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Several studies demonstrate the potential of models for the representation of phenomena such as urban heat islands. This article aimed to analyze atmospheric heat islands (UHIucl) by integrating primary air temperature data with spatial information such as land use and relief from a multicriteria model based on multiple linear regression. Furthermore, we compared the measured and estimated air temperature at 11 p.m. with the surface temperature at 10:51 p.m. (local time). These temperatures were obtained through the thermal band of the Landsat 8 satellite considering extraction points of interest in Presidente Prudente city, Brazil. The multicriteria model showed reliability in UHIucl spatialization, reaching the confidence interval (p-value ≤ 0.05). The model proves that urban surface materials are the main energy sources modulating heat transfer to the atmosphere, while vegetation has a temperature-reducing effect. Precise mappings such as the one proposed here are relevant for the formulation of measures that support decision-making by public authorities. These mappings aim at urban planning that is resilient to the effects of urban climate and can be replicated in other realities.

Multicriteria Spatial Modeling: Methodological Contribution to the Analysis of Atmospheric and Surface Heat Islands in Presidente Prudente, Brazil