Surface urban heat island distribution and socioeconomic inequalities in a major Latin American agglomeration

Abstract

Surface urban heat island (SUHI) distribution in urban areas is influenced by land cover changes caused by urbanization, which are often related to socioeconomic factors. Greater Mexico City (GMC), one of the world’s largest urban areas with the most pronounced socioeconomic disparities, provides a unique case for investigating this relationship and was consequently selected for this study. This study integrates socioeconomic data from the 2020 National Economic Census, Marginalization and Deprivation Indices, and environmental variables, such as the Normalized Difference Vegetation Index (NDVI), Normalized Difference Build-Up Index (NDBI), Land Surface Temperature, and aerosol optical depth (AOD), from remote sensing instruments to investigate their relationship with SUHI distribution. Machine learning classifiers, including Random Forest and eXtreme Gradient Boosting, were applied to determine the importance of these variables in defining SUHI patterns. Physical variables (AOD, NDVI, and NDBI) and economic marginalization were found to significantly influence SUHI spatial patterns. The irregular zoning of Mexico City results in similar SUHI exposures across socioeconomic groups. While marginalization does not significantly affect SUHI intensity, less-marginalized groups are better equipped to mitigate its negative impacts. These findings emphasize the need for targeted mitigation strategies based on socioeconomic factors and provide critical insights for sustainable urban planning.