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ВЗАИМОСВЯЗЬ МЕЖДУ ТЕМПЕРАТУРОЙ ПОВЕРХНОСТИ ЗЕМЛИ И КОЭФФИЦИЕНТОМ ВИДИМОСТИ НЕБА (НА ПРИМЕРЕ КОПТЕВСКОГО РАЙОНА МОСКВЫ)
Rapid urbanization, compounded by global climate change, is exacerbating the Urban Heat Island (UHI) effect — encompassing both Surface Urban Heat Island (SUHI) and Atmospheric Urban Heat Island (AUHI) — posing significant threats to public health. While the relationship between urban morphology, particularly the Sky View Factor (SVF), and Land Surface Temperature (LST) has been extensively investigated, analyzing high-density urban areas with complex structures remains a significant challenge. Insitu experimental methods are often constrained by limited spatial scalability and precision due to the intricate nature of urban microclimates; conversely, thermal infrared satellite data (such as Landsat 8) is limited by coarse spatial resolution. This study proposes a regression-based approach to refine LST maps derived from Landsat 8 by integrating high-resolution spectral indices (NDVI, NDBI, and NDWI) extracted from both Landsat 8 and Sentinel-2 platforms. This approach leverages the thermal-sensing capabilities of Landsat 8 in conjunction with the superior spatial resolution of Sentinel-2 to generate highly detailed surface temperature distribution maps. The findings provide profound insights into the correlation between LST variations and urban morphological parameters, including SVF, height-to-width (H/W) ratio, and distance. This methodology serves as a valuable tool for microclimate monitoring, supporting urban planners in making informed strategic decisions to mitigate the adverse impacts of the UHI effect in contemporary urban environments.