Urban green biomass plays a critical role in regulating the ecological and thermal environment of rapidly urbanizing cities. This study aims to assess the spatio-temporal dynamics of urban green biomass and its relationship with land surface temperature (LST) in Tashkent using remote sensing techniques. Multispectral satellite data from Landsat 8/9 were processed within the Google Earth Engine platform for the period 2015–2025. Vegetation indices, including the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), were calculated to quantify green biomass distribution and dynamics. Additionally, LST was derived to evaluate the thermal environment of the study area. The results indicate a general decreasing trend in NDVI and EVI values over the study period, suggesting a gradual reduction in urban green biomass. In contrast, LST exhibits an increasing trend, highlighting intensifying urban heat island effects. The correlation analysis between NDVI and LST reveals a negative relationship (R² ≈ 0.10), indicating that areas with higher vegetation density tend to have lower surface temperatures. However, the relatively weak correlation suggests that additional factors, such as urban structure and land use patterns, also influence thermal dynamics. The findings demonstrate the importance of integrating vegetation indices and thermal data for urban ecological monitoring and provide valuable insights for sustainable urban planning and green infrastructure development.
Ermakhametova et al. (Mon,) studied this question.