Several heat records have been broken in recent years and decades. Extreme high temperature not only damages human health, but also increases the risk of wildfires. As a common urban infrastructure, urban green space has been proved to have a cooling effect. In this study, the physical indicators and temperature data of 36 green spaces in Xi'an were collected, and the influence of different physical indicators of green spaces on their thermal environment was explored through correlation analysis. The results suggest that the area of green space should be between 0.6-0.7 square kilometers or the perimeter should range from 4000 to 4500 m in order to obtain the lowest internal temperature. When the area of water body in the green space is between 0.3-0.4 square kilometers or the perimeter is about 5000 m, its internal temperature is the lowest. Indicators of green space in the conclusion can be directly understood and referred by urban planners and policy makers. Results of this study thus have implications for improving urban thermal comfort by controlling the physical indicators of green space.

The Local Climate Zone (LCZ), as a foundational element of urban climate zone classification proposed by Oke and Stewart, categorizes urban surface types based on 10 influential parameters affecting the urban heat island effect, such as building density, surface reflectivity, sky view factor, and surface roughness length. This method divides cities into 17 different Local Climate Zones (LCZs) to standardize climate observations and promote global climate research exchange, offering valuable insights for heat island studies. In this study, we enhance the existing local climate zones spatial classification approach by focusing on Xi’an city’s urban layout and architectural features. By using urban spatial indicators and employing a supervised classification approach and a spatial clustering method with land parcels as statistical units, we investigate typical urban areas and classify Xi’an’s land parcels into 17 or 15 distinct local climate zones. Subsequently, through the evaluation of two distinct classification methods, the most suitable urban microclimate zoning method for Xi’an city was selected. This optimization of the local climate zoning representation introduces a spatial classification method tailored to urban climate planning and control, utilizing urban spatial indicators and remote sensing data. The resulting urban climate zoning map not only supports sample selection for urban heat environment parameter observation but also aids urban planners in identifying spatial distribution patterns for climate zoning.

Research on the correlation between wind and block spatial form focuses mainly on hot and humid cities. However, cold regions are also experiencing high summer temperatures due to global climate change. Enhancing wind speed in blocks through urban spatial control improves comfort. Existing research cannot be directly applied to cold regions due to natural differences. Using Xi’an as an example, this study explores the impact of high-rise residential block spatial form on internal and external wind environments through field measurements and simulations. Optimal strategies for block planning and architectural design are identified to improve the wind environment. Results show that blocks with high buildings on the south and north sides and low buildings in the middle achieve a more comfortable internal wind environment. Gradually increasing building height from south to north has minimal impact on downwind blocks. Reducing the angle between the main facade and dominant wind direction enhances the residential area’s wind environment. Specific spatial planning and design strategies are summarized for early-stage decision-making.