(untitled) (CIPEEX, 2026)
The Brazilian Cerrado, recognized as one of the planet’s main biodiversity hotspots, faces increasing pressures from agricultural intensification and climate change. This paper presents the development of a Thermal Vulnerability Index, which integrates environmental variables and machine learning techniques to identify areas susceptible to thermal variability, with a comparative focus across the regions of the state of Goiás (1985-2024). Region 1 (Central-South), has established itself as an industrial logistics hub, driving urban densification, real estate expansion, and agricultural intensification in the surrounding area. Region 2 (Northeastern Goiás) combines conservation areas of high ecological significance, family farming, and recent frontiers of agricultural expansion, configuring a mosaic in which anthropogenic pressures and ecosystem services co-evolve. The index was developed using models capable of "learning" patterns from data and estimating a synthetic index based on historical patterns. Although both regions have a tropical climate, the Center-South is Tropical High Altitude (Cwa), while Northeast Goiás is Tropical (Aw); the results reveal differences in the historical values ​​of the calculated index between them. Region 1, despite its higher altitude and lower temperatures, presented higher average levels of vulnerability compared to Region 2, with vulnerability hotspots highlighted in both. The findings highlight the need to integrate conservation, restoration, and green infrastructure with urban and rural planning, as well as territorialized policies sensitive to the historical and environmental specificities of each region.