Land surface and air temperature dynamics: The role of urban form and seasonality.

Due to the scarcity of air temperature (Ta) observations, urban heat studies often rely on satellite-derived Land Surface Temperature (LST) to characterise the near-surface thermal environment. However, there remains a lack of a quantitative understanding on how LST differs from Ta within urban areas and what are the controlling factors of their interaction. We use crowdsourced air temperature measurements in Sydney, Australia, combined with urban landscape data, Local Climate Zones (LCZ), high-resolution satellite imagery, and machine learning to explore the influence of urban form and fabric on the interaction between Ta and LST. Results show that LST and Ta have distinct spatiotemporal characteristics, and their relationship differs by season, ecological infrastructure, and building morphology. We found greater seasonal variability in LST compared to Ta, along with more pronounced intra-urban spatial variability in LST, particularly in warmer seasons. We also observed a greater temperature difference between LST and Ta in the built environment compared to the natural LCZs, especially during warm days. Natural LCZs (areas with mostly dense and scattered trees) showed stronger LST-Ta relationships compared to built areas. In particular, we observe that built areas with higher building density (where the heat vulnerability is likely more pronounced) show insignificant or negative relationships between LST- Ta in summer. Our results also indicate that surface cover, distance from the ocean, and seasonality significantly influence the distribution of hot and cold spots for LST and Ta. The spatial distribution for Ta hot spots does not always overlap with LST. We find that relying solely on LST as a direct proxy for the urban thermal environment is inappropriate, particularly in densely built-up areas and during warm seasons. These findings provide new perspectives on the relationship between surface and canopy temperatures and how these relate to urban form and fabric.

Background climate modulates the impact of land cover on urban surface temperature.

Cities with different background climates experience different thermal environments. Many studies have investigated land cover effects on surface urban heat in individual cities. However, a quantitative understanding of how background climates modify the thermal impact of urban land covers remains elusive. Here, we characterise land cover and their impacts on land surface temperature (LST) for 54 highly populated cities using Landsat-8 imagery. Results show that urban surface characteristics and their thermal response are distinctly different across various climate regimes, with the largest difference for cities in arid climates. Cold cities show the largest seasonal variability, with the least seasonality in tropical and arid cities. In tropical, temperate, and cold climates, normalised difference built-up index (NDBI) is the strongest contributor to LST variability during warm months followed by normalised difference vegetation index (NDVI), while normalised difference bareness index (NDBaI) is the most important factor in arid climates. These findings provide a climate-sensitive basis for future land cover planning oriented at mitigating local surface warming.

Dynamic thermal pleasure in outdoor environments - temporal alliesthesia.

Thermal comfort research has been historically centred around the concept of "thermal neutrality". Thermal neutrality originates from the steady-state indoor environment and is increasingly questioned when used to define the optimum sensation in outdoor environments. This calls for new criteria, designated for non-steady state and dynamically evolving outdoor settings. To address this need, we investigated thermal pleasure dynamics in outdoor environments based on thermal alliesthesia - a psychophysiological framework for understanding the hedonic responses elicited by non-steady-state thermal exposures. Detailed field studies were conducted in Sydney, Australia, during a 30-day period covering both summer and winter with a total of 35 subjects. The thermal sensation scale was quantitatively divided into four alliesthesial potential areas - two with moderate and two with strong alliesthesial potential - based on their divergence to the preferred sensation. We find that the temporal pleasure change (dP) can be predicted using thermal sensation change (dT). The results showed that linear regression performed strongly (R2 = 0.77 for summer and R2 = 0.79 for winter) in predicting dP when subjects' preceding sensation was in the strong alliesthesial potential zones - namely the 'Hot' and 'Cold' areas. When subjects' prior thermal sensation fell in the thermoneutral zone with moderate alliesthesial potential, a quadratic fit against dT provides a more reasonable prediction of dP (R2 = 0.61 for summer and R2 = 0.56 for winter). The dynamic thermal pleasure models provide a more nuanced subjective interpretation of outdoor urban spaces that includes thermal pleasure and delight. This study contributes further empirical support to the thermal alliesthesia framework and extends its application scope into outdoor thermal comfort research.