Mapeamento do ambiente térmico e suas relações com os parâmetros do entorno urbano

Abstract

This research aims to verify the thermal environment of a campus university, by evaluating the relative contribution of urban elements towards the modification of the air temperature. For this purpose, real data of air temperature were collected at several points of the Federal University of São Carlos (UFSCar). These were then related to the local urban indexes, by applying the technique of Artificial Neural Networks (ANN), in order to develop a prediction model. This analysis considered three different scales of approaching, taking the radius of 25, 50 and 100 meters as references. Within the areas of these radii, the Occupation Coefficient (OC), the Urban Vegetation Coefficient (UVC), the Sky View Factor (SVF) and the Ground Cover Coefficient (GCC) were estimated. This method allowed the observation of interactions among these urban parameters and the thermal tendencies. The mathematical model developed by ANN training process was identified and described to be incorporated into a Geographical Information System. By this procedure, thematic maps were developed and, consequently, a microclimatic classification for the case study was proposed. The results pointed out that the urban indexes under investigation presented different relative importance according to the scale of analysis. For the diurnal period, the urban indexes had significant influence in the air temperatures of the Campus. Furthermore, the Urban Vegetation Coefficient was one of the most important parameters in the determination of the thermal patterns reached in the Campus area.