Search Results (659)

While the explosive growth in e-commerce stresses urban logistics systems, city planners lack of fine-grained data in order to anticipate and manage the resulting freight flows. Using a three-stage analytical approach combining descriptive zonal statistics, hotspot analysis and different regression modeling from univariate to geographically weighted regression, this study integrates one year of parcel deliveries from a leading courier with open spatial layers of land-use zoning, census population, mobile-signal activity and household income to model last-mile demand across different land use types. A baseline linear regression shows that residential population alone accounts for roughly 30% of the variance in annual parcel volumes (2.5–3.0 deliveries per resident) while adding daytime workforce and income increases the prediction accuracy to 39%. In a similar approach where coefficients vary geographically with Geographically Weighted Regression to capture the local heterogeneity achieves a significant raise of the overall R² to 0.54 and surpassing 0.70 in residential and institutional districts. Hot-spot analysis reveals a highly fragmented pattern where fewer than 5% of blocks generate more than 8.5% of all deliveries with no apparent correlation to the broaden land-use classes. Commercial and administrative areas exhibit the greatest intensity (1149 deliveries per ha) yet remain the hardest to explain (global R² = 0.21) underscoring the importance of additional variables such as retail mix, street-network design and tourism flows. Through this approach, the calibrated models can be used to predict city-wide last-mile demand using only public inputs and offers a transferable, privacy-preserving template for evidence-based freight planning. By pinpointing the location and the land uses where demand concentrates, it supports targeted interventions such as micro-depots, locker allocation and dynamic curb-space management towards more sustainable and resilient urban-logistics networks. Full article

The Latin American and Caribbean (LAC) region faces persistent challenges of inequality, climate change vulnerability, and deteriorating air quality. The Aburrá Valley, where Medellín is located, is a narrow tropical valley with complex topography, strong thermal inversions, and unstable atmospheric conditions, all of which exacerbate the accumulation of pollutants. In Medellín, ${\mathrm{NO}}_2$ concentrations have remained nearly unchanged over the past eight years, consistently approaching critical thresholds, despite the implementation of air quality control strategies. These persistent high concentrations are closely linked to the variability of the atmospheric boundary layer (ABL) and are often intensified by prolonged dry periods. This study focuses on a representative street canyon in Medellín that has undergone recent urban interventions, including the construction of new public spaces and pedestrian areas, without explicitly considering their impact on ${\mathrm{NO}}_x$ dispersion. Using Computational Fluid Dynamics (CFD) simulations, this work evaluates the influence of urban morphology on ${\mathrm{NO}}_x$ accumulation. The results reveal that areas with high Aspect Ratios (AR > 0.65) and dense vegetation exhibit reduced wind speeds at the pedestrian level—up to 40% lower compared to open zones—and higher ${\mathrm{NO}}_2$ concentrations, with maximum simulated values exceeding 50 μg/m³. This study demonstrates that the design of pedestrian corridors in complex urban environments like Medellín can unintentionally create pollutant accumulation zones, underscoring the importance of integrating air quality considerations into urban planning. The findings provide actionable insights for policymakers, emphasizing the need for comprehensive modeling and field validation to ensure healthier urban spaces in cities affected by persistent air quality issues. Full article

The use of multimodal data can effectively compensate for the lack of temporal resolution in streetscape imagery-based studies and achieve hourly refinement in the study of street walkability dynamics. Exploring the 24 h dynamic pattern of urban street walkability and its diurnal variation characteristics is a crucial step in understanding and responding to the accelerated urban metabolism. Aiming at the shortcomings of existing studies, which are mostly limited to static assessment or only at coarse time scales, this study integrates multimodal data such as streetscape images, remote sensing images of nighttime lights, and text-described crowd activity information and introduces a novel approach to enhance the simulation of pedestrian perception through a visual–textual multimodal deep learning model. A baseline model for dynamic assessment of walkability with street as a spatial unit and hour as a time granularity is generated. In order to deeply explore the dynamic regulation mechanism of street walkability under the influence of diurnal shift, the 24 h dynamic score of walkability is calculated, and the quantification system of walkability diurnal change characteristics is further proposed. The results of spatio-temporal cluster analysis and quantitative calculations show that the intensity of economic activities and pedestrian experience significantly shape the diurnal pattern of walkability, e.g., urban high-energy areas (e.g., along the riverside) show unique nocturnal activity characteristics and abnormal recovery speeds during the dawn transition. This study fills the gap in the study of hourly street dynamics at the micro-scale, and its multimodal assessment framework and dynamic quantitative index system provide important references for future urban spatial dynamics planning. Full article

Nomadic heritage villages constitute significant material cultural heritage. Under China’s cultural revitalization and rural development strategies, these villages face spatial degradation driven by tourism and urbanization. Current research predominantly employs isolated analytical approaches—space syntax often overlooks social dynamics while social network analysis (SNA) overlooks physical interfaces—hindering the development of holistic solutions for socio-spatial resilience. This study proposes a multi-scale integrated assessment framework combining social network analysis (SNA) and space syntax to systematically evaluate public space structures in traditional nomadic villages of Xinjiang. The framework provides scientific evidence for optimizing public space design in these villages, facilitating harmonious coexistence between spatial functionality and cultural values. Focusing on three heritage villages—representing compact, linear, and dispersed morphologies—the research employs a hierarchical “village-street-node” analytical model to dissect spatial configurations and their socio-functional dynamics. Key findings include the following: Compact villages exhibit high central clustering but excessive concentration, necessitating strategies to enhance network resilience and peripheral connectivity. Linear villages demonstrate weak systemic linkages, requiring “segment-connection point supplementation” interventions to mitigate structural elongation. Dispersed villages maintain moderate network density but face challenges in visual integration and centrality, demanding targeted activation of key intersections to improve regional cohesion. By merging SNA’s social attributes with space syntax’s geometric precision, this framework bridges a methodological gap, offering comprehensive spatial optimization solutions. Practical recommendations include culturally embedded placemaking, adaptive reuse of transitional spaces, and thematic zoning to balance heritage conservation with tourism needs. Analyzing Xinjiang’s unique spatial–social interactions provides innovative insights for sustainable heritage village planning and replicable solutions for comparable global cases. Full article

As a catalyst for sustainable urbanization, urban vibrancy drives human interactions, economic agglomeration, and resilient development through its spatial manifestation of diverse activities. While previous studies have emphasized the connection between built environment features—especially street network centrality—and urban vibrancy, the broader mechanisms through which the full spectrum of street configuration dimensions shape vibrancy patterns remain insufficiently examined. To address this gap, this study applies a GeoXAI approach that synergizes random forest modeling and GeoShapley interpretation to reveal the influence of street configuration on urban vibrancy. Leveraging multi-source geospatial data from Xiamen Island, China, we operationalize urban vibrancy through a composite index derived from three-dimensional proxies: life service review density, social media check-in intensity, and mobile device user concentration. Street configuration is quantified through a tripartite measurement system encompassing network centrality, detour ratio, and shape index. Our findings indicate that (1) street network centrality and shape index, as well as their interactions with location, emerge as the dominant influencing factors; (2) The relationships between street configuration and urban vibrancy are predominantly nonlinear, exhibiting clear threshold effects; (3) The impact of street configuration is spatially heterogeneous, as evidenced by geographically varying coefficients. The findings can enlighten urban planning and design by providing a basis for the development of nuanced criteria and context-sensitive interventions to foster vibrant urban environments. Full article

In the context of rapid urbanization, urban streets have become critical spatial environments for children’s daily activities, directly influencing their mobility safety, behavioral development, and the spatial equity of cities. However, conventional assessment methods largely rely on subjective surveys and qualitative analyses, lacking objectivity and scalability. To address these limitations, this study takes urban streets in Shanghai as a case study and integrates deep learning technologies to propose a generalizable methodology for developing a child-friendliness evaluation and enhancement system that incorporates multi-source data and perceptual indicators for urban streets. The system extracts spatial features of streets based on urban street environmental information, and incorporates evaluation inputs from intergenerational user groups, including children and their caregivers. A neural network model is trained to enable automated, multidimensional assessment of child-friendliness and to generate context-sensitive and adaptable strategies. The findings reveal significant perceptual differences between user groups: children place greater emphasis on playfulness and interactivity, while caregivers prioritize safety and comfort. This validates the necessity and effectiveness of adopting an intergenerational collaborative perspective for comprehensive child-friendliness evaluation. By overcoming the limitations of traditional approaches in terms of accuracy and efficiency, this research expands the methodological repertoire of child-friendly urban studies and provides data-driven support for the intelligent design and inclusive governance of urban streets. Full article

The article analyzes the meanings embedded in street art in Florence that portrays women, likely created by female artists. Between 18 May and 27 May 2024, during the Communities and Artistic Participation in Hybrid Environment (CAPHE) project, we observed a significant number of feminist street art pieces in Florence’s historic center. Using qualitative content analysis based on Gillian Rose’s methodology (2016), we interpreted the collected visual materials through semiotic and socio-cultural lenses. The findings revealed the deliberately interventionist nature of the analyzed works, addressing themes such as gender inequality, human rights, violence against women, and cultural stereotypes. This street art serves as a social manifesto and a means of activating both the local community and tourists, aligning with global feminist discourse while addressing Florence’s local issues. We conclude that Florence’s street art provides a space for visual resistance, education, and the promotion of gender equality and women’s emancipation in the context of contemporary social challenges. Full article

Air pollution is one of the most serious environmental threats, with particulate matter PM₁₀ and PM_2.5 representing its most harmful components, significantly affecting public health. These particles are primarily generated by transport, industry, residential heating, and agriculture, and are associated with increased incidence of respiratory and cardiovascular diseases, asthma attacks, and heart attacks, as well as chronic illnesses and premature mortality. The most vulnerable groups include children, the elderly, and individuals with pre-existing health conditions. This study focuses on the analysis of health risks associated with PM₁₀ and PM_2.5 air pollution in the city of Zvolen, which serves as a representative case due to its urban structure, traffic load, and industrial activity. The aim is to assess the current state of air quality, identify the main sources of pollution, and evaluate the health impacts of particulate matter on the local population. The results will be compared with selected Slovak cities—Banská Bystrica and Ružomberok—to understand regional differences in exposure and its health consequences. The results revealed consistently elevated concentrations of particulate matter (PM) across all analyzed cities, frequently exceeding the guideline values recommended by the World Health Organization (WHO), although remaining below the thresholds set by current national legislation. The lowest average concentrations were recorded in the city of Zvolen (PM₁₀: 20 μg/m³; PM_2.5: 15 μg/m³). These lower values may be attributed to the location of the reference monitoring station operated by the Slovak Hydrometeorological Institute (SHMÚ), situated on J. Alexy Street in the southern part of the city—south of Zvolen’s primary industrial emitter, Kronospan. Due to predominantly southerly wind patterns, PM particles are transported northward, potentially leading to higher pollution loads in the northern areas of the city, which are currently not being monitored. We analyzed trends in PM₁₀ and PM_2.5 concentrations and their relationship with hospitalization data for respiratory diseases. The results indicate a clear correlation between the concentration of suspended particulate matter and the number of hospital admissions due to respiratory illnesses. Our findings thus confirm the significant adverse effects of particulate air pollution on population health and highlight the urgent need for systematic monitoring and effective measures to reduce emissions, particularly in urban areas. Full article

YouthMappers chapters, utilizing OpenStreetMap (OSM), play a pivotal role in tackling climate challenges through education and activism. This study investigates the influence of a booster grant project on enhancing Climate Activism and Education efforts through YouthMappers chapters in Sri Lanka. Through a geometric approach, the research integrates measurable survey data from OSM platform data from 223 YouthMappers chapter respondents at four (04) universities in Sri Lanka to evaluate five critical factors/dimensions: Capacity Building and Funding Support (CBFS), Climate Activism and Education (CAE), Community Engagement and Collaboration (CEC), Technical Skills and Resources (TSR), and Sustainability and Policy Integration (SPI). The Friedman test confirmed statistically significant differences across all factors’ variables (p < 0.001), highlighting strengths in technical competence and educational integration, with gaps identified in community engagement and sustainability. A Radial Basis Function (RBF) model revealed moderate predictive accuracy, excelling in variables like CAE and TSR but indicating higher error rates in SPI and CEC. Practical outcomes include flood risk maps, curriculum-integrated teaching schemes, and localized mapping workshops. These results underscore the booster grant’s role in enabling impactful, youth-led geospatial initiatives. However, challenges such as internet access, training gaps, and language barriers remain. This study recommends expanding student and community participation, refining training strategies, and integrating OSM into university curricula. These scalable interventions offer valuable insights for replication in other vulnerable regions, enhancing climate resilience through community-driven, data-informed youth engagement. Full article

This study investigates the Roman land division system, centuriation, using LIDAR data and historical data to understand the landscape during the Roman period, in this case between Roman cities such as Siscia and Andautonia. LIDAR data analysis provided evidence of the preservation of the Roman centuriation system in the present day Turopoljski Lug forest. The azimuth suggests that centuriation aligned with Siscia’s ager, while the precise territorial limits between the two agers remain unclear. Additionally, the orientation of Siscia’s streets and the alignment of modern roads like Zagrebačka street suggest continuity of the Roman road system. The research also sheds light on the agricultural nature of the region in the Roman period, challenging traditional views of Turopolje as a marshy, forested area from prehistoric periods. The presence of Roman-era drainage systems and the re-evaluation of the historical landscape indicate that the region was actively cultivated. The study also discusses the abandonment of the centuriation system after the Roman period and its subsequent transformation into forested land. Future research should focus on the exact borders between the agers of Siscia and Andautonia and the ongoing influence of Roman land division on later historical landscapes. Full article

Climate change today is considered one of the most severe global problems. Additionally, it is inherently linked to sustainable development, particularly considering that it is a widespread problem affecting virtually all regions, countries, and continents. Therefore, it is essential to monitor its perception and behaviours towards it. Hence, there is the need for a diagnosis of climate-change attitudes found in various parts of the world. This premise is the foundation for the original study reported in the article. It offers the results of a survey of 300 adult rural residents from southeastern Poland. The article aims to diagnose the respondents’ attitudes towards climate change in the context of sustainable development premises. Respondents’ opinions on the potential activities their local communities could take to be more sustainable are a substantial part of the results. The most common suggestions were low-emission public transport (in the Wadowice District, it was 55% of responses) and road and street redesign to promote safe cycling and walking environments (in the Kraków and Tarnów Districts, over 50% of responses). The respondents found the promotion of sustainable development among youth and older people to be the least important (in three out of five districts, this percentage did not exceed 20%). The other thematic block was specific environmental protection and sustainable development activities that society should prioritise over a five-year horizon. The participants considered the development of new ways to eliminate waste in total production (in the Tarnów District, over 73% of responses), new technologies to curb the carbon footprint and GHG emissions (over 63% in the Wadowice District), and new technologies to scrape and monitor air pollutants (approx. 70% in the Kraków District). Full article

The prevalence of car dependence and sedentary lifestyles has created concern in the transportation and health sectors. Walking is the most popular and practical kind of exercise that can significantly enhance health. In Chile, more than half of older adults have health issues and almost 72% of the elderly population never engages in physical activity. This study aims to investigate the relationship between older adults’ walking behavior and the built environment along the streets and parks in Santiago’s middle-income neighborhoods. Six medium-income central and pericentral neighborhoods of Santiago were selected. The average number of older persons who walk along the paths and two modified audit forms were used to measure walking behavior and built environment features, respectively. Both correlation analysis and backward regression were used to examine the associations. While elements like the existence of bus stops, pedestrian streets, and general cleanliness contribute to the enhanced number of older adults who walk along street segments, the presence of insecurity signs was found to be negatively associated with the number of older adults who walk in the neighborhood parks. Furthermore, complexity and mystery showed a negative association with the number of older adults in the neighborhood parks. Urban policymakers might use these findings to encourage older adults to walk more in Santiago’s medium-income neighborhoods. Full article

Urban green spaces (UGSs) play a pivotal role in sustaining the livelihoods of urban dwellers. This study sought to explore the impact of UGSs on livelihoods in Bulawayo and Johannesburg cities. A mixed-methods approach was used to develop a nuanced understanding of the nexus between UGSs and the livelihoods of the residents. A questionnaire survey (n = 658) with 329 participants from each city and 20 interviews were used to gather and generate data. Twelve types of UGSs were identified, with a relatively large proportion of the participants recognizing informal recreational areas as the common type of urban green space (UGS) in both cities. Domestic gardens, cemeteries, parks, woodlands, institutional green spaces, street trees, wastelands, commonages, and green roofs were other green spaces in both cities. Economically, job opportunities emerged in areas such as selling wares, photography, and the collection of firewood and wild fruits for sale. Likewise, farming activities and property values increased. Socially, they were valuable recreation and leisure spots for picnicking, dog walking, dating escapades, mental and spiritual wellness as well as education. Environmentally, UGSs were special in terms of medicinal provisions and aesthetics. However, urbanization and encroachment are undermining the extent of livelihood benefits. Therefore, it is imperative to revitalize UGSs by instituting robust partnerships and collaboration between government agencies, mobilize resources and expertise, value addition to existing UGSs, rigorous education to promote better appreciation, inclusion of the locals in the design process so that green spaces meet their needs and priorities, and establishing effective maintenance and management systems that ensure sustainability of UGSs. Full article

Objective: The purpose of this study was to investigate the association of built environment and intrapersonal factors with leisure-time physical activity (LTPA), and the possible moderating effect of intrapersonal factors on the association between the built environment and LTPA. Methods: A total of 514 older people in the village of Fuwen were included in this study. Data on LTPA, intrapersonal factors (social, fitness, medical, benefits/challenges, recognition), and the built environment (traffic safety, street connectivity, walking facilities, access to services, crime safety, aesthetics, residential density, land use mix diversity) were collected. Multivariate linear regression analysis with the “enter” method was conducted to analyze the association of perceived scores of built environment and intrapersonal factors with LTPA. Results: Among the intrapersonal factors, fitness was positively related to LTPA (p = 0.012). Among the built environment factors, traffic safety (p = 0.02) and crime safety (p = 0.047) were positively related to LTPA, while walking facilities was negatively associated with LTPA (p = 0.007). Additionally, fitness had a significant moderating effect on the association between walking facilities and LTPA (p = 0.025). Conclusions: Older people with higher fitness requirements and better perceived traffic safety and crime safety tend to engage in greater levels of LTPA. The findings provide valuable insights for policymakers, particularly in designing ecologically livable villages that promote physical activity among older populations. Full article

Traffic congestions due to construction and maintenance works of road infrastructure cause travel delays, unpredictability and less tolerant road users. Bicyclists are more flexible with road closures, shifting to alternative routes, public transport and other active transport depending on the infrastructure, quality and transport services. However, the mixed traffic environment near road closures increases the safety risks for bicyclists. Traditional traffic monitoring systems rely on costly and demanding intrusive sensors. The application of wireless sensors and machine learning algorithms can enhance the analysis and prediction ability of traffic distribution and characteristics in the proximity of road closures. This paper applies artificial neural networks (ANNs) coupled with a Generalised Delta Rule (GDR) algorithm to analyse the sensor traffic data before, during and after the closure of the Mill Road Bridge in Cambridge City in the United Kingdom. The ANN models show that the traffic volume of motorbikes (44%) and buses (34%) and the proximity of Mill Road Bridge (39%) are significant factors affecting bicycle traffic before the closure. During the bridge closure, the proximity of the bridge (99%) and traffic volume of large rigid vehicles (51%) are the most important factors of bicycle distribution in nearby streets leading cyclists to unsafe detours. After the reopening of the Mill Road Bridge, unclear signage caused continued traffic impact, with motorbikes (17%) and large vehicles (24%) playing the most significant role in the spatial distribution of bicycle traffic. This paper emphasises safety concerns from mixed traffic and highlights the importance of cost-effective sensor-based traffic monitoring and analysis of the sensor data using neural networks. Full article