ABSTRACT Multiple coupled green space data and representations from Earth observations are available for deriving green space exposure measurements, but they may not be equally effective in health outcome modeling. This indicates algorithmic and representational uncertainties in green space research. In this study, we conceptualized this methodological issue and systematically compared a suite of available green space representations for mobility-oriented green space exposure measurements. Five typical green space representations in Hong Kong were derived from either remote sensing or street view image (SVI) data. Multiple exposure measurements were then derived through a spatiotemporal accumulation approach using each green space representation. The results indicate that green space exposure measurements derived from different representations may have different magnitudes, inconsistent correlations between each other, contradictory associations with participants’ activity space sizes, and may or may not reveal the disparities in the characteristics of green space in different geographic contexts. Since different green space representations may be coupled with different health pathways, our study provided essential insights into properly conceptualizing green space representations to derive causally relevant and effective green space exposure measurements and to mitigate the algorithmic and representational uncertainties in a range of environmental health studies that consider green space an important factor in human health.

How urban park exposure shapes dyslipidemia risk: Evidence from mobility data in Seoul, South Korea.

Amidst rapid global urbanization, understanding the association between urban planning and mental health is crucial. This review synthesizes fragmented evidence on six core elements - walkability, green spaces, blue spaces, population density, public transport accessibility, and road design-to address gaps in causality and equity, providing timely insights for creating psychologically supportive urban environments. Evidence consistently indicates a moderate protective association between urban green space and mental health. Findings for walkability and population density are highly heterogeneous, often moderated by socioeconomic factors and air pollution. Research on blue spaces and road design remains limited, highlighting significant variability and context-dependence across planning elements. Methodological challenges, such as establishing causality, simplistic exposure metrics, and inadequate consideration of equity-constrain current evidence. Future research should prioritize longitudinal and natural experiment designs, dynamic multiexposure assessments, and explicit equity integration to generate actionable guidance for urban planning that supports mental well being equitably.

In recent decades, citizen science has emerged as a key approach to engage the public in research, enhancing scientific productivity and democratizing science. However, the effective use of citizen-generated environmental data for climate change analysis and decision-making remains limited due to the heterogeneity of data sources, formats, and platforms, which hinders interoperability and reuse within existing environmental data infrastructures. This paper presents the Environmental Impact Hub (EIH), developed within the EU Horizon 2020 I-CHANGE project, as an interoperable data infrastructure designed to integrate heterogeneous environmental observations from citizen science activities, low-cost sensors, institutional monitoring networks, and Earth observation systems. Guided by the principle ‘from citizens to citizens’, the EIH adopts a modular architecture based on a Data and Information Broker, a Citizen Observatory Archive, and an interactive Dashboard, enabling data discovery, access, and reuse through open standards and APIs. The infrastructure was tested across eight Living Labs in Europe and beyond, demonstrating its capability to ingest, harmonize, and expose heterogeneous datasets, and to support interoperability with major initiatives such as Copernicus, GEO/EuroGEO, and the Green Deal Data Space. The EIH exemplifies a scalable, FAIR-aligned approach to integrating citizen-generated data into Digital Earth ecosystems, supporting climate-related environmental applications and data-driven services.

Health-related activity outcomes of visual characteristics in urban green spaces: An on-site comparison between self-reported and observed activities

Trade-off between urban green spaces and public service facilities in China's metropolises: Through the lens of population mobility under urbanization

The 15-15 rule for healthy cities: An operational subject-object integrated model to bridge greenspace accessibility and effective exposure in environmental planning.

Unraveling the 3D structure of urban green spaces: Key drivers of cooling effects across urban heat scenarios

Global inequalities in population exposure to urban green space cooling

The regulation direction and magnitude of urban green space on ozone depend on vegetation photosynthetic activity

Mowing reshapes the multielement stoichiometry of aboveground plant matter: A lesson from two cities for urban lawn management.

ABSTRACT Three-dimensional (3D) maps of urban green spaces (UGS) provide a significant dataset for estimating carbon sequestration and understanding urban ecosystem functions. However, existing 3D-UGS mapping methods are often designed for light laser detection and ranging (LiDAR) data with high cost and small coverage, limiting their scalability for city-level applications. In response to the above limitations, we developed a multi-view intelligent fusion network by using multi-view images to generate a 3D-UGS map. The proposed algorithm consists of three parts: (1) Height information estimation network; (2) UGS extraction network; and (3) 3D-UGS map generation module. A height information estimation network was used to retrieve detailed UGS height information. UGS extraction network-based multimodal feature fusion idea was proposed to extract 2D-UGS. 3D-UGS map generation module was developed to produce a fine-grained 3D-UGS map. The proposed algorithm yields a high-quality 3D-UGS map with a root mean square error (RMSE) ranging from 0.85 m to 1.06 m for the urban semantic 3D (US3D) dataset. The results showed that the proposed algorithm achieves remarkable 3D-UGS map performance with an average RMSE of 2.045 m at Beijing. Our research provides new insight into how multi-view images and artificial intelligence (AI) can be integrated to generate fine 3D-UGS maps at the city scale.

Urban heat exposure patterns and domain-specific executive function in adolescents.

Beyond proximity: A three-dimensional assessment of urban park green space equity in Seoul

Purpose As climate warming and urban heat exposure continue to intensify, accurately identifying the cooling effect of vegetation is essential for developing effective urban climate adaptation strategies. However, the relationship between the Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) is highly sensitive to spatial scale. Inappropriate scale selection may lead to misjudgments of urban cooling potential due to the Modifiable Areal Unit Problem (MAUP). This study aims to reveal the scale dependency of the NDVI–LST relationship and assess its implications for urban green space planning and climate adaptation decision-making. Design/methodology/approach Taking Shanghai as a case study, this research constructs multi-scale grids while maintaining consistent spatial resolution of remote sensing data. Land use change information from 2000 to 2024 is integrated into the analysis. By combining the Random Forest model with the SHAP interpretation method, this study examines the statistical relationship, nonlinear response structure and variations in cooling turning points of NDVI–LST across different scales and land use contexts. This approach enables a systematic assessment of how spatial aggregation methods influence the identification of vegetation cooling effects. Findings The results show that as the analysis scale shifts from coarse to fine, local heterogeneity and contextual effects are significantly enhanced. The nonlinear response structure of NDVI–LST and its cooling thresholds undergo systematic changes with scale. At coarse scales, local fluctuations are smoothed out and the overall response becomes more stable. At fine scales, nonlinear characteristics become more pronounced and spatial differences more prominent. From the MAUP perspective, scale selection not only affects the assessment of statistical correlations but may also introduce biases in evaluating the cooling efficiency of green spaces within climate adaptation planning. Originality/value This study proposes a reusable multi-scale assessment framework from the MAUP perspective. It reveals the scale sensitivity of the NDVI–LST relationship and its contextual dependency across different land use backgrounds. The findings highlight the critical value of multi-scale information in urban green infrastructure planning and heat risk management. This provides methodological innovation and practical references for developing evidence-based urban climate adaptation strategies.

Urban sacred forests are culturally embedded green spaces that contribute to urban sustainability, yet their roles remain insufficiently integrated into urban planning and green infrastructure frameworks. This study examines urban sacred forests as socio-cultural infrastructure by analyzing visitor recognition of ecosystem services, patterns of engagement, and interest in local knowledge in Kanazawa, Japan. A visitor-based survey was conducted across six shrine and temple forests between June and July 2023, yielding 342 valid responses. Descriptive statistics, chi-square tests, and correlation analyses were applied to examine relationships among visit frequency, ecosystem service recognition, community participation, and learning interest. The results indicate that visitors predominantly recognize cultural and experiential ecosystem services, particularly scenic beauty, spiritual connection, stress reduction, and connection to nature, whereas regulating and socio-economic services are less salient. Visit frequency is positively associated with community participation, with frequent visitors more likely to report involvement in site-related activities. These findings highlight the multifunctional role of urban sacred forests as spaces that support well-being, social capital, and cultural continuity. By functioning as socio-cultural infrastructure, sacred forests complement conventional urban green spaces with culturally grounded, relational benefits that are not readily captured by standard planning approaches. Integrating urban sacred forests into green infrastructure and cultural heritage policies, alongside participatory and intergenerational governance strategies, can strengthen their contribution to resilient, inclusive, and culturally rich cities.

Background. The growth of urban populations leads to swift urban development. Consequently, much of the unplanned expansion of new neighborhoods results in the loss of public open space. The deficiency of public open space, particularly Urban Green Space (UGS), diminishes the quality of life and adversely affects community health. This study seeks to provide an overview of the significance of UGS. Furthermore, it aims to evaluate the accessibility of UGS in the context of Famagusta city in Cyprus.Method. The methodology employed in this study integrates geographical information systems, questionnaires, and field surveys to assess UGS accessibility within the study area. Additionally, the principles of English Nature concerning UGS accessibility were utilized as a foundation for this evaluation.Result. The findings of the study indicate that the rapid urbanization of the area has led to a reduction in UGS. Indeed, the existing UGS in Famagusta is both physically and visually inaccessible. The absence of paved pedestrian pathways, lighting, recreational amenities, and seating furniture renders the UGS ineffective. The current circumstances necessitate immediate action from the relevant authorities.

ABSTRACT Amid rapid urbanisation and growing concerns about social isolation, urban green spaces are increasingly recognised as environments that may support mental well-being. However, existing research has largely focused on the physical availability and proximity of green spaces, with limited attention to how individuals’ perceptions of green space quality influence experiences of loneliness, particularly in rapidly urbanising contexts such as urban India. Addressing this gap, the present study examines how perceptions of accessibility, design quality, safety, and opportunities for social interaction in urban green spaces relate to loneliness. The study draws on a cross-sectional survey of 221 respondents from diverse demographic groups. Loneliness was measured using the UCLA Loneliness Scale, while perceptions of green spaces were assessed through a structured questionnaire. Correlation and regression analyses were conducted to examine associations between perceived green space characteristics and reported loneliness. The findings indicate a significant association between loneliness and negative perceptions of green spaces, particularly among women and younger individuals, suggesting that subjective experiences of urban environments may influence well-being strongly than spatial availability. Design attributes such as shaded seating and recreational opportunities show stronger associations with reduced loneliness than proximity alone, highlighting the importance of user-sensitive green space design in urban planning.

ABSTRACT This study explores the relationship between green space availability which is measured as both proportional land cover and per capita values, and socio-economic indicators across 129 regions in eight Southeast Asian countries. Using a cross-sectional and quantitative approach, the research assesses correlations between green space availability and key metrics such as the Human Development Index (HDI), GDP per capita, health index, and life expectancy. Data were sourced from Global Data Lab and mined from Google Earth Engine. Descriptive statistics, Spearman correlation, multiple linear regression, and cluster analyses were applied to identify patterns and relationships. The findings highlight considerable differences in the amount of green space available per person across regions, with more developed areas generally having less green space per capita due to population pressures. Results show significant negative correlations between green space per capita and HDI (ρ = −0.6445, p < 0.05), GDP per capita (ρ = −5,492, p < 0.05), and health index (ρ = −0.6794, p < 0.05). Green space proportion also negatively correlated with HDI (ρ = −0.1345, p < 0.05). These results suggest that the observed negative relationships between green space and development are not necessarily indicative of a direct trade-off, highlighting the need to reinterpret green space indicators within rapidly urbanising Southeast Asian contexts. When population density is introduced as a control variable, these associations remain consistent, suggesting that density-related spatial pressures, rather than the absence of green space itself, largely drive these patterns.

ABSTRACT This study investigates the relationship between neighborhood income levels and urban green space provision in Kumasi Metropolis, Ghana, through an environmental justice lens. Using a mixed-methods design, it integrates GIS-based spatial analysis with household surveys and interviews of urban planning officials. Satellite imagery enabled mapping and quantification of green spaces via Percent of Urban Green Space (PercUGS) for extent and UGS Patch Density (UGS PD) for fragmentation patterns across neighborhoods. The results show that high-income neighborhoods, particularly Nhyiaeso, have larger and less fragmented green spaces, with a PercUGS value of 75.15%. In contrast, lower-income neighborhoods such as Ayigya and Gyinyase have smaller and more fragmented green spaces, with PercUGS values of 32.25% and 36.98%, respectively. These patterns indicate inequalities in the availability and distribution of green spaces, which are linked to differences in planning control, land management, and enforcement across neighborhoods. The study concludes that urban green space provision in the Kumasi Metropolis is shaped by socio-economic conditions, resulting in environmental inequalities. The findings suggest the need to strengthen planning and governance systems to ensure a more equitable distribution and sustainable management of green spaces.