season in Kelowna, BC, Canada. We quantified the additional thermal variation introduced through downscaling and used Generalized Additive Models (GAMs) to relate this variation to high-resolution land cover characteristics summarized within 100 m grid cells. Land cover composition and landscape compositional heterogeneity together explained 65.5% of the additional variation introduced by downscaling. Added thermal variation was most strongly associated with canopy and impervious cover, two landscape characteristics consistently identified as major controls on urban land surface temperature. These findings suggest that the additional spatial variation introduced through downscaling is consistent with independently derived landscape structure known to influence urban thermal patterns. Rather than providing direct validation of downscaled temperatures, this analysis offers an indirect means of evaluating whether downscaled LST produces interpretable, landscape-consistent thermal variability that may be useful for urban analysis and planning.

Source: Remote Sensing

DOI: 10.3390/rs18183091

Authors: Evan Shea, Aubrey Benson, Tijmen Witvliet, Mark Fillo, Melissa R. McHale

Institution: University of British Columbia

Language: English

Topic: Urban Heat Island Mitigation

Subfield: Environmental Engineering

Field: Environmental Science

Domain: Physical Sciences

SDGs: Sustainable cities and communities, Climate action

Open Access status: gold

Estimated APC paid: $3,258