Search Results (585)

In this perspective article, we introduce Ecocebo as a novel concept describing the modulatory effects of physical environments, whether natural or built, on drug effect. Positioned as a spatial component of the placebo effect, Ecocebo is grounded in evidence-based design principles and proposes that environmental features such as natural light, greenery, spatial geometry, and calming esthetics can significantly influence sensory, emotional, and cognitive processes. These environmental factors may enhance or modify pharmacological responses, especially for analgesics, anxiolytics, and antidepressants. We highlighted how exposure to restorative spaces can reduce pain perception, stress, and the need for medication, paralleling findings in placebo research where contextual and sensory cues influence brain regions linked to emotion and pain regulation. We propose virtual reality (VR) as the most suitable methodological tool to study Ecocebo in controlled and ecologically valid settings. VR allows for the precise manipulation of spatial features and real-time monitoring of physiological and psychological responses. We also propose integrating VR with neuromodulation techniques to investigate brain–environment–drug interactions. Finally, we addressed key methodological challenges such as defining control conditions and standardizing the measurement of presence. This perspective opens new directions for the integration of non-pharmacological and pharmacological interventions and personalized therapeutic environments to optimize clinical outcomes. Full article

Urban greening distribution critically impacts residents’ quality of life and environmental sustainability. While the Green View Index (GVI), derived from street view imagery, is widely adopted for urban green space assessment, its limitation lies in the inability to capture non-street-area vegetation. Remote sensing imagery, conversely, provides full-coverage urban vegetation data. This study focuses on Beijing’s Third Ring Road area, employing DeepLabv3+ to calculate a street-view-based GVI as a predictor. Correlations between the GVI and Sentinel-2 spectral bands, along with two vegetation indices, such as the Normalized Difference Vegetation Index (NDVI) and Fractional Vegetation Cover (FVC), were analyzed under varying buffer radius. Regression and classification models were subsequently developed for GVI prediction. The optimal classifier was then applied to estimate green perception levels in non-street zones. The results demonstrated that (1) at a 25 m buffer radius, the near-infrared band, NDVI, and FVC exhibited the highest correlations with the GVI, reaching 0.553, 0.75, and 0.752, respectively. (2) Among the five machine learning regression models evaluated, the random forest algorithm demonstrated superior performance in GVI estimation, achieving a coefficient of determination (R²) of 0.787, with a root mean square error (RMSE) of 0.063 and a mean absolute error (MAE) of 0.045. (3) When evaluating categorical perception levels of urban greenery, the Extremely Randomized Trees classifier (Extra Trees) demonstrated superior performance in green vision perception level estimation, achieving an accuracy (ACC) score of 0.652. (4) The green perception level in non-road areas within Beijing’s Third Ring Road is 56.8%, which is considered relatively poor. Moreover, the green perception level within the Second Ring Road is even lower than that in the area between the Second and Third Ring roads. This study is expected to provide valuable insights and references for the adjustment and optimization of green perception distribution in Beijing, thereby supporting more informed urban planning and the development of sustainable, human-centered green spaces across the city. Full article

PM_2.5 is an air pollutant that has a direct link to increased cardiovascular and respiratory morbidity and mortality, which has been demonstrated in numerous studies. Existing research highlights species-specific variations in the capacity of trees to capture and retain particulate matter (PM). However, a critical gap remains regarding sensitivity analyses of i-Tree Eco model assumptions. Such analyses are crucial for validating the model’s PM deposition estimates against empirically derived efficiencies, a deficiency that the present study addresses. The study consisted of two steps: a tree inventory was carried out at three selected sites, based on which, an ecosystem service analysis was performed using i-Tree Eco, and samples were taken from the leaves of trees at the analysed sites, which were the basis for comparing the data from the i-Tree Eco method and laboratory methods. The study focused on comparing PM_2.5 and PM₁₀ removal estimates derived from both the model and laboratory measurements. The results revealed significant discrepancies between the modelled and laboratory values. A comparison of the average annual PM₁₀ accumulation measured using laboratory methods for individual tree species showed that Tilia sp. achieved 24%, Fraxinus sp. 47.6%, Aesculus sp. 50.77%, and Quercus robur 23.4% of the PM₁₀ uptake efficiency estimated by the i-Tree Eco model. For PM_2.5 uptake, the values obtained through both methods were more consistent. Furthermore, trees growing under more challenging environmental conditions exhibited smaller diameter at breast height (DBH) and lower PM₁₀ and PM_2.5 removal efficiency according to both methods. While I-Tree Eco incorporates tree biophysical characteristics and health status, its methodology currently lacks the resolution to reflect site-specific environmental conditions and local pollutant concentrations at the individual tree level. Therefore, laboratory methods are indispensable for calibrating, validating, and supplementing i-Tree Eco estimates, especially when applied to diverse urban environments. Only the combined application of empirical and model-based methods provides a comprehensive understanding of the potential of urban greenery to improve air quality. Full article

In order to determine the impact of urbanization on raptors in the semi-desert conditions of southwestern Kazakhstan, an analysis of the spatio-temporal distribution of raptors is presented for the first time based on the results of surveys of the avifauna of Kyzylorda. Eight species of raptors were recorded: field Hen Harrier (Circus cyaneus), Marsh Harrier (C. aeroginosus), Eurasian Sparrowhawk (Accipiter nisus), Long-Legged Buzzard (Buteo rufinus), Eurasian Buzzard (B. buteo), Steppe Eagle (Aquila nipalensis), Eurasian Hobby (Falco subbuteo), and Common Kestrel (F. tinnunculus). The probability of raptors being present was negatively associated with dense urban low-rise buildings with limited greenery in the bay and the new part of the city. At the same time, the dense urban development with little or no greenery in the old central part of the city provides adequate habitat (including a foraging base and nesting sites) for the Common Kestrel. Raptor presence was positively associated with the Syrdarya River floodplain and wasteland with small groups of trees and/or shrubs. The landfill site located on the north-eastern edge of the city serves as a feeding ground for the Long-Legged and Eurasian Buzzards, while the airport area is inhabited by the Eurasian Buzzard, Steppe Eagle, and Common Kestrel. Based on this study, we would recommend that enterprises (e.g., grain storage facilities, airports) and local executive bodies who are interested in the conservation of raptors and regulating the population of the pigeons around their territories should retain or plant more native vegetation and shrubs and preserve areas with green spaces. Full article

Global warming, anthropogenic pressure, and urban expansion at the expense of green spaces are leading to an increase in the incidence of urban heat islands, creating discomfort and health issue for citizens. This present research aimed at quantifying the impact of nature-based solutions to support decision-making processes in sustainable energy action plans. A simple method is provided, linking applied thermodynamics to physics-informed modeling of urban built-up and green areas, high-resolution climate models at urban scale, greenery modeling, spatial georeferencing techniques for energy, and entropy exchanges evaluation in urban built-up areas, with and without vegetation. This allows the outdoor climate conditions and thermo-hygrometric well-being to improve, reducing the workload of cooling plant-systems in buildings and entropy flux to the environment. The finalization and post-processing of obtained results allows the definition of entropy footprints. The main findings show a decrease in greenery’s contribution for different scenarios, referring to a different climatological dataset, but an increase in entropy that becomes higher for the scenario with higher emissions. The comparison between the entropy footprint values for different urban zones can be a useful support to public administrations, stakeholders, and local governments for planning proactive resilient cities and anthropogenic impact reduction and climate change mitigation. Full article

Equity in urban greenery is essential to improving residents’ well-being and contributing to environmental justice. Research on equity in street-scale urban greenery remains limited, but this study addresses it by employing the green view index (GVI), a widely recognized indicator for assessing green space quality from a pedestrian perspective, using semantic segmentation methods and Baidu Street View (BSV) images to quantify street-level greenery. Through spatial clustering and hot spot analysis, the visibility and spatial distribution of street greenery in Hangzhou’s central urban area were examined. Furthermore, the Lorenz curve, Gini coefficient, and location entropy were applied to evaluate disparities in green visibility across urban spaces. The results show that the average GVI at the sample point level, road level, and district level in the study area are 0.167, 0.142, and 0.177, respectively. Meanwhile, the spatial heterogeneity of the GVI is highly pronounced, with distinct clustering characteristics. The Gini coefficient of street greenery visibility is 0.384, indicating a moderate level of inequality in the distribution of greenery resources. Notably, a higher GVI does not necessarily correspond to better internal greenery equity, highlighting disparities in the distribution of urban greenery. This study offers a more precise and refined quantification of urban greenery equity, providing critical insights for addressing spatial disparities and informing urban planning strategies aimed at promoting equitable green infrastructure. Full article

Climate change intensifies the challenge of elevated temperatures in dense urban areas, notably in Seoul, South Korea. This study investigates the effects of land use and urban form on summer air temperatures by leveraging Seoul’s city-wide Smart Seoul Data of Things sensor network. Using spatial regression models and temperature data collected during July and August 2021, the analysis identifies key environmental factors associated with urban heat dynamics. The results show that medium- and high-density residential areas, industrial zones, and roads consistently increase temperatures, while greenery, taller buildings, and greater urban porosity contribute to cooling effects. The findings highlight the need for urban planning strategies that expand green spaces, promote vertical development with attention to ventilation, and reconfigure built environments to enhance thermal comfort. This study provides robust empirical insights and offers evidence-based recommendations for climate-responsive urban planning and policies in Seoul and similar high-density cities worldwide. Full article

Environmental awareness and sustainability are essential for city development. Therefore, the study examined the attitudes of 1023 Polish Generation Z students from WULS-SGGW in Warsaw, Poland, toward urban trees and willingness to support tree planting. The findings revealed that 75% care about the environment, 93% value nature, and 92% enjoy seeing new trees. Additionally, 74% support funding tree planting, 51% would volunteer, and 39% donate money. However, 54% believe that property owners should be free to cut trees. The Agglomerative Hierarchical Clustering (AHC) method was applied to divide students into clusters. Clusters differed first in students’ attitudes toward trees, from “Tree Lovers” to “Tree Sceptics”, and second in students’ anthropocentric vs. environmental orientation: opposing (“Trees First”) vs. supporting (“People First”) the right to freely cut private trees. An additional questionnaire allowed us to link students’ clusters with importance assigned to positive and adverse tree attributes, like “Attractiveness,” “Usefulness,” and “Danger”. The study results do not provide a clear answer regarding the issue of Polish Generation Z students and the future sustainable development of urban greenery. They want to support trees for practical qualities, beauty, and utility. However, many place an even greater value on their right to self-determination regarding their property, including tree removal. Full article

The metro railway system is pivotal not just as a crucial transportation network for daily commuters but also as a significant enhancer of urban vibrancy, especially through its role in attracting a substantial volume of non-commuters. This study focuses on non-commuting travel behaviors around metro stations, exploring how the built environment affects non-commuters’ destination choices. A Random Forest model is developed based on data from Chengdu, China. The model is interpreted with SHapley Additive exPlanations (SHAP) analysis. Route length, building coverage, greenery, and proximity are key factors and indicate a nonlinear impact on non-commuters’ destination choices. The impact of these factors was found to vary significantly depending on the scale and context, indicating a need for nuanced urban planning approaches. The findings highlight the need for sophisticated urban planning that balances functionality and needs in transit-oriented development, aiming to cater to non-commuters and promote sustainable, vibrant urban spaces. Full article

The implementation of Vertical Greening Systems (VGS), like green façades, on historic building facades is approached with caution due to concerns regarding material compatibility, visual impact, and potential compromises to cultural significance. However, VGS can offer significant contributions to urban sustainability when integrated with knowledge and care of historic buildings by reducing the urban heat island effect, improving air quality, fostering a green economy, and creating greener environments. These tensions highlight a critical research gap: how can VGS contribute to urban sustainability while respecting the values of historic building façades? This study addresses this gap by exploring professional interest groups’ opinions on implementing VGS on historic buildings, focusing on the perceived benefits and concerns from environmental, social, economic, cultural, legal, and technical aspects. A mixed-methods approach was employed, combining the findings from the literature review with a survey targeting individuals involved in VGS implementations or heritage conservation. The survey included both open- and closed-ended questions. Of the 165 individuals contacted, 83 valid responses were analyzed. Results from the open-ended questions showed that 89% of respondents recognized the environmental benefits of VGS, while 85% raised technical issues, particularly regarding material compatibility. An important insight emerged from comparing open-ended and closed-ended responses: respondents were more likely to acknowledge the benefits of VGS when prompted. This indicates that raising awareness about the use of VGS on historic buildings is essential. The findings offer practical implications for early-stage planning, stakeholder engagement, and the design of heritage conservation policy. They illustrate a need for an informed decision-making process for the integration of VGS onto historic building facades, aligning with conservation ethics and urban sustainability. Preface: This study aims to create a discussion on the potential synergies between vertical greening and historic buildings, with the intention of guiding future conservation strategies to enhance urban sustainability. We do not advocate for vertical greenery as a universal solution, but rather seek to explore under which conditions vertical greening may be compatible with conservation practice. For the purposes of this study, “historic buildings” refer to structures that possess cultural, architectural, or historical significance, whether they are formally protected or informally valued by their communities. We acknowledge that the term may vary in meaning across different national and cultural contexts. Moreover, our analysis focuses on cases where both the vertical greening and historic façades are presumed to be in structurally sound and well-maintained condition. Full article

As people spend extended periods of time indoors, stress and negative emotions caused by work have become increasingly difficult to ignore. Observing window views is widely considered an effective method to alleviate stress and promote mental health. However, the specific visual elements within these views that contribute to stress reduction and the differential restorative benefits across varying compositions remain insufficiently understood. This study focuses on four major visual elements commonly seen through windows: sky, buildings, greenery, and roads. Using a horizontal layering approach, nine window views were created based on different proportions of these elements. Participants were exposed to these views, and their responses were evaluated through the positive and negative affect scale (PANAS), as well as electroencephalographic (EEG) data acquisition. The findings indicate that greenery exhibits the most pronounced positive effect on stress mitigation and the enhancement of positive affect, while the presence of roads is more likely to elicit negative emotional responses. Additionally, the visual richness and structural completeness of the window scenes are found to significantly impact restorative outcomes. These findings provide empirical insights for landscape and architectural design aimed at improving psychological well-being. Full article

During the transition of culture-featured district planning from static conservation to innovation-driven models, existing research remains constrained by mechanistic paradigms, reducing districts to functional containers and neglecting human perceptual interactions and meaning-production mechanisms. This study explores and quantifies the generative mechanisms of spatial communicability and cultural dissemination efficacy within human-centered frameworks. Grounded in humanistic urbanism, we analyze Harbin Central Street as a case study integrating historical heritage with contemporary vitality, developing a tripartite communicability assessment framework comprising perceptual experience, infrastructure utility, and behavioral dynamics. Machine learning-based threshold analysis reveals that spatial encoding elements govern communicability through significant nonlinear mechanisms. The conclusion shows synergies between street view-quantified greenery visibility and pedestrian accessibility establish critical human-centered design thresholds. Spatial data analysis integrating physiologically sensed emotional experiences and topologically analyzed spatial morphology resolves metric fragmentation while examining spatial encoding’s impact on interaction efficacy. This research provides data-driven decision support for sustainable urban renewal and enhanced cultural dissemination, advancing heritage sustainability. Full article

This article presents a spatial analysis of projects selected by city residents and implemented in five successive editions (2015–2019) of the participatory budgeting in Częstochowa, Poland. The study examines the relationship between the type of hard projects (small investments in public infrastructure and landscaping) and the pre-existing characteristics of the land use of each district. Kernel density estimation and Spearman correlation analysis were used. The highest spatial density occurred in projects related to the modernization of roads and sidewalks, recreation, and greenery, indicating a relatively high number of proposals within or near residential areas. Key correlations included the following: (1) greenery projects were more common in districts lacking green areas; (2) recreational infrastructure was more frequently chosen in areas with significant water features; (3) street furniture projects were mostly selected in districts with sparse development, scattered buildings, and postindustrial sites; (4) educational infrastructure was often chosen in low-density, but developing districts. The selected projects often reflect local deficits in specific land use or public infrastructure, but also stress the predestination of the recreational use of waterside areas. Full article

Urban heat islands (UHIs) are a growing sustainability challenge impacting public health, energy use, and climate resilience, especially in hot, arid cities like San Antonio, Texas, where land surface temperatures reach up to 47.63 °C. This study advances a data-driven, interdisciplinary approach to UHI mitigation by integrating Machine Learning (ML) with physical and socio-demographic data for sustainable urban planning. Using high-resolution spatial data across five functional zones (residential, commercial, industrial, official, and downtown), we apply three ML models, Random Forest (RF), Support Vector Machine (SVM), and Gradient Boosting Machine (GBM), to predict land surface temperature (LST). The models incorporate both environmental variables, such as imperviousness, Normalized Difference Vegetation Index (NDVI), building area, and solar influx, and social determinants, such as population density, income, education, and age distribution. SVM achieved the highest R² (0.870), while RF yielded the lowest RMSE (0.488 °C), confirming robust predictive performance. Key predictors of elevated LST included imperviousness, building area, solar influx, and NDVI. Our results underscore the need for zone-specific strategies like more greenery, less impervious cover, and improved building design. These findings offer actionable insights for urban planners and policymakers seeking to develop equitable and sustainable UHI mitigation strategies aligned with climate adaptation and environmental justice goals. Full article

Street view imagery has become a vital tool for assessing urban street greenery, with the Green View Index (GVI) serving as the predominant metric. However, while GVI effectively quantifies overall greenery, it fails to capture the nuanced, human-scale experience of urban greenery. This study introduces the Front-Facing Green View Index (FFGVI), a metric designed to reflect the perspective of pedestrians traversing urban streets. The FFGVI computation involves three key steps: (1) calculating azimuths for road points, (2) retrieving front-facing street view images, and (3) applying semantic segmentation to identify green pixels in street view imagery. Building on this, this study proposes the Street Canyon Green View Index (SCGVI), a novel approach for identifying boulevards that evoke perceptions of comfort, spaciousness, and aesthetic quality akin to room-like streetscapes. Applying these indices to a case study in Nanjing, China, this study shows that (1) FFGVI exhibited a strong correlation with GVI (R = 0.88), whereas the association between SCGVI and GVI was marginally weaker (R = 0.78). GVI tends to overestimate perceived greenery due to the influence of lateral views dominated by side-facing vegetation; (2) FFGVI provides a more human-centered perspective, mitigating biases introduced by sampling point locations and obstructions such as large vehicles; and (3) SCGVI effectively identifies prominent boulevards that contribute to a positive urban experience. These findings suggest that FFGVI and SCGVI are valuable metrics for informing urban planning, enhancing urban tourism, and supporting greening strategies at the street level. Full article