Optimizing the spatial pattern (spatial compositive and spatial configuration) of urban greenspace can effectively alleviate the urban heat island effect. While the relationship between air temperature (AT) and spatial composition of urban greenspace has been widely studied, this study aimed to investigate the relationship between AT and spatial configuration of urban greenspace and its diurnal variations and scale effects. Based on hourly AT data from 36 meteorological stations in Changsha, China, and land cover data interpreted from the Gaofen 2 remote sensing images, this study first quantified spatial composition (i.e., percent of greenspace) and spatial configuration (i.e., average patch area, patch density, edge density, landscape shape index, and mean shape index) of urban greenspace at different scales (30 m to 2000 m buffer surrounding the air station), then Pearson correlations (between AT and each landscape metric) and partial Pearson correlations (between AT and spatial configuration metrics with percent of greenspace controlled) were analyzed. Multiple linear regression was applied to model the variation of AT using the landscape metrics as independent variables. Finally, the variance partitioning analysis was performed to investigate the relative importance of spatial composition and spatial configuration of urban greenspace to explain the variation of AT. The results showed that (1) the temperature range reached 1.73 °C during the day and 2.94 °C at night. Urban greenspace was fragmented especially at small scales. (2) The Pearson correlation between AT and percent of greenspace fluctuated with the increase of scale and was generally higher during the day than during the night. (3) The spatial pattern of urban greenspace explained as high as 55% of the AT variation, showing diurnal variations and scale effects (i.e., a maximum of 0.54 during the day at 50 m buffer and a maximum of 0.55 during the night at 400 m buffer). (4) A higher percent of greenspace, more aggregated greenspace patches, and simpler greenspace shapes can generate a stronger cooling effect. (5) The relative importance of spatial composition and spatial configuration of greenspace varied among spatial scales and showed diurnal variations. These results emphasize the scale effect as well as diurnal variation of the relationship between urban greenspace spatial pattern and AT. These findings provide theoretical guidance for urban greenspace planning and management to improve the urban thermal environment in rapidly developing subtropical cities such as Changsha, China.

Understanding how urban park landscape features are associated with service population and service radius can inform park planning and management. In Changsha, China, this study measured both indicators for 29 parks on one weekday and one weekend day in spring 2025 using mobile signaling data, quantified landscape features from multisource data, and examined their associations. Service population and service radius were not highly correlated. The adjusted R² values for the two indicators were 71.8% and 84.5%, respectively. Park area and the number of parking lots within the park were significantly associated with both indicators in the same direction. Percent vegetation cover and the number of stores within the park were significantly associated with the two indicators in opposite directions. Elevation, presence of large-scale flower landscapes, distance to the nearest subway station, number of surrounding bus stops, distance to the city center, slope, percent water body, edge density of vegetation patches, number of public restrooms, and number of surrounding residential quarters were significantly associated with only one indicator. These findings reveal synergistic, trade-off, and indicator-specific association patterns between landscape features and urban park recreational services, and may inform differentiated urban park planning and management.