Urbanization alters the relative importance of local and landscape factors affecting plant communities in the Tokyo megacity.

Plant communities are impacted by local factors (related to environmental filtering) and landscape factors (related to dispersal limitation). While many studies have shown that the relative importance of these factors in understanding plant community dynamics due to urbanization, little is known about how they are altered by urbanization-a significant threat to biodiversity. This study evaluates the relative importance of local environmental (local factors), landscape, and spatial (landscape factors) variables that influence plant communities in 34 urban green spaces comprising two different habitats (forests and grasslands) along the urban-rural gradients in the Tokyo megacity, Japan. To continuously assess the relative importance of each factor along the urban-rural gradients, we extracted 1000 landscapes within a certain range that contained several sites. Subsequently, the relative importance of each factor and urbanization rate (proportion of artificial built-up area) were estimated for each landscape. Our study found that the relative importance of both local and landscape factors decreased, while that of local factor for native species in forest habitats and that of landscape factors for native species in grassland habitats increased. Collectively, these findings suggest that city size and habitat characteristics must be considered when predicting changes in plant communities caused by urbanization.

Utilizing regression model to characterize the impact of urban green space features on the subjective well-being of older adults.

Based on the background of rapid global ageing, research exploring urban green spaces and the subjective well-being of urban residents has become one of the key research interests. However, the evidence for assessing the real benefits of urban green spaces on the subjective well-being of older adults by comprehensively examining the features of urban green spaces is limited. We surveyed older urban green space users (n = 536) aged 60 years and older in Nanjing, China, and evaluated the impacts of spatial, green, and grey features of urban green spaces on older people's overall satisfaction with urban green spaces and subjective well-being. The results of the multiple linear regression model showed a strong association between the three types of urban green space features, overall satisfaction with urban green space, and subjective well-being of older adults. The study results indicated that the grey feature of urban green spaces emerged as the most influential factor (p = 0.004) among the three features of urban green spaces in relation to their effect on the subjective well-being of older adults. This implies that it is essential to focus on the importance of grey s of urban green spaces in the planning and design of urban green spaces for older adults' use of different urban green spaces and their sense of well-being. These results contribute to the development of healthy ageing policies and age-friendly urban green space management strategies in rapid ageing countries around the world.

Assessing allergy risk from ornamental trees in a city: Integrating open access remote sensing data with pollen measurements.

Platanus sp. pl. (plane trees) are common ornamental tree in Poland that produces a large amount of wind-transported pollen, which contains proteins that induce allergy symptoms. Allergy sufferers can limit their contact with pollen by avoiding places with high pollen concentrations, which are restricted mainly to areas close to plane trees. Their location is thus important, but creating a detailed street tree inventory is expensive and time-consuming. However, high-resolution remote sensing data provide an opportunity to detect the location of specific plants. But acquiring high-resolution spatial data of good quality also incurs costs and requires regular updates. Therefore, this study explored the potential of using open access remote sensing data to detect plane trees in the highly urbanized environment of Poznan (western Poland). Airborne light detection and ranging (LiDAR) was used to detect training treetops, which were subsequently marked as young plane trees, mature plane trees, other trees or artefacts. Spectral and spatial variables were extracted from circular buffers (r = 1 m) around the treetops to minimize the influence of shadows and crown overlap. A random forest machine learning algorithm was applied to assess the importance of variables and classify the treetops within a radius of 6.2 km around the functioning pollen monitoring station. The model performed well during 10-fold cross-validation (overall accuracy ≈ 92%). The predicted Platanus sp. pl. locations, aggregated according to 16 wind directions, were significantly correlated with the hourly pollen concentrations. Based on the correlation values, we established a threshold of prediction confidence, which allowed us to reduce the fraction of false-positive predictions. We proposed the spatially continuous index of airborne pollen exposure probability, which can be useful for allergy sufferers. The results showed that open-access geodata in Poland can be applied to recognize major local sources of plane pollen.

Enhancing the city-level thermal environment through the strategic utilization of urban green spaces employing geospatial techniques.

Smart urban planning needs to have a multicriteria-based approach to prevent the deteriorating local thermal climate. Maximizing the cooling potential using the available grey infrastructure would be the utmost priority of future smart cities. Remote sensing and GIS can be the appropriate tools to develop a climate-resilient urban planning framework. Studies are needed to include different features of vertical and horizontal landscaping to mitigate heat stress and enhance liveability at the city level. With this goal, the current work outlined a holistic approach to efficiently using green spaces with minimal reconstruction. The problem of regional climate threat was evaluated with urban heat island characterization. Moran's I clustering identified nearly 12% of the study area to be under considerable heat stress during summer days. Multiple techniques, such as mapping local climate zones, segment mean shift-based roof extraction, vegetation index computation, solar azimuth-based green wall site selection, etc., were applied to formulate solutions and provide an integrated method for city-level environment enhancement. A considerable area was identified as most suitable for green roof cover, and it was also computed that the transition towards green roof at only these locations may bring down the maximum heat island intensity by 0.74 °C. Additionally, solar zenith, illumination effect, and building height information were combined to create a distinct method where vertical plantation would flourish exceptionally. A rigorous assessment of more than 130 urban green spaces further quantified the relation between landscape geometry and cooling effect to provide optimum green space designs for future urban planning.

Residual distribution and risk assessment of neonicotinoids in urban green space soils of the pearl river delta, South China: A socioeconomic analysis.

Urban green spaces are the soil component in cities that interacts most closely with humans. This study investigated the residues of seven neonicotinoids (NEOs) in soils from urban green spaces within the Pearl River Delta (PRD) region and analyzed the correlation between the residue characteristics and the region's economic development. Notably, we introduced the Nemerow Index method, a comprehensive approach, to quantify the overall pollution level of NEOs in the soil of urban park green spaces and utilized this to assess the cumulative exposure probability risks for different populations in this scenario. We found that: (1) The soil of urban park green spaces exhibited varying degrees of NEOs contamination (Σ7NEOs: N.D.-137.31; 6.25 µg/kg), with imidacloprid and clothianidin constituting the highest proportions (89.46 % and 83.60 %); (2) The residual levels of NEOs in Children's Park were significantly higher than those in community parks within Guangzhou, with an average value of 13.30 µg/kg compared to 3.30 µg/kg; (3) The residual characteristics of NEOs exhibited a positive correlation with regional economic development; specifically, the per capita GDP well correlated with IMIRPF, a summation of seven NEOs in imidacloprid equivalents via relative potency factors (R2 =0.86). Regions with higher economic development typically exhibited elevated IMIRPF levels; (4) The fitted cumulative probability distributions for average daily exposure doses revealed that children's exposure was an order of magnitude higher than adults'. Despite this, the exposure risks for both groups remained within acceptable limits.

Urban greenspace types and climate factors jointly drive the microbial community structure and co-occurrence network.

The benefits of urban green space are socially widely recognized as a direct link between plant-microbe interactions and the maintenance of biodiversity, community stability, and ecosystem functioning. Nevertheless, there is a lack of knowledge about the factors influencing microbial communities in urban green spaces, especially those related to phyllosphere epiphytes and stem epiphytes. In this study, we analyzed the microbial community assembly in leaf and stem bark samples collected from Square, Road, Campus, and Park. Illumina sequecing of 16S amplicons was performed to characterize microbial diversity and composition. The α-diversity was significantly higher in the bark epiphytic community, compared to the phyllosphere. Moreover, urban greenspaces'type altered the way communities gathered. The main soil and air properties factors of the urban greenhouse (e.g. soil temperature, atmospheric moisture, air temperature) were shaping the characteristics of bacterial communities on the leaf surface and bark epiphytic. In addition, in the co-occurrence network analysis, keystone taxa were not mostly observed in abundant species, which may be necessary to maintain ecosystem functions. Finally, our findings provide a deeper understanding of the ecological dynamics and microbial interactions within plant phyllosphere and stem epiphytes microbiomes.

The Dynamic Relationship between Social Cohesion and Urban Green Space in Diverse Communities: Opportunities and Challenges to Public Health.

Social cohesion is a key factor within social determinants of health and well-being. Urban green spaces can provide environments that potentially facilitate meaningful and positive social interactions that promote social cohesion, equity, human health, and well-being. However, the lack of integration of existing research on social cohesion, urban green spaces, and public health in diverse (e.g., racially and ethnically) communities limits culturally relevant strategies to address health disparities. In this manuscript, we synthesize research on the potential of urban green spaces to promote social cohesion and public health in historically excluded communities. Particularly, we explore the development of social cohesion as it relates to the social environment, built environment, leisure opportunities, green space maintenance, safety, and green gentrification. We highlight key factors and their application to meet opportunities and challenges to social and public health. A conceptual framework is presented to provide an overview and illustrate connections found in the literature.

[Application of LA-UNet network model in remote sensing classification of urban green space]. / LA-UNet网络模型在城市绿地遥感分类中的应用.

The accurate identification and monitoring of urban green space is of great significance in urban planning and ecological management. In view of the complex background of urban green space, the traditional remote sensing classification technology is prone to the problem of misalignment and adhesion. Taking Yuhua District of Changsha City as the research area and Gaofen-2 (GF-2) remote sensing image as the data source, we proposed a remote sensing classification method for urban green space based on the LA-UNet model, which was based on the UNet model. We introduced the DWTCA channel attention mechanism module to improve the attention of the network to green space information, and used the CARAFE module to up sample the extracted features to achieve accurate classification of trees, shrubs and other land types in the complex background of the city. The results showed that the LA-UNet model had the best classification effect of urban green space when using standard false color remote sensing images. The overall accuracy and mean intersection over union were 96.3% and 90.9%, which were 2.8% and 6.1% higher than the UNet model, respectively. In the Potsdam public dataset, the overall accuracy and mean intersection over union of the LA-UNet model were also better than those of the UNet model, which increased by 0.9% and 1.8%, respectively, indicating that the LA-UNet model had good robustness and versatility. In summary, the proposed LA-UNet model could effectively alleviate the problems of misalignment and adhesion of urban green space, with advantages in the remote sensing classification of urban green space. The improved LA-UNet model had a smaller parameter volume than the UNet model, which could effectively improve the classification accuracy of urban green space. This study would provide a methodological reference for the accurate classification and understanding the spatial distribution of urban green space.

Integrating subjective feelings into the evaluation of ecological restoration outcomes of urban green space: Indicator framework from bibliometrics analysis and evidence synthesis.

Despite much progress has been made in the evaluation of ecological restoration outcomes, there is still a lack of a suitable framework for evaluating the ecological restoration outcomes of urban green space. In view of this, this study systematically analyzed the characteristics and differences between the evaluation index systems of ecological restoration outcome and urban green space quality evaluation, and then discussed the relationship between objective elements of landscape and people's subjective feelings. On this basis, an ecological restoration outcome evaluation framework was developed for urban green space considering people's subjective feelings. It was found that the existing studies of ecological restoration outcome evaluation mainly focused on the change of ecological components and structure, while urban green space environmental quality evaluation on the cultural services. Common ecological components and structure and people's subjective feelings were not all synergy or trade-off relations, in fact, there were still cases of trade-off and synergy relations co-existing. Therefore, a framework was constructed for evaluating the ecological restoration outcome of urban green space, including ecological components and structure, ecological services, social services, and people's subjective feelings.

A Review on Recent Deep Learning-Based Semantic Segmentation for Urban Greenness Measurement.

Accurate urban green space (UGS) measurement has become crucial for landscape analysis. This paper reviews the recent technological breakthroughs in deep learning (DL)-based semantic segmentation, emphasizing efficient landscape analysis, and integrating greenness measurements. It explores quantitative greenness measures applied through semantic segmentation, categorized into the plan view- and the perspective view-based methods, like the Land Class Classification (LCC) with green objects and the Green View Index (GVI) based on street photographs. This review navigates from traditional to modern DL-based semantic segmentation models, illuminating the evolution of the urban greenness measures and segmentation tasks for advanced landscape analysis. It also presents the typical performance metrics and explores public datasets for constructing these measures. The results show that accurate (semantic) segmentation is inevitable not only for fine-grained greenness measures but also for the qualitative evaluation of landscape analyses for planning amidst the incomplete explainability of the DL model. Also, the unsupervised domain adaptation (UDA) in aerial images is addressed to overcome the scale changes and lack of labeled data for fine-grained greenness measures. This review contributes to helping researchers understand the recent breakthroughs in DL-based segmentation technology for challenging topics in UGS research.

Distribution, source apportionment, and ecological risk assessment of soil antibiotic resistance genes in urban green spaces.

Urban green spaces play a crucial role in cities by providing near-natural environments that greatly impacts the health of residents. However, these green spaces have recently been scrutinized as potential reservoirs of antibiotic resistance genes (ARGs), posing significant ecological risks. Despite this concern, our understanding of the distribution, sources, and ecological risks associated with ARGs remains limited. In this study, we investigated the spatial distribution of soil ARGs using spatial interpolation and auto-correlation analysis. To apportion the source of soil ARGs in urban green spaces of Tianjin, Geo-detector method (GDM) was employed. Furthermore, we evaluated the ecological risk posed by ARGs employing risk quotients (RQ). The results of our study showed a significantly higher abundance of Quinolone resistance genes in the soil of urban green spaces in Tianjin. These genes were mainly found in the northwest, central, and eastern regions of the city. Our investigation identified three main factors contributing to the presence of soil ARGs: antibiotic production, precipitation, livestock breeding, and hospital. The results of ecological risk in RQ value showed a high risk associated with Quinolone resistance genes, followed by Aminoglycoside, Tetracycline, Multidrug, MLSB, Beta Lactam, Sulfonamide, and Chloramphenicol. Mantel-test and correlation analysis revealed that the ecological risk of ARGs was greatly influenced by soil properties and heavy metals. This study provides a new perspective on source apportionment and the ecological risk assessment of soil ARGs in urban green spaces.

Blood meal analysis reveals sources of tick-borne pathogens and differences in host utilization of juvenile Ixodes ricinus across urban and sylvatic habitats.

AIMS: Urban green spaces are locations of maximal human activity, forming areas of enhanced risk for tick-borne disease (TBD) transmission. Being also limited in spatial scale, green spaces form prime targets for control schemes aiming to reduce TBD risk. However, for effective control, the key species maintaining local tick and tick-borne pathogen (TBP) populations must be identified. To determine how patterns of host utilization vary spatially, we utilized blood meal analysis to study the contributions of voles, shrews, squirrels, leporids and cervids towards blood meals and the acquisition of TBPs of juvenile Ixodes ricinus in urban and sylvatic areas in Finland. METHODS AND RESULTS: A total of 1084 nymphs were collected from the capital city of Finland, Helsinki and from a sylvatic island in southwestern Finland, and subjected to qPCR analysis to identify DNA remnants of the previous host. We found significant differences in host contributions between urban and sylvatic environments. Specifically, squirrels and leporids were more common hosts in urban habitats, whereas cervids and voles were more common in sylvatic habitats. In addition to providing 18.4% of larval blood meals in urban habitats, red squirrels were identified as the source of 28.6% (n = 48) of Borrelia afzelii detections and 58.1% (n = 18) of Borrelia burgdorferi sensu stricto detections, indicating an important role for local enzootic cycles. CONCLUSIONS: Our study highlights that the key hosts maintaining tick and TBP populations may be different in urban and sylvatic habitats. Likewise, hosts generally perceived as important for upkeep may have limited importance in urban environments. Consequently, targeting control schemes based on off-site data of host importance may lead to suboptimal results.

Analysis and evaluation of the burning characteristics of six commonly used herbaceous species in Beijing.

Surface vegetations are one of the key factors affecting the spread of green space fires. To explore the combustibility of commonly used local surface layer herbaceous species in Beijing, and to provide a reference for the construction and management of urban green space, we comprehensively evaluated the combustibility of Carex giraldiana, Carex breviculis, Liriope spicata, Iris lactea, Iris tectorum, and Buffaloe dactyloides, with the entropy weight method and K-mean cluster analysis based on the principal component analysis method. We measured the combustion characteristics indicators (blade ignition point, combustion time and heat release rate), physical and chemical indicators (leaf moisture content and crude fat content), and biological characteristics indicators (blade thickness and unit load) during the key period of fire prevention. The results showed that blade thickness and ignition point got the highest weight and affected the overall combustibility most. Peak heat release rate and ignition time had the lowest weight and minimal impact on the overall combustibility. The combustibility of the six species followed an order of B. dactyloides > C. breviculmis > L. spicata > C. giraldiana > I. lactea > I. tectorum. Results of the clustering analysis showed that the combustion ability of B. dactyloides, C. breviculmis, and L. spicata were in class Ⅰ, with the strongest combustion ability; C. giraldiana was in class Ⅱ; I. lactea and I. tectorum were in class Ⅲ, with the lowest flammability. As widely used surface vegetations, critical attention should be paid on B. dactyloides, C. breviculmis and L. spicata for fire prevention in winter and spring.

Urban green space area mitigates the accumulation of heavy metals in urban soils.

Despite that the heavy metals in urban soils pose a threat to public health, the critical factors that influence their concentrations in urban soils are not well understood. In this study, we conducted a survey of surface soil samples from urban green spaces in Shanghai, to analyze the concentrations of the key heavy metals. The results showed that Zn was the most abundant metal with an average concentration of 122.99 mg kg-1, followed by Pb (32.72 mg kg-1) and Cd (0.23 mg kg-1). All concentrations were found to be below the risk screening values defined by the National Environmental Quality Standards for soils of development land in China (GB36600-2018), indicating no current risk in Shanghai. However, there was a clear accumulation of heavy metals, as the mean concentrations were significantly higher than the background values. Furthermore, we explored the relationships between key heavy metals with population density, GDP and green space area. Both Spearman correlation and Random Forest analysis indicated that per capita green space area (pGSA) and population density were the most crucial factors influencing the status of heavy metals in urban soils, unlike edaphic factors e.g. SOM content in farmland soils. Specifically, there was a significantly positive linear correlation between heavy metal concentrations and population density, with correlation coefficients ranging from 0.3 to 0.4. However, the correlation with pGSA was found to be non-linear. The nonlinear regression analysis revealed threshold values between heavy metals concentrations and pGSA (e.g Zn 22.22 m2, Pb 24.92 m2, and Cd 25.92 m2), with a sharp reduction in heavy metal concentrations below the threshold and a slow reduction above the threshold. It suggests that an increase in per capita green space area can mitigate the accumulation of heavy metals caused by growing population density, but the effect is limited after the threshold. Our findings not only provide insights into the distribution patterns of heavy metals in the urban soils at the local scale, but also contribute to the urban greening at the global scale and offer guidance for city planning in the face of increasing population densities over the coming decades.

How do urban green spaces influence heat-related mortality in elderly? A realist synthesis.

BACKGROUND: An important consequence of climate change for urban health is heat-related mortality. Vulnerable groups, especially elderly, will be the most affected. A solution put forward in many reports and policy documents is the introduction or expansion of urban green spaces. While they have a proven effect in decreasing the ambient temperature and reducing heat related mortality, the causal pathways are far from clear. Moreover, results vary for different contexts, population types and characteristics of green spaces as they are 'complex systems thrusted into complex systems'. To our knowledge, there is no systematic synthesis of the literature that examines the mechanisms by which and the circumstances under which green spaces work to decrease heat-related mortality for elderly. METHODS: We performed a realist synthesis- a theory-driven review method- to develop a complexity- and context-sensitive program theory. As a first step, a causal loop diagram was constructed which describes the possible pathways through which urban green spaces influence heat-related mortality in elderly. In a second step, one of the pathways - how they may lead to a reduction of heat-related mortality by increasing social capital - was further explored for underlying mechanisms, the context in which they work and the differentiated patterns of outcomes they generate. Literature was searched for evidence supporting or contradicting the initial programme theory, resulting in a refined theory. RESULTS: Results show how urban green space can impact on heat-related mortality in elderly by its influence on their exposure to outdoor and indoor heat, by improving their resilience as well as by affecting their access to treatment. Urban green spaces and their interactions with social capital affect the access to health information, social support, and the capacity for effective lobbying. Several mechanisms help to explain these observed demi-regularities, among others perceived behavioural control, perceived usefulness, receptiveness, ontological security, and self-interest. If and how they are triggered depends on the characteristics of the urban green space, the population, and other contextual factors. CONCLUSION: Looking into the impact of urban green spaces on heat-related mortality in elderly, researchers and policy makers should take interest in the role of social capital.

GPS-derived environmental exposures during pregnancy and early postpartum - Evidence from the madres cohort.

The built and natural environment factors (e.g., greenspace, walkability) are associated with maternal and infant health during and after pregnancy. Most pregnancy studies assess exposures to environmental factors via static methods (i.e., residential location at a single point in time, usually 3rd trimester). These do not capture dynamic exposures encountered in activity spaces (e.g., locations one visits and paths one travels) and their changes over time. In this study, we aimed to compare daily environmental exposure estimates using residential and global positioning systems (GPS)-measured activity space approaches and evaluated potential for exposure measurement error in the former. To do this, we collected four days of continuous geolocation monitoring during the 1st and 3rd trimesters of pregnancy and at 4-6 months postpartum in sixty-two pregnant Hispanic women enrolled in the MADRES cohort. We applied residential and GPS-based methods to assess daily exposures to greenspace, access to parks and transit, and walkability, respectively. We assessed potential for exposure measurement error in residential vs GPS-based estimates using Pearson correlations for each measure overall and by study period. We found residential and GPS-based estimates of daily exposure to total areas of parks and open spaces were weakly positively correlated (r = 0.31, P < .001) across pregnancy and postpartum periods. Residential estimates of %greenspace (r = 0.52, P < .001) and tree cover (r = 0.55, P < .001) along walkable roads were moderately correlated with GPS-based estimates. Residential and GPS-based estimates of public transit proximity, pedestrian-oriented intersection density, and walkability index score were all highly positively correlated (r > 0.70, P < .001). We also found associations between residential and GPS-based estimates decreased among participants with greater daily mobility. Our findings suggest the popular approach that assessing the built and natural environment exposures using residential methods at one time point may introduce exposure measurement error in pregnancy studies. GPS-based methods, to the extent feasible, are recommended for future studies.

Biodiversity and human health: A scoping review and examples of underrepresented linkages.

Mounting evidence supports the connections between exposure to environmental typologies(such as green and blue spaces)and human health. However, the mechanistic links that connect biodiversity (the variety of life) and human health, and the extent of supporting evidence remain less clear. Here, we undertook a scoping review to map the links between biodiversity and human health and summarise the levels of associated evidence using an established weight of evidence framework. Distinct from other reviews, we provide additional context regarding the environment-microbiome-health axis, evaluate the environmental buffering pathway (e.g., biodiversity impacts on air pollution), and provide examples of three under- or minimally-represented linkages. The examples are (1) biodiversity and Indigenous Peoples' health, (2) biodiversity and urban social equity, and (3) biodiversity and COVID-19. We observed a moderate level of evidence to support the environmental microbiota-human health pathway and a moderate-high level of evidence to support broader nature pathways (e.g., greenspace) to various health outcomes, from stress reduction to enhanced wellbeing and improved social cohesion. However, studies of broader nature pathways did not typically include specific biodiversity metrics, indicating clear research gaps. Further research is required to understand the connections and causative pathways between biodiversity (e.g., using metrics such as taxonomy, diversity/richness, structure, and function) and health outcomes. There are well-established frameworks to assess the effects of broad classifications of nature on human health. These can assist future research in linking biodiversity metrics to human health outcomes. Our examples of underrepresented linkages highlight the roles of biodiversity and its loss on urban lived experiences, infectious diseases, and Indigenous Peoples' sovereignty and livelihoods. More research and awareness of these socioecological interconnections are needed.

Atmospheric particulate matter retention capacity of bark and leaves of urban tree species.

Urban vegetation can effectively filter and adsorb particulate matter (PM). However, limited studies have been conducted on the PM retention capacity of tree barks. This study investigated the ability of five common urban tree species in the Yangtze River Delta region to retain PM through their barks and leaves by conducting a 14-day tree PM retention experiment on the five tree species during autumn and winter. The results showed that (1) the PM retention per unit area of bark was 6.9 times and 11.8 times higher than that of leaves during autumn and winter, respectively; (2) when considering total surface area, bark and leaves exhibited comparable PM retention capacities at the whole-plant scale; (3) the ability of bark to retain PM is species-specific, which can be attributed to different bark morphology among different tree species; and (4) bark and leaves exhibited distinct preferences for retaining PM of different particle sizes, even when exposed to similar environmental conditions. This study highlights the remarkable ability of tree bark to PM removal and provides valuable insights into the role of urban trees in mitigating PM pollution. Furthermore, these findings can provide valuable insights into studies on dry deposition modelling, urban planning, and green space management strategies.

Measuring the 3-30-300 rule to help cities meet nature access thresholds.

The 3-30-300 rule offers benchmarks for cities to promote equitable nature access. It dictates that individuals should see three trees from their dwelling, have 30 % tree canopy in their neighborhood, and live within 300 m of a high-quality green space. Implementing this demands thorough measurement, monitoring, and evaluation methods, yet little guidance is currently available to pursue these actions. To overcome this gap, we employed an expert-based consensus approach to review the available ways to measure 3-30-300 as well as each measure's strengths and weaknesses. We described seven relevant data and processes: vegetation indices, street level analyses, tree inventories, questionnaires, window view analyses, land cover maps, and green space maps. Based on the reviewed strengths and weaknesses of each measure, we presented a suitability matrix to link recommended measures with each component of the rule. These recommendations included surveys and window-view analyses for the '3 component', high-resolution land cover maps for the '30 component', and green space maps with network analyses for the '300 component'. These methods, responsive to local situations and resources, not only implement the 3-30-300 rule but foster broader dialogue on local desires and requirements. Consequently, these techniques can guide strategic investments in urban greening for health, equity, biodiversity, and climate adaptation.

Urban green spaces and behavioral and cognitive development in children: A health impact assessment of the Barcelona "Eixos Verds" Plan (Green Axis Plan).

BACKGROUND: Urban environments lack natural features, while nature exposure in cities has been associated with health benefits, including children's neurodevelopment. Through extensive street greening, Barcelona's Eixos Verds (Green Axis) Plan enhances safety, environment, and climate resilience. We aimed to assess the Eixos Verds Plan's potential impact on children's behavioral and cognitive development due to the increased green space expected under the Eixos Verds implementation. METHODS: We performed a quantitative health impact assessment for Barcelona children at census-tract level (n = 1068). We assessed the Eixos Verds Plan's impact by comparing baseline green space distribution with the proposed plan, translating it into percentage green area (%GA) and Normalized Difference Vegetation Index (NDVI). By combining these exposure metrics with child-specific risk estimates and population data, we estimated potential improvements in children's behavioral and cognitive development due to full Eixos Verds implementation. RESULTS: With the full Eixos Verds implementation, citywide, %GA increased by 6.9% (IQR: 6.4%; range: 0-23.1%) and NDVI by 0.065 (IQR: 0.083; range: 0.000-0.194). Child behavioral and cognitive development outcomes are expected to improve compared to the baseline. Based on NDVI increases, children's Total Difficulties and Hyperactivity/Inattention scores, based on the Strengths and Difficulties Questionnaire (SDQ), are projected to decrease by 5% (95% CI: 0-15%) and 6% (95% CI: 0-17%). Working Memory and Superior Working Memory scores are expected to increase by 4% and 5%, respectively, based on the computerized n-back test, while the Inattentiveness score could be reduced by 1%, based on the computerized attentional test (ANT). INTERPRETATION: Urban greening as planning tool can improve behavioral and cognitive development in city children. Methods and results of our study are applicable to many cities worldwide, and similar results for children of real-life urban greening interventions can be expected.