Understanding the spatial distribution of land surface temperature (LST) and its impact factors is crucial for mitigating urban heat island effect. However, few studies have quantitatively investigated the spatial non-stationarity and spatial scale effects of the relationships between LST and its impact factors at multi-scales. The main purposes of this study are as follows: (1) to estimate the spatial distributions of urban heat island (UHI) intensity by using hot spots analysis and (2) to explore the spatial non-stationarity and scale effects of the relationships between LST and related impact factors at multiple resolutions (30–1200 m) and to find appropriate scales for illuminating the relationships in a plain city. Based on the LST retrieved from Landsat 8 OLI/TIRS images, the Geographically-Weighted Regression (GWR) model is used to explore the scale effects of the relationships in Zhengzhou City between LST and six driving indicators: The Fractional Vegetation Cover (FVC), the Impervious Surface (IS), the Population Density (PD), the Fossil-fuel CO₂ Emission data (FFCOE), the Shannon Diversity Index (SHDI) and the Perimeter-area Fractal Dimension (PAFRAC),which indicate the vegetation abundance, built-up, social-ecological variables and the diversity and shape complexity of land cover types. Our findings showed that the spatial patterns of LST show statistically significant hot spot zones in the center of the study area, partly extending to the western and southern industrial areas, indicating that the intensity of the urban heat island is significantly spatial clustering in Zhengzhou City. In addition, compared with the Ordinary Least Squares (OLS) model, the GWR model has a better ability to characterize spatial non-stationarity and analyze the relationships between the LST and its impact factors by considering the space-varying relationships of different variables, especially at the fine spatial scales (30–480 m). However, the strength of GWR model has become relatively weak with the increase of spatial scales (720–1200 m). This reveals that the GWR model is recommended to be applied in the analysis of UHI problems and related impact factors at scales finer than 480 m in the plain city. If the spatial scale is coarser than 720 m, both OLS and GWR models are suitable for illustrating the correct relationships between UHI effect and its influence factors in the plain city due to their undifferentiated performance. These findings can provide valuable information for urban planners and researchers to select appropriate models and spatial scales seeking to mitigate urban thermal environment effect.

Urban parks are an important part of urban ecosystems and play an important role in biodiversity conservation. However, it is still unclear how park characteristics affect plant diversity which could hinder the conservation of urban biodiversity due to the ineffective design of urban parks. The diversity of woody plants in 33 parks of Changchun, China, was measured with plot measurements and linked with urban park characteristics (e.g., size and age of the park) to uncover the relationship between them. The results show that urban woody plant species were abundant, with 98 species belonging to 51 genera and 26 families in the snow climate city of Changchun. The variation in woody plant diversity was largely explained by internal patch characteristics (e.g., size, age, shape), and external factors surrounding the park (e.g., land use type and socioeconomic level) accounted for only 16.0% in our study. For internal patch characteristics, older urban parks with larger areas demonstrated a richer level of plant diversity and increased nonlinearly with increasing park area. The threshold size significantly affecting plant diversity variation was approximately 30 ha. Plant diversity had positive linear relationships with the ages of urban parks, supporting the legacy effect. In addition, woody plant diversity nonlinearly decreased with increasing park shape index, which suggested that the plant diversity could also be increased by optimizing the park shape. Regarding the external factors surrounding parks, the spatial distribution of woody plant diversity varied greatly from the urban center to the suburbs. House prices around the park had positive linear relationships with woody plant diversity in parks, supporting the luxury effect. However, building and road proportions, and green space proportion had no relationship with plant diversity in parks. This study can provide a robust reference for enriching plant diversity in urban parks, thus improving the development of urban sustainable cities.