The Urban Heat Island (UHI) effect refers to the temperature difference between urban and surrounding rural areas, with higher temperatures in urban areas, especially after sunset. The Surface Urban Heat Island (SUHI), a proxy for UHI, can be evaluated using Remote Sensing (RS) data by calculating the Land Surface Temperature (LST). Bragança (Portugal) has an in situ network, with 23 sensors installed in 2011, classified into seven different Local Climate Zones (LCZs), to measure Air Temperature (Tair). The primary objectives of this study were to: i) calculate the LST using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data available on Google Earth Engine (GEE) from 2000-2023 at these 23 points, divided into spring/summer (a); and autumn/winter (b); ii) calculate and analyze the Intensity of SUHI (SUHIint) (2000-2023), using LST, based on the temperature difference recorded at each sensor compared to the average temperature at the Rural Areas (RCD) sensors, and evaluate the thermal behavior in the LCZs; iii) calculate the UHI (UHIint), using Tair data; and iv) correlate SUHIint and UHIint (2011-2023). As a result, 17 images from (a) and four from (b) were processed, and the highest LST medians were associated with classes featuring anthropogenic elements in both, with (a) being more heterogeneous. Comparisons between SUHIint and UHIint, were obtained in 13 days, only from (a). The highest median temperature values were in anthropogenic classes. The correlation between SUHIint and UHIint was "strong" (74%) and "very strong" (26%), confirming their similarity in thermal behaviour.
Urban Heat Island (UHI) is an effect that corroborates to the increase of temperature in urban settlements when compared to the surrounding vegetated areas, especially after sunset. This research aimed to understand the Surface Urban Heat Island (SUHI), a sub-classification correlated to the UHI effect, in the city of Bragança (Portugal), at 23 points classified in different Local Climate Zone (LCZ), between 2003 and 2022, using Remote Sensing (RS) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The data were obtained at four passage times: 11 am, 1 pm, 10 pm and 2 am and analyzed separately for summer and winter. Qualitative and quantitative analyses were applied, using an average of 1,337 Land Surface Temperature (LST) data, processed in the Google Earth Engine (GEE) platform. The computation of the SUHI intensity (SUHIint) for each year was obtained from the differences in LST between each of the LCZ and the average values from Rural Areas (RCD), considering both summer and winter campaigns. The boxplots showed similar medians in all LCZs at 11 am and 1 pm. At 10 pm and 2 am, only slight differences were found among the median values. The similarity in results may be associated with the low spatial resolution of the sensor and the difficulty in distinguishing between LCZs. The SUHIint was positive in most of the results (about 71%). Of the 23 points analyzed, ten were not located in unique pixels, which compromised the analysis of the results in the different LCZs. This condition reinforces the need for use higher spatial resolution data to allow for a differentiation among LCZs data.
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