In the context of urban warming associated with rapid urbanization, the relationship between urban landscape patterns and land surface temperature (LST) has been paid much attention. However, few studies have comprehensively explored the effects of two/three-dimensional (2D/3D) building patterns on LST, particularly by comparing their relative contribution to the spatial variety of LST. This study adopted the ordinary least squares regression, spatial autoregression and variance partitioning methods to investigate the relationship between 2D/3D building patterns and summertime LST across 2016–2017 in Shanghai. The 2D and 3D building patterns in this study were quantified by four 2D and six 3D metrics. The results showed that: (1) During the daytime, 2D/3D building metrics had significant correlation with LST. However, 3D building patterns played a significant role in predicting LST. They explained 51.0% and 10.2% of the variance in LST, respectively. (2) The building coverage ratio, building density, mean building projection area, the standard deviation of building height, and mean building height highly correlated with LST. Specifically, the building coverage ratio was the main predictor, which was obviously positively correlated with LST. The correlation of building density and average projected area with LST was positive and significant, while the correlation of building height standard deviation and average building height with LST was negative. The increase in average height and standard deviation of buildings and the decrease in building coverage ratio, average projected area, and density of buildings, can effectively improve the urban thermal environment at the census tract level. (3) Spatial autocorrelation analysis can elaborate the spatial relationship between building patterns and LST. The findings from our research will provide important insights for urban planners and decision makers to mitigate urban heat island problems through urban planning and building design.

The urban heat island (UHI) effect has a serious negative impact on urban ecosystems and human well-being. Mitigating UHI through nature-based methods is highly recommended. The cooling effect of urban blue infrastructure (UBI) can significantly alleviate the effects of UHI. Revealing the crucial influencing factors of the cooling effect of UBI is of great significance for mitigating the UHI effect. In this study, the water-cooling intensity (WCI) and water-cooling range (WCR) were used to quantitatively analyze the cooling effect of UBI in Hefei city in summer. Furthermore, the influencing factors and their interactions with the cooling effect of UBI were investigated based on the Geodetector model. The results revealed that: (1) The surface thermal environment of the built-up area of Hefei presented obvious spatial differentiation characteristics. (2) There were nine influencing factors that significantly influenced the WCI variation, with the greatest influencing factor of road density. In contrast, only the landscape shape index had a significant effect on WCR variation. (3) The interaction of environmental characteristics, water body characteristics, and socioeconomic characteristics had a significant influence on the cooling effect of UBI, and the interaction relationship between the influencing factors was mutually enhanced. The findings from our research can provide a theoretical reference and practical guidance for the protection, restoration, and planning of UBI as a nature-based solution to improve the urban thermal environment.

In this study, a retrospective analysis of the relationship between the land use/land cover (LULC) change and associated surface urban heat island (SUHI) effect in fast-growing Greater Hefei between 1995 and 2016 was performed. Our results reveal the heterogeneous patterns of LULC change. The concentric buffer-based urban–rural gradient analysis reveals that most of the newly emerging developed land occurred within downtown Hefei. In contrast, in three suburban municipality/county jurisdictions, the overall area change in the non-developed land was much lower, but the net increase in developed land is remarkable. Meanwhile, the spatiotemporal patterns of SUHI are in good agreement with that of the developed land, as evidenced by the notable increase in SUHI intensity (SUHII) levels and SUHI spatial extent (SUHISE) in response to the rapid urban expansion, particularly along transportation corridors. In addition, partial least square regression (PLSR) models indicate that the buffer-based predictors/independent variables are significantly related to the responses (SUHII and SUHISE), explaining approximately 61.3% of the variance in the SUHII and 79.8% of the variance in the SUHISE, respectively. Furthermore, the relative strength of the independent variables in determining the relationship was quantitatively examined. The findings of this study provide clear evidence for decision making for sustainable land development and mitigation of the SUHI effect.

With the continuous development of urbanization, the urban heat island (UHI) phenomenon is becoming increasingly prominent. Especially with the development of various large urban agglomerations and the shrinking distance between cities, the regional thermal environment has attracted extensive attention. Therefore, we used Modis land surface temperature (LST) data and employed least squares, standard deviation and spatial autocorrelation analysis methods to analyze the spatiotemporal patterns and characteristics of summer daytime regional urban heat islands (RHI) in the Beijing–Tianjin–Hebei (BTH) urban agglomeration. Our results indicated that the relative land surface temperature (RLST) in the southeastern part of BTH with a relatively high level of urbanization showed a significant and continuous upward trend. With the continuous development of the level of urbanization in the southeast, the center of gravity (GC) of RHI gradually moved to the southeast, and the development direction of RHI changed from northwest–southeast to northeast–southwest. The area transfer of RHI was concentrated in no change and little change, indicating that the evolution trend of RHI was relatively stable. The high-high aggregation areas were mainly located in the more developed areas in the southeast. In addition, the methods and results of this study can provide reasonable and effective insights into the future development and planning of the BTH.

Suitability evaluation of urban construction land is critical for both urban master planning and the proper utilization of land resources. Using the Beihu New District of Jining City, China, as a case study, this paper introduces a novel research approach for comprehensive suitability evaluation based on vertical-horizontal processes. First, by considering both the land development potential and ecological constraint resistance, the potential-resistance (PR) model was developed and used to analyze the suitability for urban construction of vertical processes. Then, given the results of the vertical suitability analysis, the current urban built-up areas were selected as the sources of urban expansion, and the minimum cumulative resistance (MCR) model was applied to evaluate the suitability for urban development in terms of horizontal processes. The study area was regionalized into four categories—priority, suitable, restricted, and prohibited areas—which were defined based on the development threshold. The results showed that restricted and prohibited areas for urban construction occupied most of the study area. Totally, 648.51 km² was categorized as restricted or prohibited, accounting for 12.89% and 54.75% of the total area, respectively. Priority and suitable areas for urban construction covered a total area of 310.37 km², accounting for 16.55% and 15.81% of the total area, respectively. These areas were mainly distributed around urban centers and urban built-up areas. These findings reflect the substantial potential for future urban development and construction in the study area. The newly developed principles and methods of suitability evaluation for urban construction land presented in this paper provide more appropriate scales and spatial location for urban development and an ecological baseline for future urban growth.

Context: Against the backdrop of global climate change and enhanced human activities, heatwave issues occur frequently, and lead to increasing population heatwave exposure (PHE) risk. Although early studies have suggested that blue-green spaces (BGS) may mitigate PHE by regulating the surface thermal environment, few researches have investigated the comprehensive effect of various types of BGS on PHE from climate zone perspective, especially at the fine scale. Objectives: This study attempted to investigate the comprehensive impacts of various BGS on PHE from the perspective of climate zones to provide more targeted decision support for PHE mitigation. Methods: Taking China as the study area, this study quantified the relationship between various BGS and PHE across different climate zones, combined with gradient boosting regression tree (GBRT) model, shapley additive explanation (SHAP), and variance partitioning analysis (VPA). Results: HAW (hot summer and warm winter) and HAC (hot summer and cold winter) climate zones had obviously higher probability of heatwaves than the other climate zones, and their PHE was very severe. BGS had a strong explanatory power for PHE variation in all climate zones. The joint explanatory power of various types of BGS for PHE was basically greater than their independent explanatory power. With the increase of latitude, the independent explanatory power of forest decreased, while that of grassland increased. The dominant factors influencing PHE varied with climate zones, but percentage of landscape, landscape shape and landscape connectivity of various BGS played more important roles in regulating PHE. Conclusions: The effects of BGS landscape pattern on population heatwave exposure varied across different climate zones. Our findings can provide new and more targeted insights and decision-making guidance for government policymakers and planners in different climate zones, regarding he formulation of pattern optimization strategies and planning management policies of BGS, in order to effectively mitigate the population exposure to heatwaves.