Urban green space (UGS), as a form of green infrastructure, has been given increasing attention in urban planning and its policies. The quality of a UGS is fundamental for the sustainable development of the urban economy, society, environment, and quality of human life, although UGS is unevenly distributed within cities. Aiming to analyze the quality of UGS at the scale of Jiedaos in China, this paper took Haizhu district in Guangzhou as a case study based on collected data from 2010 and aerial imagery from 2012. The Urban Neighborhood Green Index (UNGI) was established by combining four weighted parameters: the green index (P1), the density of buildings (P2), proximity to green areas (P3) and building height (P4). Results from comparing with green index show that (1) the UNGI performed better for UGS planning due to its ability of uncovering impact of the built environment and its accessibility on quality of UGS; (2) the UGS has significant effects on neighbors, which underlies social inequity of UGS supply and presents rich information for urban planning and decision making; (3) a small green field attaching to a community plays a key role in fulfilling the need of neighbors for green space, fitness, and leisure in China, which is usually ignored due to the ownership of private property. It suggests recognizing UGS and improving its quality in old towns as well as improving urban villages characterized by poor quality of green space with green infrastructures. The UNGI can inform city planners regarding their consideration of UGS, and it can contribute to measurements of sustainability and the development of green infrastructure.

Previous investigations of urban heat islands (UHI) are primarily focused either on the canopy heat island intensity (aUHII) derived from weather stations, or on the surface urban heat island intensity (sUHII) derived from satellite instruments. Research of the relationship between sUHII and aUHII (the sUHII‐aUHII relationship) is limited and this study attempts to further progress this possibility by examining the night‐time sUHII‐aUHII relationship for three factors: season, wind speed (WS), and basic land‐use categories modified from local climate zones (urban/suburban), in Birmingham, United Kingdom. Using high‐resolution datasets of canopy air temperature from Birmingham Urban Climate Laboratory and land surface temperature from the MODIS instrument aboard the Terra and Aqua satellites, with a unique methodology of regression analysis, confidence ellipse analysis of covariance (ANCOVA), and 2‐D Kolmogorov–Smirnov (K‐S) tests, statistical evidence is provided to present the varying patterns and magnitudes between sUHII and aUHII. The significance of the impact of the three considered factors is clearly supported by the statistical tests. The results indicate that satellite data can be used to infer aUHII with a higher confidence for low WS conditions. Results also demonstrate better confidence in the approach for summer and spring seasons, and for more urbanized sites. Indeed, the analysis potentially indicates that wind advection is a key factor for the investigation of the sUHII‐aUHII relationship. Overall, the methods used here are transferable to other cities and/or can be used to guide further research to explore the sUHII‐aUHII relationship under other environmental conditions.

Urban heat islands have garnered significant attention due to their potential impact on human life. Previous studies on urban heat islands have focused on characterizing temporal and spatial variations over longer periods of time. In this study, we investigated the urban heat island (UHI) in Birmingham from September 2013 to August 2014 using higher temporal resolution SEVIRI satellite surface temperature data along with data from the Birmingham Urban Climate Laboratory (BUCL) meteorological station and the UK Meteorological Office meteorological station. Our aim was to characterize the diurnal variations in the surface urban heat island intensity (SUHII) and canopy urban heat island intensity (CUHII) and to explore their relationship under the influence of three factors (day/nighttime, season, and wind speed) using regression analysis. Our findings reveal that SUHII and CUHII exhibit relatively stable patterns at night but vary significantly during the day with opposite diurnal trends. In addition, SUHII and CUHII were more variable in spring and summer but less variable in winter. During the nighttime, SUHII represents CUHII with high confidence, especially during spring and summer, but less so during the cold season. In addition, SUHII represents CUHII with greater confidence under low-wind conditions. This study deepens our understanding of the diurnal dynamics of urban heat islands and the influence of atmospheric conditions on the relationship between surface and canopy heat islands in urban areas. The results of this study can be used for heat island studies in cities that lack high-precision observation networks and to guide sustainable urban development.