Assessing the Spatial Benefits of Green Roofs to Mitigate Urban Heat Island Effects in a Semi-Arid City: A Case Study in Granada, Spain Sánchez-Cordero, Francisco Nania Escobar, Leonardo Santos Hidalgo García, David López-Chacón, Sergio Ricardo urban heat island Land surface temperature green roof Random forest local climate zone Machine learning Studies show that Nature-Based Solutions can mitigate Urban Heat Island (UHI) effects by implementing green spaces. Green roofs (GRs) may minimize land surface temperature (LST) by modifying albedo. This research predicts, assesses, and measures the impact of reducing the LST by applying green roofs in buildings by using a Random Forest algorithm and different remote sensing methods. To this aim, the city of Granada, Spain, was used as a case study. The city is classified into different Local Climate Zones (LCZs) to determine the area available for retrofitting GRs in built-up areas. A total of 14 Surface Temperature Collection 2 Level-2 images were acquired through Landsat 8–9, while 14 images for spectral indices such as the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Building Index (NDBI), and Proportion Vegetation (PV) were calculated from Sentinel-2 in dates coinciding or close to LST images. Additional factors were considered including the sky view factor (SVF) and water distance (WD). The results suggest that Granada has limited suitable areas for retrofitting GRs, and available areas can reduce LST with a moderate impact, at an average of 1.45 °C; however, vegetation plays an important role in decreasing LST. This study provides a methodological example to identify the benefits of implementing GRs in reducing LST in semi-arid cities and recommends a combination of strategies for LST mitigation. 2025-07-08T09:23:38Z 2025-07-08T09:23:38Z 2025-06-16 journal article Sánchez-Cordero, F.; Nanía, L.; Hidalgo-García, D.; López-Chacón, S.R. Assessing the Spatial Benefits of Green Roofs to Mitigate Urban Heat Island Effects in a Semi-Arid City: A Case Study in Granada, Spain. Remote Sens. 2025, 17, 2073. [DOI: 10.3390/rs17122073] https://hdl.handle.net/10481/105110 10.3390/rs17122073 eng http://creativecommons.org/licenses/by/4.0/ open access Atribución 4.0 Internacional MDPI