The quantitative relationship between all commonly used landscape metrics and land surface temperature （LST） across three spatial contexts including the main urban area， the urban development area， and the entire municipality of Wuhan City was analyzed by deriving the LST values and classifying land cover categories of Wuhan city based on Landsat 8-9 remote sensing data acquired on September 18 and 19， 2022 to study the effects of the patterns of blue-green spatial landscape on the LST to better utilize the thermal environment regulation function of blue-green infrastructure. The principal component regression analysis was used to identify the dominant factors affecting LST under different spatial contexts and reveal their underlying mechanisms. The results showed that water bodies and green spaces had a significant “cooling island effect”， with the cooling intensity of water bodies （8.96-9.34 ℃） significantly greater than that of green spaces （4.44-5.47 ℃）. Overall， the independent explanatory power of the landscape metrics for LST changes followed in the order of water bodies > green spaces， landscape composition > spatial configuration， patch-level > landscape-level > class-level， and the main urban area > the urban development area > the administrative area. The dominant factors affecting LST varied across spatial contexts. The four key factors in the main urban area were the percentage of water body area （PLAND_W）， water body patch density （PD_W）， effective mesh size of green spaces （MESH_G）， and edge density of green spaces （ED_G）， collectively explaining 82.4% of the LST variation. The dominant factors in the metropolitan development area were contrast-weighted edge density of water bodies （CWED_W）， percentage of water body area （PLAND_W）， mean proximity index of green spaces （SIMI_MN_G）， and percentage of green space area （PLAND_G）， collectively explaining 59.2% of the LST variation. The five dominant landscape metrics related to blue-green spaces in the entire municipality， only explained 35% of the LST variation. Water bodies and construction land had a strong explanatory power for changes in the thermal environment， and the cooling effect of green spaces was significantly weakened or suppressed when considering the combined effects of other landscape elements outside of blue-green spaces. It is indicated that the regulation function of blue-green infrastructure in the thermal environment has a distinct context effect. Measures for optimizing the spatial allocation and structural configuration of blue-green landscapes according to different environmental matrices including preserving large water bodies in central urban areas， ensuring adequate water surface coverage， enhancing connectivity between smaller water bodies， enriching the morphological complexity of blue-green spaces in urban development zones and metropolitan regions， and strengthening their interactive frequency with surrounding environments can effectively enhance the cooling performance of blue-green infrastructure.