The Barcelona Metropolitan Area (BMA) is located in Catalonia, northeastern Spain. With a population of over 3 billion people, the BMA is one of the most populous metropolitan areas on the Mediterranean coast. A local climatic modification known as the urban heat island (UHI) occurs in the urban areas. The UHI is usually quantified by means of air temperature, although remote sensing can be used to extract a thermal image of the earth's surface to provide temperature values throughout the study area. Estimation of the land surface temperature (LST) for the BMA enabled us to establish the spatial patterns of LST and to detect the poles of heat and cold within the BMA on 24 dates during the 2013-2018 period, distributed among the 4 seasons of the year. To this end we performed a principal component analysis (PCA) and a cluster analysis (CA). Moreover, we employed the Random Forest (RF) regression method to quantify the influence and variation of diverse geographic covariates according to season and location in the study area. Finally, to determine the influence of land covers on temperature, the thermal values of the 4 land covers included in the Corine Land Cover dataset were analyzed: industrial units, continuous urban fabric, green urban areas, and forest areas. Results show that the heat poles are concentrated in industrial areas primarily, followed by urban fabric areas. On the contrary, the cold pole is found in green urban areas, as well as forested areas. The maximum temperature range between land covers was detected in spring and summer, while in winter this difference was negligible. Our study showed that green urban areas presented temperatures up to 2.5 °C lower than in urban areas. The results of the present research are intended to serve as a roadmap for enhancing thermal comfort in the BMA.
Keywords: Barcelona metropolitan area; Corine land cover; Land surface temperature; Landsat 8; PCA; Random forest.
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