Proposing an effective and inexpensive tool to detect urban surface temperature changes associated with urbanization processes in small cities

A consequence of urbanization is the loss of vegetation cover, replaced by urban areas. This study investigates the evolution of the built-up areas and its influence on increasing the surface temperature through methodology applicable to small and medium-sized municipalities where urbanization process monitoring is limited. For the case study, the municipality of Penedo, located in the State of Alagoas, was selected. Landsat-5 and Landsat-8 images were used to evaluate urban landscape through normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), and the land surface temperature (LST). A simple tool that summarizes NDBI and LST changes was proposed - the Change Detection Index (CDI). It was possible to highlight areas where the increase in temperatures is associated with the built area's intensification. Furthermore, the machine learning k-means clustering tool was applied to create groups and analyze the relationship between urbanization and temperature increase, confirming the CDI values and validating this tool. An evident increase in the built area was highlighted by CDI and cluster analysis, indicating a heat island's potential formation at the implantation area of a housing complex in the municipality. The spatial analysis indicates priority areas for intervention by a simple methodology that facilitated dialogue and understanding between stakeholders, associated with a low-cost tool with the potential for reproduction and adaptation, providing indicators to urban studies and decision-makers and handle the lack of monitoring data in small and medium-sized municipalities. [Display omitted] •A low-cost method is developed for a thermal surface assessment of small cities.•The proposed Change Detection Index combines NDBI and LST variations.•K-means grouping analysis was combined with the Change Detection Index.•UHI vulnerable areas were identified, allowing local mitigation strategies indication.•The method allows the monitoring of the urban plan's efficacy implementation.