<![CDATA[The Urban Heat Island (UHI) phenomenon is a critical environmental issue in tropical urban areas such as Yogyakarta, especially in dense zones with diverse building typologies. This study aims to analyze the relationship between building typology and UHI intensity using a spatial approach powered by Python. Land surface temperature data were extracted from Landsat 8 imagery, while building typologies were classified based on spatial functions (residential, commercial, mixed-use, and public). Through overlay analysis and heatmap visualization, it was found that commercial and mixed-use buildings exhibited the highest surface temperatures (up to 34.2 °C), while residential and vegetated public facilities showed lower temperatures (around 27–29 °C). The open-source-based approach (GeoPandas, Rasterio, Folium) proved effective for spatial mapping and correlational analysis. This research contributes significantly to thermal mitigation strategies based on building morphology and supports adaptive planning for tropical cities facing microclimate change.]]>
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