Abstract Urban parks can effectively reduce surface temperatures, which is an important strategic approach to reducing the urban heat island effect. Quantifying the cooling effect of urban parks and identifying their main internal influencing factors is important for improving the urban thermal environment, achieving maximum cooling benefits, and improving urban sustainability. In this study, we extracted data frobut this is often unrealisticm 28 urban parks in Zhengzhou, China. We combined multivariate data, such as Landsat 8 data, to retrieve the land surface temperature (LST), extract the park interior landscape, and quantify the cooling effect using three cooling indices: park cooling distance ( L ∆max ), temperature difference magnitude (∆ T max ), and temperature gradient ( G temp ). Furthermore, the relationship between the internal landscape characteristics of the park and the average LST and cooling indices of the park was analyzed. The results showed that different buffer ranges affect the LST-distance fitting results of urban parks, and a 300-m buffer zone is the optimal fitting interval. However, specific parks should be analyzed to select the optimal buffer range and reduce the cooling index calculation errors. Additionally, the mean values of LST, ∆ T max , L ∆max , and G temp for the 28 parks in Zhengzhou were 34.11, 3.22 °C, 194.02 m, and 1.78 °C/hm, respectively. Park perimeter (PP), park area, internal green area (GA), and landscape shape index (LSI) were both significantly correlated with ∆ T max and the main factors associated with maintaining a low LST in parks. L ∆ max was mainly affected by the GA, LSI, and perimeter-area ratio, whereas G temp was positively correlated with PP. Finally, the threshold value of efficiency for parks in Zhengzhou was 0.83 ha, and comprehensive parks showed optimal cooling in every aspect. 

Cooling island effect in urban parks from the perspective of internal park landscape

The frequency and intensity of extreme heat events have been increasing due to the combined effects of global climate change and urbanization. Urban green infrastructure, including urban green and blue space, has been recognized as an effective measure to mitigate urban heat. However, the effects of green infrastructure on heat health risk were insufficiently addressed. To address this gap, we conducted a comprehensive assessment in the megacity of Beijing with a rapidly aging population. Various data sources were collected, including remote sensing images, meteorological data from weather stations, point of interest(POI) data, and social statistics. Following the risk triangle theory, the hazard, population exposure, and social vulnerability components of heat health risk were evaluated at the census tract level. The weights of vulnerability indicators were determined using Principal Component Analysis. Moran's I and Getis-Ord Gi* statistics were used to identify risk hotspot areas. To evaluate the effects of green infrastructure on heat health risk, a Green Infrastructure Index (GII) was created to quantitatively measure the abundance and accessibility of green infrastructure. The analysis, using a spatially-explicit Heat Health Risk Index (HHRI), indicated that the HHRI in the central urban area inhabited by high-income population groups is 2.66 times that of its suburban counterpart. The primary driving factors of heat health risk were identified as high population density and elevated temperatures. Census tracts with abundant green infrastructure exhibited a low likelihood of becoming high-risk areas, with a probability of less than 2%, while regions with limited green infrastructure had a 54.26% probability of becoming high-risk areas. This highlights the significance of expanding the coverage of green spaces and water areas to reduce heat health risk. The findings provide valuable insights for the development of risk mitigation measures enhancing urban thermal resilience through nature-based climate adaptation. 

Understanding fine-scale heat health risks and the role of green infrastructure based on remote sensing and socioeconomic data in the megacity of Beijing, China

Urban blue-green space (UBGS) has been extensively investigated for its climate regulation capability in the context of climate change. However, current efforts are limited toward the cooling effects mismatch in supply and demand of UBGS. This study adapts the framework of ecosystem supply and demand to quantify the supply-demand matching of the cooling effects of UBGS. Two indices were proposed to evaluate cooling provision and demand of UBGS: Cooling Supply Index (CSI), accounting for cooling contribution and spatial effect, and Cooling Demand Index (CDI), considering physical and social dimensions of cooling demand. Four-quadrant analysis and bivariate local indicators of spatial autocorrelation (BiLISA) analysis were employed to distinguish the supply-demand matching status: high supply with high demand, low supply with high demand, low supply with low demand, and high supply with low demand. The results show that 1) CSI and CDI yield great performance in quantifying cooling supply and demand, respectively; 2) the four-quadrant analysis and bivariate LISA analysis are complementary to each other, and can target those areas in different matching statuses for climate-sensitive planning and design; and 3) particular attention should be given to areas characterized by low supply with high demand. This study marks a crucial step toward integrating social aspects into the analysis of cooling effects provided by UBGS. It enriches the analysis framework for urban ecosystem services and provides valuable guidance for landscape planning to mitigate heat stress. 

Matching Supply and Demand of Cooling Service Provided by Urban Green and Blue Space

Urban parks have been considered as an environmental mitigation strategy for heat island effect, but the spatial contribution of influencing factors affecting Park Cooling Intensity (PCI) is still uncertain. In this study, we selected 814 urban parks in Zhejiang Province, China to locate the key factors and their specific relative importance on the park scale by using the combination of eXtreme Gradient Boosting tree (XGBoost) and Shapley Additive exPlanations algorithm (SHAP). The results are as follows: (1) Most parks in the province had a cooling effect with an average PCI of 1.98°C. (2) Park area was the most important factor for PCI globally, followed by the patch density inside the park, but the water-derived factors except park inner waters were not at the forefront. (3) The significance of the water-related features (BUFwidth, waterLPI etc.) were remarkable for riverine parks indicated by heuristic local SHAP values. This study demonstrates that the interpretable algorithm combined with machine learning method is helpful to reveal the spatially explicit contribution of key factors for urban parks at a finer scale for more scientific management. 

Spatialized importance of key factors affecting park cooling intensity based on the park scale

Anthropogenic warming and rapid urbanization have exacerbated the deterioration of urban thermal environments, increasing interest in the ability of parks to regulate local climates. However, their potential to mitigate local thermal discomfort and spatial mismatch in supply and demand is poorly understood. We 1) examined the cooling effects of Shanghai's parks via a thermal comfort index, 2) identified the role of parks in improving local thermal environments by comparing thermal discomfort and park cooling capacity, and 3) explored the spatial mismatch between the demand for thermal discomfort mitigation and the supply of park cooling based on multiple park accessibility. The extent of park cooling is inversely related to the level of urbanization, while cooling intensity is positively associated with urbanization. Only 20.65% of the parks effectively mitigate local thermal discomfort, highlighting the need for improvements. Cooling accessibility increases from the city center to the periphery, with 22.70% of areas lacking access to park cooling services within a 15-min radius. Further improvements can enhance the thermal comfort of accessible parks by 49.55%. Priority adaptation is required in old urban areas and key development zones in peripheral urban areas to meet the needs of their large populations. Our study contributes to the study of urban thermal discomfort mitigation via parks in the context of climate adaptation planning. 

Parks may not be effective enough to improve the thermal environment in Shanghai (China) as our modified H3SFCA method suggests

With increasing global warming and urbanization, extreme heat events threaten the health of urban dwellers. Urban parks can alleviate severe urban heating, but previous research on park cooling effect has largely involved single-dimension analysis and lacked a multi-dimensional perspective that explores the equity of park cooling services. To address the issue, this study proposes a comprehensive framework of cooling effect–accessibility–urban development for assessing and planning 113 urban parks in Nanjing, China. The results show an unequal distribution of the park cooling services index (PCSI), which decreases outward from the city center to surrounding areas, with an average PCSI within the ring road 1.34 times higher than outside. The value of the cooling effect was relatively low, with the two lowest levels accounting for 65.5%, and the parks with low values of accessibility and urban development were concentrated outside the ring road. Additionally, increasing the park area, Normalized difference vegetation index of vegetated area, and blue-green proportion could effectively enhance the cooling effect. Four park cooling service types were identified according to supply-demand, as well as intervention strategies and adaptive planning measures were developed. This study constructed a new comprehensive framework for park cooling services to improve equity and promote urban parks. 

A comprehensive framework of cooling effect-accessibility-urban development to assessing and planning park cooling services

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Trends in Research about COVID-19 Vaccine Documented through Bibliometric and Visualization Analysis

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A comprehensive framework of cooling effect-accessibility-urban development to assessing and planning park cooling services

Trends in Research about COVID-19 Vaccine Documented through Bibliometric and Visualization Analysis