Multiscale Analysis of Land Surface Temperature (LST) for Urban Heat Island (UHI): Combining Satellite and Unmanned Aerial Vehicle (UAV) in Bragança (Portugal)

The Urban Heat Island (UHI) effect is characterized by higher temperatures in urbanized areas compared to surrounding vegetated areas, particularly during the period between sunset and sunrise. This effect can influence the local microclimate, leading to socio-environmental impacts. Various factors contribute to the formation of UHI, such as albedo, surface material types, and morphology, making certain areas more prone to accumulating electromagnetic energy and retaining greater amounts of sensible heat. Remote Sensing (RS) is one of the methodologies used to study this effect, allowing the acquisition of Land Surface Temperature (LST) data without physical contact between the sensor and the target. This enables the mapping of large areas with complex geological formations and limited accessibility. Sensors can be deployed on different platforms, such as satellites, airplanes, and unmanned aerial vehicle (UAV), each with specific characteristics regarding operational features and spatial, temporal, and spectral resolutions.  The objective of this study was to analyze, on a multi-scalar level, the UHI effect in different Local Climate Zones (LCZ) in Bragança (Portugal) using LST data obtained from Landsat 8 and 9 satellites, UAVs and Air Temperature (Ta) data, obtained in situ collection, from a network with 23 sensors. The results show that anthropogenic surfaces tend to retain more heat and amplify UHI formation across all techniques despite the satellite overpass time (around 11 a.m.) not being ideal for UHI studies.  Regarding spatial resolution, Landsat LST was effective for analyzing homogeneous and macro-scale areas, while UAV proved to be more effective in capturing and distinguishing LST in heterogeneous areas or zones of transition between LCZs typologies. Both Ta and LST from the UAV and satellite showed a high correlation. These findings highlight the added value of using multi-scalar techniques for UHI studies.