Search Results (234)

Urban vitality acts as a key driver of sustainable urban development, while the built environment serves as its physical foundation. However, spatial heterogeneity in urban landscapes leads to imbalanced impacts of economic, social, and environmental factors on vitality. Therefore, it is essential to investigate the underlying principles governing vitality impacts imposed by diverse components of the built environment at the spatial level. This study synthesized multi-source remote sensing data alongside geospatial datasets aiming to quantify vitality and built environment indicators across Shenyang, China. We applied Ordinary Least Squares (OLS) regression for collinearity diagnosis and Multi-scale Geographically Weighted Regression (MGWR) to model spatial heterogeneity impacts at the planning-unit level. The regression factor analysis yielded three primary conclusions: (1) Functional Mixture Degree, Bus Stop Density, and Subway Station Density demonstrated a statistically significant positive correlation with urban vitality. (2) FAR (Floor Area Ratio), Vegetation Coverage, Commercial Facility Density, and Road Density exhibited differentiated effects in core areas versus peripheral areas. (3) Public Facility Density and Bus Stop Density showed a negative correlation trend with vitality levels in Industrial Functional Zones. We propose a geospatial analysis framework that leverages remote sensing to decode spatially heterogeneous built environment–vitality linkages. This approach supports precision urban renewal planning by identifying location-specific interventions. Geospatial big data and MGWR offer replicable tools for analyzing urban sustainability. Future work should integrate real-time sensor data to track vitality dynamics. Full article

As mental health issues such as stress, anxiety, and depression become increasingly prevalent in urban populations, there is a critical need to embed restorative functions into the built environment. Urban parks, as integral components of ecological infrastructure, play a vital role in promoting psychological well-being. This study explores how diverse park environments facilitate mental health recovery through multi-sensory engagement, using integrated psychophysiological assessments in a wetland park in Zhengzhou, China. Electroencephalography (EEG) and perceived restoration scores were employed to evaluate recovery outcomes across four environmental types: waterfront, wetland, forest, and plaza. Key perceptual factors—including landscape design, spatial configuration, biodiversity, and facility quality—were validated and analyzed for their roles in shaping restorative experiences. Results reveal significant variation in recovery effectiveness across environments. Waterfront areas elicited the strongest physiological responses, while plazas demonstrated lower restorative benefits. Two recovery pathways were identified: a direct, sensory-driven process and a cognitively mediated route. Biodiversity promoted physiological restoration only when mediated by perceived restorative qualities, whereas landscape and spatial attributes produced more immediate effects. Facilities supported psychological recovery mainly through cognitive appraisal. The study proposes a smart park framework that incorporates environmental sensors, adaptive lighting, real-time biofeedback systems, and interactive interfaces to enhance user engagement and monitor well-being. These technologies enable urban parks to function as intelligent, health-supportive infrastructures within the broader built environment. The findings offer evidence-based guidance for designing responsive green spaces that contribute to mental resilience, aligning with the goals of smart city development and healthy life-building environments. Full article

Obesity has emerged as one of the most significant public health challenges of the 21st century, with its prevalence increasing at an alarming rate globally. While individual factors such as diet and physical inactivity are well-known contributors, the built environment, particularly housing, plays a critical yet understudied role in shaping obesity-related behaviors. This study examines the multilayered relationship between housing and obesity, focusing on built and neighborhood environment, affordability, and the social environment. Poor housing quality, such as overcrowding and inadequate ventilation, can potentially lead to chronic stress and sedentary behaviors, while housing design influences physical activity through characteristics such as design features and outdoor spaces. Housing location affects access to amenities such as parks and healthy food options, with disparities in access contributing to obesity in low-income areas. Similarly, neighborhood walkability, influenced by infrastructure and land use, encourages active transportation and recreation. Housing affordability also impacts dietary choices and access to recreational facilities, particularly for low-income families. Moreover, the social environment within housing communities can foster or hinder healthy behaviors through social networks and community engagement. This study emphasizes the need for health-conscious urban planning and policies that address these housing-related factors to combat obesity and promote healthier lifestyles. By integrating these Obesity–Housing Nexus, policymakers can create environments that support physical activity, healthy eating, as well as overall health and well-being. Full article

Urban vitality serves as an important indicator for evaluating the level of urban quality development and sustainability. In response to a series of urban challenges arising from rapid urban expansion, enhancing urban quality and fostering urban vitality have become key objectives in contemporary urban planning and development. This study summarizes the spatial distribution patterns of urban vitality at the street and neighborhood levels in the central area of Qingdao, and analyzes their spatial characteristics. A 5D built environment indicator system is constructed, and the effects of the built environment on urban vitality are explored using the Optimal Parameter Geographic Detector (OPGD) and the Multi-Scale Geographically Weighted Regression (MGWR) model. The aim is to propose strategies for enhancing spatial vitality at the street and neighborhood scales in central Qingdao, thereby providing references for the optimal allocation of urban spatial elements in urban regeneration and promoting sustainable urban development. The findings indicate the following: (1) At both the subdistrict and block levels, urban vitality in Qingdao exhibits significant spatial clustering, characterized by a pattern of “weak east-west, strong central, multi-center, cluster-structured,” with vitality cores closely aligned with urban commercial districts; (2) The interaction between the three factors of functional density, commercial facilities accessibility and public facilities accessibility and other factors constitutes the primary determinant influencing urban vitality intensity at both scales; (3) Commercial facilities accessibility and cultural and leisure facilities accessibility and building height exert a positive influence on urban vitality, whereas the resident population density appears to have an inhibitory effect. Additionally, factors such as building height, functional mixing degree and public facilities accessibility contribute positively to enhancing urban vitality at the block scale. (4) Future spatial planning should leverage the spillover effects of high-vitality areas, optimize population distribution, strengthen functional diversity, increase the density of metro stations and promote the coordinated development of the economy and culture. Full article

This study aimed to predict the potential habitats of Luciola unmunsana using a species distribution model (SDM). Luciola unmunsana is an endemic species that lives only in South Korea, and because its females do not have genus wings and are less fluid, it is difficult to collect, so research related to its distribution and restoration is relatively understudied. Therefore, this study predicted the potential habitats of Luciola unmunsana across South Korea using the single model Maximum Entropy (MaxEnt) and a multi-model ensemble model to prepare basic data necessary for a conservation and habitat restoration plan for the species. A total of 39 points of occurrence were built based on public data and prior research from the Jeonbuk Green Environment Support Center (JGESC), the Global Biodiversity Information Facility (GBIF), and the National Institute of Biological Resources (NIBR). Among the input variables, climate variables were based on the shared socioeconomic pathway (SSP) scenario-based ecological climate index, while nonclimate variables were based on topography, land cover maps, and the Enhanced Vegetation Index (EVI). The main findings of this study are summarized below. First, in predicting Luciola unmunsana potential habitats, the EVI, water network analysis, land cover, and annual precipitation (Bio12) were identified as good predictors in both models. Accordingly, areas with high vegetation activity in their forests, adjacent to water resources, and stable humidity were predicted as potential habitats. Second, by overlaying the predicted potential habitats and highly significant variables, we found that areas with high vegetation vigor within their forests, proximity to water systems, and relatively high annual precipitation, which can maintain stable humidity, are potential habitats for Luciola unmunsana. Third, literature surveys used to predict potential habitat sites, including Geumsan-gun, Chungcheongnam-do, Yeongam-gun, Jeollabuk-do, Mudeungsan Mountain, Gwangju-si, Korea, and Gijang-gun, Busan-si, Korea, confirmed the occurrence of Luciola unmunsana. This study is significant in that it is the first to develop a regional SDM for Luciola unmunsana, whose population is declining due to urbanization. In addition, by applying various environmental variables that reflect ecological characteristics, it contributes to more accurate predictions of the potential habitats of this species. The predicted results can be used as basic data for the future conservation of Luciola unmunsana and the establishment of habitat restoration strategies. Full article

Automated external defibrillator resources (AEDRs) are the crux of out-of-hospital cardiac arrest (OHCA) responses, enhancing safe and sustainable urban environments. However, existing studies failed to consider the nexus between built environment (BE) features and AEDRs. Can explainable machine-learning (ML) methods reveal the BE-AEDR nexus? This study applied an Optuna-based extreme gradient boosting (OP_XGBoost) decision tree model with SHapely Additive exPlanations (SHAP) and partial dependence plots (PDPs) aiming to scrutinize the spatial effects, relative importance, and non-linear impact of BE features on AEDR intensity across grid and block urban patterns in Tianjin Downtown, China. The results indicated, that (1) marginally, the AEDR intensity was most influenced by the service coverage (SC) at grid scale and nearby public service facility density (NPSF_D) at block scale, while synergistically, it was shaped by comprehensive accessibility and land-use interactions with the prioritized block pattern; (2) block-level granularity and (3) non-linear interdependencies between BE features and AEDR intensity existed as game-changers. The findings suggested an effective and generalizable approach to capture the complex interplay of the BE-AEDR and boost the AED deployment by setting health at the heart of the urban development framework. Full article

While the existing research has extensively explored the impact of urban green spaces on residents’ well-being, studies specifically focusing on waterfront sports buildings remain scarce. This study examines how the combined effects of built environment characteristics in waterfront sports facilities enhance user satisfaction through psychological mechanisms. Based on survey data from 721 users across nine major waterfront sports complexes in China, we find that (1) four social function dimensions (social interaction, accessibility, safety, and multifunctionality) show significant positive correlations with satisfaction; (2) place attachment mediates these relationships. These findings validate the importance of integrating water-oriented design principles with community needs, offering both theoretical contributions to human–water interaction studies and practical implications for urban blue space (defined as visible water features including rivers, lakes, and coastal areas) development. Full article

To advance evidence-based urban design prioritizing non-motorized mobility, this study proposes a street view-enabled explainable machine learning framework that systematically links built environment semantics to non-motorized transportation vitality optimization. By integrating Baidu Street View images with deep learning-based object detection (Faster R-CNN), we quantify fine-grained human-powered and mechanically assisted mobility vitality. These features are fused with multi-source geospatial data encompassing 23 built environment variables into an interpretable machine learning pipeline using SHAP-optimized random forest models. The key findings reveal distinct nonlinear response patterns between HP and MA modes to built environment factors; for instance, a notable promotion in mechanically assisted NMT vitality is observed as enterprise density increases beyond 0.2 facilities per ha. Emergent synergistic and threshold effects are evident from variable interactions requiring multidimensional planning consideration, as demonstrated in phenomena such as the peaking of human-powered NMT vitality occurring at public facility densities of 0.2–0.8 facilities per ha, enterprise densities of 0.6–1 facilities per ha, and spatial heterogeneity patterns identified through Bivariate Local Moran’s I clustering. This research contributes an innovative technical framework combining street view image recognition with explainable AI, while practically informing urban planning through evidence-based mobility zone classification and targeted strategy formulation, enabling more precise optimization of pedestrian-/cyclist-oriented urban spaces. Full article

Designing physical environments that are safe, functional, and equitable for all users is crucial to understanding the needs and requirements of the local community from a gender perspective, to achieve gender equality and women’s safety in the public realm. In the Saudi context, international assessments of women’s rights still acknowledge the country as one of the most prominent examples of structural gender inequality, both in the world and relative to regional peers within the Middle East and North Africa. This research aims to illuminate women’s mobility behavior as a tool for women’s inclusion in the built environment, supporting policymakers to design projects that build more inclusive cities for women. This research examines the dynamic relationship between women’s mobility and the built environment in Riyadh, Saudi Arabia, within the context of Vision 2030. By employing a mixed-method approach, including literature reviews and a comprehensive survey, the research highlights critical indicators such as safety, cultural norms, and infrastructure. The research concludes that safety, cultural and social norms, and the availability of public facilities significantly impact women’s ease of mobility. The paper reaches an actionable recommendation for policymakers to create more inclusive urban environments that support women’s aspirations and needs, ultimately contributing to a more equitable society that supports the expectations and needs of all women in Riyadh. Full article

As cities globally prioritize sustainable transportation, understanding gender-differentiated responses to the urban built environment is critical for equitable mobility planning. This study combined the Social Ecological Model (SEM) with the theoretical perspective of Gendered Spatial Experience to explore the differentiated impacts of the Perceived Street Built Environment (PSBE) on the cycling behavior of men and women. Questionnaire data from 285 e-bike and traditional bicycle riders (236 e-bike riders and 49 traditional cyclists, 138 males and 147 females) from Gulou District, Nanjing, between May and October 2023, were used to investigate gender differences in cycling behavior and PSBE using the Mann–Whitney U-test and crossover analysis. Linear regression and logistic regression analyses examined the PSBE impact on gender differences in cycling probability and route choice. The cycling frequency of women was significantly higher than that of men, and their cycling behavior was obviously driven by family responsibilities. Greater gender differences were observed in the PSBE among e-bike riders. Women rated facility accessibility, road accessibility, sense of safety, and spatial comfort significantly lower than men. Clear traffic signals and zebra crossings positively influenced women’s cycling probability. Women were more sensitive to the width of bicycle lanes and street noise, while men’s detours were mainly driven by the convenience of bus connections. We recommend constructing a gender-inclusive cycling environment through intersection optimization, family-friendly routes, lane widening, and noise reduction. This study advances urban science by identifying gendered barriers in cycling infrastructure, providing actionable strategies for equitable transport planning and urban design. Full article

The sustainable management of organic waste is a global priority due to its environmental impact and the increasing pressure on urban and rural systems, particularly in regions with limited technological infrastructure. This study introduces and validates a comprehensive methodology based on Digital Twins (DTs) to optimize production and service systems in organic waste management. The methodology includes contextual and propositional phases and is built on a modular three-layer architecture (physical, cloud, and virtual) that enables real-time monitoring, simulation, and feedback. It was validated through a field implementation in a composting facility in Cajamarca, Colombia. The results showed a 10% increase in composting efficiency and a monthly gain of 1200 kg of compost. A statistical analysis confirmed a significant increase in process efficiency (p < 0.001) and a reduction in performance variability (p < 0.01). The return on investment reached 18,957.6% using low-cost technology. These findings demonstrate the viability and adaptability of the proposed methodology for low-tech environments and support its potential for scaling in circular economy applications across waste management and agriculture. Full article

High-speed rail (HSR) station areas play a vital role in shaping urban form, stimulating economic activity, and enhancing spatial vitality. Understanding the factors that influence this vitality is key to supporting sustainable urban development and transit-oriented planning. This study investigates 66 HSR station areas in 35 Chinese cities by integrating multi-source data—Sina Weibo check-in records, urban support indicators, station attributes, and built environment variables—within a city–node–place analytical framework. Using Multiple Linear Regression (MLR) and Light Gradient Boosting Machine (LightGBM) models, we identify key drivers of spatial vitality, while SHAP analysis reveals nonlinear and interaction effects. The results show that city population size, urbanization level, commercial land use, transit accessibility, and parking facilities significantly enhance station area vitality. However, diminishing returns are observed when commercial land and bus stop densities exceed certain thresholds. The station location index shows a negative correlation with spatial vitality. The analysis of interaction effects highlights strong synergies between urban development and functional configuration, as well as between accessibility and service infrastructure. Different station types exhibit varied spatial patterns and require differentiated strategies. This study offers empirical insights for aligning transport infrastructure and land use planning, supporting the development of vibrant, accessible, and sustainable HSR station areas. Full article

Urban vitality is a critical indicator of both urban sustainability and quality of life. However, comprehensive studies examining the threshold effects and interaction mechanisms of built environment factors on urban vitality at the block level remain limited. This study proposed to develop a comprehensive framework for urban vitality by incorporating multi-source data, and the central urban area of Xi’an, China, was selected as the study area. Four machine learning models, LightGBM, XGBoost, GBDT, and random forest, were employed to identify the most fitted model for analyzing threshold effects and interactions among built environment factors on shaping urban vitality. The results showed the following: (1) Xi’an’s urban vitality exhibited a distinct gradient, with the highest vitality concentrated in the Yanta District; (2) life service facility density was the most significant determinant of vitality (19.91%), followed by air quality (9.01%) and functional diversity (6.49%); and (3) significant interactions among built environment factors were observed. In particular, streets characterized by both high POI diversity (greater than 0.8) and low PM_2.5 concentrations (below 48.5 μg/m³) exhibited notably enhanced vitality scores. The findings of this study provide key insights into strategies for boosting urban vitality, offering actionable insights for improving land use allocations and enhancing quality of life. Full article

As climate change intensifies, cities are experiencing more severe rainfall and frequent waterlogging. When rainfall exceeds the carrying capacity of urban drainage networks, it poses a significant risk to urban facilities and public safety, seriously affecting sustainable urban development. Compared with general urban built-up areas, they demonstrate greater vulnerability to rainfall-induced waterlogging due to their obsolete infrastructure and high heritage value, making it imperative to comprehensively enhance their waterlogging resilience. In this study, Qingdao’s historic urban area is selected as a sample case to analyze the interaction between rainfall intensity, the built environment, and population and business characteristics and the mechanism of waterlogging disaster in the historic urban area by combining with the concept of resilience; then construct a resilience assessment system for waterlogging in the historic urban area in terms of dangerousness, vulnerability, and adaptability; and carry out a measurement study. Specifically, the CA model is used as the basic model for simulating the possibility of waterlogging, and the waterlogging resilience index is quantified by combining the traditional research data and the emerging open-source geographic data. Furthermore, the waterlogging resilience and obstacle factors of the 293 evaluation units were quantitatively evaluated by varying the rainfall characteristics. The study shows that the low flooding resilience in the historic city is found in the densely built-up areas within the historic districts, which are difficult to penetrate, because of the high vulnerability of the buildings themselves, their adaptive capacity to meet the high intensity of tourism and commercial activities, and the relatively weak resilience of the built environment to disasters. Based on the measurement results, targeted spatial optimization strategies and planning adjustments are proposed. Full article

Since 2019, China has been promoting the renovation of old urban residential areas built in 2000 or earlier. However, older communities surrounding large urban hospitals face unique challenges, including deteriorating infrastructure, complex social dynamics, and conflicts between tenants and residents. This study focuses on old communities near Xiangya Hospital in Changsha, Hunan Province, employing questionnaire surveys to analyze residential satisfaction and demands across three dimensions: housing spaces, community public spaces, and social relations. Using multilevel linear regression, structural equation modeling, and moderation effect analysis, this research systematically investigates influencing factors and group heterogeneity. The findings reveal that community greening, recreational facilities, and property management are core drivers of residential satisfaction, while social relationships and public spaces play critical mediating roles. Distinct group-specific needs emerged: elderly residents prioritized greening, security, and property management responsiveness; medical students emphasized sound insulation and tenant management; and patients and their families heavily emphasized ventilation and lighting, hygienic conditions, and infrastructure. To address these issues, the study proposes an integrated renewal strategy emphasizing the integration of physical upgrades and soft governance. The findings provide theoretical and practical insights for the systematic renewal of similar older hospital-adjacent communities. Full article