Search Results (7)

Urban blue–green space (UBGS) plays a critical role in mitigating the urban heat island (UHI) effect and reducing land surface temperatures (LSTs). However, existing research has not sufficiently explored the optimization of UBGS spatial configurations or their interactions with urban morphology. This study takes New York City as a case and systematically investigates small-scale urban cooling strategies by integrating multiple factors, including adjustments to the blue–green ratio, spatial layouts, vegetation composition, building density, building height, and layout typologies. We utilize multi-source geographic data, including LiDAR derived land cover, OpenStreetMap data, and building footprint data, together with LST data retrieved from Landsat imagery, to develop a prediction model based on generative adversarial networks (GANs). This model can rapidly generate visual LST predictions under various configuration scenarios. This study employs a combination of qualitative and quantitative metrics to evaluate the performance of different model stages, selecting the most accurate model as the final experimental framework. Furthermore, the experimental design strictly controls the study area and pixel allocation, combining manual and automated methods to ensure the comparability of different ratio configurations. The main findings indicate that a blue–green ratio of 3:7 maximizes cooling efficiency; a shrub-to-tree coverage ratio of 2:8 performs best, with tree-dominated configurations outperforming shrub-dominated ones; concentrated linear layouts achieve up to a 10.01% cooling effect; and taller buildings exhibit significantly stronger UBGS cooling performance, with super-tall areas achieving cooling effects approximately 31 percentage points higher than low-rise areas. Courtyard layouts enhance airflow and synergistic cooling effects, whereas compact designs limit the cooling potential of UBGS. This study proposes an innovative application of GANs to address a key research gap in the quantitative optimization of UBGS configurations and provides a methodological reference for sustainable microclimate planning at the neighborhood scale. Full article

Global ecosystems are facing challenges posed by warming and excessive carbon emissions. Urban areas significantly contribute to carbon emissions, highlighting the urgent need to improve their ability to sequester carbon. While prior studies have primarily examined the carbon sequestration benefits of single green or blue spaces, the combined impact of urban blue–green spaces (UBGSs) on carbon sequestration remains underexplored. Meanwhile, the rise of machine learning provides new possibilities for assessing this nonlinear relationship. We conducted a study in the Yangzhou urban area, collecting Landsat remote sensing data and net primary productivity (NPP) data at five-year intervals from 2001 to 2021. We applied the LightGBM-SHAP model to systematically analyze the correlation between UBGSs and NPP, extracting key landscape metrics. The results indicated that landscape metrics had varying impacts on NPP. At the patch and type level, the Percentage of Landscape was significantly positively correlated with NPP in green space, while the contiguity index and fractal dimension index favored carbon sequestration under certain conditions. The contribution of blue space was lower, with some indicators exhibiting negative correlations. At the landscape level, the contagion index and aggregation index of UBGS had positive effects on NPP, while the division index and landscape shape index were negatively correlated with NPP. The results enhance the understanding of the relationship between UBGS and carbon sequestration, and provide a reference for urban planning. Full article

Urban blue–green spaces (UBGSs) are a significant avenue for addressing the worldwide mental health crisis. To effectively optimise landscape design and management for the promotion of health benefits from UBGS, it is crucial to objectively understand public preferences. This paper proposes a method to evaluate public landscape preference from the perspective of seeing and thinking, takes the examples of seven parks around the Dianchi Lake in Kunming, China, and analyses the social media data by using natural language processing technology and image semantic segmentation technology. The conclusions are as follows: (1) The public exhibits significantly high positive sentiments towards various UBGSs, with over 93% of comments expressed positive sentiments. (2) Differences exist in the frequency and perception of landscape features between image and text modalities. Landscape elements related to stability are perceived more in images than in text, while dynamic and experiential elements are perceived more in text than in images. (3) In both modalities, the distinctive landscape features of parks are more frequently perceived and preferred by the public. In the end, the intrinsic links between landscape elements and public sentiment and preferences are discussed, and suggestions for design and management improvements are made to consolidate their health benefits to the public. Full article

Urban blue-green space (UBGS), where public life occurs, is vital for social interaction, social cohesion, public spirit cultivation, and community formation. UBGS publicness reflects whether it supports and facilitates community formation. From the perspective of the man–land relationship, UBGS with high publicness should have three significant characteristics: accessibility of elements, functional selectivity, and structural connectivity and shareability. This study took Changsha as the case study and evaluated its UBGS publicness in 2012, 2016, and 2020. We analyzed the evolution of the UBGS publicness pattern, and the results indicated the following: (1) The elements accessibility indicator showed a decreasing trend year by year and maintained the pattern of low in the city center and high in the suburban area; (2) the functional diversity indicator changed from a monocentric polarized spatial pattern to a polycentric and balanced spatial pattern; (3) the structural connectivity indicator generally improved and showed the core-edge pattern; and (4) the comprehensive indicator showed that the pattern developed from the core edge to the core edge as the primary focus with fan-shaped expansion supplemented. Based on this, combined with Changsha’s urban development history, environmental, policy, economic, and social factors supported, led, promoted, and guided the formation and evolution of the UBGS publicness pattern. This study improved the theoretical foundation of UBGS publicness, provided ideas and methods for the UBGS publicness evaluation on the urban scale, and may provide a reference for the construction of livable and sustainable cities. Full article

Urban high-temperature disasters have gradually emerged as a significant threat to human society. Therefore, it is crucial to assess and identify areas at risk of such disasters and implement urban planning measures aimed at mitigating their impact. Additionally, a multitude of studies have demonstrated the significant cooling effect of urban blue-green spaces (UGBS), which play a pivotal role in urban environments. Incorporating a UBGS layout into planning and evaluation processes has substantial potential for mitigating high-temperature disasters. This paper presents the construction of a set of assessment processes for mitigating urban high-temperature disaster risk using a UBGS structure layout specifically for the main urban area of Harbin, China. We employed GIS and multi-source remote sensing imagery to develop local climate zone (LCZ) maps applicable to the designated study area. The differentiated impact of UBGS factors on high-temperature disaster risk was determined using the multi-scale geographical weighted regression model (MGWR). The results showed the following: (a) There was an overall low risk level, with 19.61% of the high-risk areas concentrated within the second ring road, forming a spatial pattern characterized by “one line, one cluster”. (b) The risk of the building category LCZs was generally higher than that of the natural category LCZs. The risk of the architectural LCZs could be summarized as the risk of low-density LCZs being smaller than that of the high-density LCZs, except LCZ 5. The mean value of the LCZ 2 and LCZ 5 types was the highest. (c) Through indicator screening, AREA_MN, SHAPE_MN, PD, and NP were found to be significant determinants influencing the risk, and the effectiveness and spatial differentiation of these main factors exhibited notable disparities. (d) By comparing different LCZ types, we concluded that the mitigation effect of these factors on risk may be interfered with by building height (BH); NP may be positively interfered with by BH; and PD and SHAPE_MN may be negatively interfered with by BH. The research results provided a new perspective and practical scientific basis for high-temperature disaster risk-mitigation planning based on UBGSs under LCZ classification. Full article

Urban blue-green space (UBGS), as an important component of the urban environment, is found to closely relate to human health. An extensive understanding of the effects of UBGS on human health is necessary for urban planning and intervention schemes towards healthy city development. However, a comprehensive review and discussion of relevant studies using bibliometric methods is still lacking. This paper adopted the bibliometric method and knowledge graph visualization technology to analyze the research on the impact of UBGS on residents’ health, including the number of published papers, international influence, and network characteristics of keyword hotspots. The key findings include: (1) The number of articles published between 2001 and 2021 shows an increasing trend. Among the articles collected from WoS and CNKI, 38.74% and 32.65% of the articles focus on physical health, 38.32% and 30.61% on mental health, and 17.06% and 30.61% on public health, respectively. (2) From the analysis of international partnerships, countries with high levels of economic development and urbanization have closer cooperation than other countries. (3) UBGS has proven positive effects on residents’ physical, mental, and public health. However, the mediating effects of UBGS on health and the differences in the health effects of UBGS on different ages and social classes are less studied. Therefore, this study proposes several future research directions. First, the mediating effect of UBGS on health impacts should be further examined. Furthermore, the interactive effects of residents’ behaviors and the UBGS environment should be emphasized. Moreover, multidisciplinary integration should be strengthened. The coupling mechanism between human behavior and the environment should also be studied in depth with the help of social perception big data, wearable devices, and human–computer interactive simulation. Finally, this study calls for developing health risk monitoring and early warning systems, and integrating health impact assessment into urban planning, so as to improve residents’ health and urban sustainability. Full article

The two most common land cover types in urban areas, artificial surface (AS) and urban blue-green space (UBGS), interact with land surface temperature (LST) and exhibit competitive effects, namely, heating and cooling effects. Understanding the variation of these effects along the AS ratio gradient is highly important for the healthy development of cities. In this study, we aimed to find the critical point of the joint competitive effects of UBGS and AS on LST, and to explore the variability in different climate zones and cities at different development levels. An urban land cover map and LST distribution map were produced using Sentinel-2 images and Landsat-8 LST data, respectively, covering 28 major cities in China. On this basis, the characteristics of water, vegetation, and LST in these cities were analyzed. Moreover, the UBGS (water or vegetation)–AS–LST relationship of each city was quantitatively explored. The results showed that UBGS and AS have a competitive relationship and jointly affect LST; this competition has a critical point (threshold). When the proportion of UBGS exceeds this value, UBGS replaces AS as the dominant variable for LST, bringing about a cooling effect. In contrast, when AS dominates LST, it causes a warming effect. The critical points between AS and water and between AS and vegetation in 28 major cities in China were 80% and 70%, respectively. The critical point showed an obvious zonal difference. Compared with cities in subtropical and temperate climate regions, the critical point of arid cities is higher, and UBGS exhibited better performance at alleviating the urban thermal environment. The critical point of cities with higher development levels is lower than that of cities with lower development levels. Even areas with relatively low AS coverage are prone to high temperatures, and more attention should be paid to improving the coverage of UBGS. Our research results provide a reference for the more reasonable handling of the relationship between urban construction, landscape layout, and temperature control. Full article