The rapid changes of land covers in urban areas are one of major environmental concerns because of their environmental impacts. Such land cover changes include the transformation of green space to impervious surface, and the increase of land surface temperature (LST). The objective of this study was to examine the spatial variation of urban landscape composition and configuration, as well as their influences on LST in Suzhou City, China. Landsat-8 image was processed to extract land covers and retrieve LSTs that were used to study relationship between spatial variation of LST and land covers. The results indicated that there was a significantly negative correlation between mean LST and green space coverage along the urban–rural gradients. With every 10% increased green space coverage, the mean LST drop was about 1.41 °C. A grid-base analysis performed at various grid sizes indicated that an increase in the percentage of surface water body area has a greater cooling effect of the mean LST than a vegetation increase. The mean LST had a significantly negative correlation with both the shape and aggregation indexes of the green space patches. Our results suggest that the sustainable landscape planning of green space in a typical city with a large water area should include both the vegetation and the surface water covers. The increased percentage of vegetation and surface water covers had the greatest cooling effect on an urban thermal environment, which is one of the ecosystem services that green space provides. A dense distribution of green space patches with complex shapes should be considered in urban sustainable landscape planning for increasing ecosystem services.
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