Search Results (280)

Street networks shape urban dynamics. However, at the important meso- and micro-scales, a research limitation remains in systematically linking the spatial logic of streets to the physical configuration of street-level commerce, in particular through an analytical lens that distinguishes between different urban network functions. With a view to overcoming this limitation and extending space syntax theory into the fine-grained analysis of commercial form, this study applies its dual-network logic, contrasting foreground networks and background networks. The spatial patterns of street stores were analyzed across eight street segments in four Chinese cities: Tianjin, Nanjing, Zhengzhou, and Hong Kong. Network types were distinguished using Normalized Angular Choice and patchwork pattern analysis. By using 2019 POI data, Street View imagery, and field surveys, a comparative quantitative analysis was conducted across three metrics: operation methods, functional diversity, and 100-m density. The results indicate differences: chain stores hold a clear advantage in high-value segments of the foreground network, a pattern supported by statistical tests. These segments also exhibit higher functional diversity (mean ENT = 5.12). In contrast, high-value street segments of the background network exhibit a consistently higher prevalence of sole stores. They also have a commercial density approximately 2.6 times greater than that of their foreground counterparts. These findings provide empirical evidence on how foreground and background networks support different kinds of commercial ecologies: one oriented toward micro-economy efficiency and standardized supply, the other toward socio-culturally embedded, high-intensity local exchange. Consequently, by linking specific street spatial configurations to measurable commercial outcomes, this research contributes methodologically by operationalizing the dual-network framework at a novel scale and offering a replicable analytical tool for diagnosing and guiding commercial spatial planning in cities. Full article

Commercial pedestrian streets serve as vital urban public spaces for residents’ daily leisure and social interaction. However, amid rapid urbanization, many such streets exhibit a tendency towards homogenization, raising practical concerns about the capacity of these environments to consistently deliver rich psychological restorative experiences. Existing research on the restorativeness of urban streets has primarily focused on macro or meso scales, leaving the restorative impacts of micro-scale elements, such as public art within streetscapes, insufficiently explored. To address this research gap, this study takes Tanhualin Historic Cultural Street in Wuhan as its research setting. Employing a streetscape image simulation experiment combined with an online questionnaire survey, it assesses the influence of public art on the perceived restorativeness of commercial pedestrian streets. The results indicate that public art substantially enhances the perceived restorative capacity of commercial pedestrian streets. Further analysis reveals clear independent main effects of both the form and theme of public art on perceived restorativeness, with the influence of form being more pronounced, and no statistically significant interaction effect between the two. These findings offer novel insights for enhancing the restorative potential of commercial pedestrian streets and provide design recommendations for future urban street renewal and sustainable development. Full article

Flooding is a recurrent problem in many Brazilian cities, resulting in significant losses that affect health, assets, finance, and the environment. The uncertainty regarding extreme rainfall events due to climate change makes this challenge even more severe, compounded by inadequate urban planning and the occupation of risk areas, particularly for the municipality of Catu, in the state of Bahia, which also suffers from recurrent floods. Critical hotspots include the Santa Rita neighborhood and its surroundings, the main supply center, and the city center—the municipality’s commercial hub. The focus of this research is the unprecedented quantification of the socioeconomic impact of these floods on the low-income population and the region’s informal sector (street vendors). This research focused on analyzing and modeling the destructive potential of intense rainfall in the Santa Rita region (Supply Center) of Catu, Bahia, and its effects on the local economy across different recurrence intervals. A hydrological simulation software suite based on computational and geoprocessing technologies—specifically HEC-RAS 6.4, HEC-HMS 4.11, and QGIS— 3.16 was utilized. Two-dimensional (2D) modeling was applied to assess the flood-prone areas. For the socioeconomic impact assessment, a loss procedure based on linear regression was developed, which correlated the different return periods of extreme events with the potential losses. This methodology, which utilizes validated, indirect data, establishes a replicable framework adaptable to other regions facing similar socioeconomic and drainage challenges. The results revealed that the area becomes impassable during flood events, preventing commercial activities and causing significant economic losses, particularly for local market vendors. The total financial damage for the 100-year extreme event is approximately US $30,000, with the loss model achieving an R² of 0.98. The research concludes that urgent measures are necessary to mitigate flood impacts, particularly as climate change reduces the return period of extreme events. The implementation of adequate infrastructure, informed by the presented risk modeling, and public awareness are essential for reducing vulnerability. Full article

The rapid urbanization of Pleiku City, Vietnam, has led to a sharp increase in the demand for and prices of residential land, creating challenges for urban management and land valuation. This study aims to identify and quantify the key factors influencing residential land prices in Pleiku to provide a scientific basis for land use planning and smart urban development. Data were collected through surveys of 30 state officials involved in land valuation and 250 households living along major streets in Pleiku. Cronbach’s alpha was used to test the reliability of the collected data, and exploratory factor analysis (EFA) was used to identify influencing factor groups. The results show that residential land prices are strongly influenced by multiple factors, with location and infrastructure playing the most decisive roles. Market land prices were found to be approximately 1.5–2 times higher than state-regulated prices. Among the identified factor groups, location and infrastructure had the strongest influence, followed by economic, social, legal, and specific land use factors. Price differences between land plots mainly reflect variations in location, street characteristics, accessibility, and commercial potential. The study concludes that location and infrastructure development are the dominant drivers of residential land prices in Pleiku. These findings have important implications for land valuation, urban planning, and the implementation of smart urban construction policies in rapidly developing cities in Vietnam. Full article

In a situation where cities are increasingly being developed vertically and complexly, a novel approach for analyzing vertical urban functional patterns is proposed. For this purpose, a multi-dimensional GDC (Geo Data Cube) consisting of spatial and temporal data x, y, z, t, and f dimensions containing layer information was created. At this time, the size of the GDC cell (interval in x, y, z dimensions) is calculated by cell point data using the three-dimensional (3D) Moran’s I index value calculated with the 3D Diversity Factor (DF) based on information entropy proposed to reduce the uncertainty of information for each cell. In other words, the cell with the smallest index value was chosen to minimize the influence of Modifiable Areal Unit Problem (MAUP) that occurs when mapping. The 3D land use index (3D LUI) is calculated as a linearly weighted sum of the spatial accessibility of uses between cells (3D KDF) and the enrichment of uses (3D EF), taking into account the first law of geography. Finally, the 3D LUI value for each use was calculated for each cell of the GDC, and the use with the highest value was determined as the urban function of the cell. As a result of applying this to Seocho-gu, Seoul, Republic of Korea (ROK) in June 2024 and visually evaluating it using the street view provided by Kakao Map, it was confirmed that commercial and residential functions were vertically separated in buildings with residential–commercial complexes or shops on the ground floor. It was also confirmed that such characteristics did not appear in the two-dimensional (2D) urban functional patter analysis. Full article

This work presents an experimental assessment of radiative cooling (RC) films and compound parabolic concentrator (CPC) optics integrated into systems relevant for smart cities: LED street luminaires and small photovoltaic (PV) and thermoelectric (TE) modules used as energy-harvesting (EH) sources for IoT devices. Using commercial RC film and simple 2D/3D CPC geometries, we conducted outdoor measurements under realistic conditions. For a commercial LED luminaire, several configurations were compared (painted aluminum reference, full RC coverage of the head, partial RC strips above the LED and driver, and RC combined with CPCs), recording surface temperatures during daytime and nighttime operation. In parallel, single-junction PV cells and Peltier-type TE generators were mounted on aluminum plates in three configurations: reference, RC-coated, RC + 3D-CPC. Their surface temperatures and open-circuit (OC) voltages were monitored in daylight. Across all campaigns, RC consistently reduced device or surface temperatures by a few degrees Celsius compared to the reference, with larger reductions under higher irradiance. For PV and TE modules, thermal differences produced small but measurable increases in OC voltage—percent-level for PV, millivolt-level for TE. CPCs generally preserved or slightly enhanced the cooling effect in some configurations, acting as incremental modifiers rather than primary drivers. The experiments are deliberately exploratory and provide initial experimental evidence that RC integration can be beneficial in real devices. They establish an empirical baseline for future work on long-term, multi-season campaigns, electrical characterization, optimized materials/optics, and system-level prototypes in smart-city lighting and IoT EH applications. Full article

With the ongoing advancement of urbanization, the renewal of old urban areas has emerged as a central front in enhancing urban quality, with street space improvement playing a pivotal role in advancing sustainable urban development. This study focuses on Chengdu, a highly urbanized megacity, employing a combination of multi-point continuous street view photography, spatial mapping, and landscape design interventions to systematically examine human activity patterns, commercial dynamics, and pathways for spatial optimization along the street-facing interfaces of old residential neighborhoods and their adjacent urban streets. The findings reveal that: (1) commercializing the street-facing façades enhances local employment opportunities; (2) window-type fences demonstrate superior adaptability by effectively balancing commercial accessibility with resident safety; and (3) a diverse mix of commercial types sustains the vitality of street-level economies in these areas. These results not only offer actionable spatial strategies for the renovation of old residential zones in Chengdu but also contribute transferable insights for urban regeneration efforts globally. Full article

Heavy metals are widespread environmental contaminants from natural and anthropogenic sources, posing risks to human health and ecosystems. In urban areas, levels are elevated due to industrial activity, traffic emissions, and building materials. Camden, New Jersey, a city with a history of industry and illegal dumping, faces increased risk due to aging sewer and stormwater systems. These systems frequently flood neighborhoods and parks, heightening residents’ exposure to heavy metals. Despite this, few studies have examined metal distribution in Camden, particularly during storm events. This study analyzes stormwater metal concentrations across residential and commercial areas to assess contamination levels, potential sources, and land use associations. Stormwater samples were collected from 33 flooded street locations after four storm events in summer 2023, along with samples from a flooded residential basement during three storms. All were analyzed for total lead, cadmium, and arsenic using inductively coupled plasma–mass spectrometry (ICP-MS, (Department of Chemistry and Biochemistry, Rowan University, Glassboro, NJ, USA)). Concentration data were visualized using geographic information system (GIS)-based mapping in relation to land use, socioeconomic, and public health factors. In Camden’s stormwater, lead levels (1–1164 µg L⁻¹) were notably higher than those of cadmium (0.1–3.3 µg L⁻¹) and arsenic (0.2–8.6 µg L⁻¹), which were relatively low. Concentrations varied citywide, with localized hot spots shaped by environmental and socio-economic factors. Principal component analysis indicates lead and cadmium likely originate from shared sources, mainly industries and illegal dumping. Notably, indoor stormwater samples showed higher heavy metal concentrations than outdoor street samples, indicating greater exposure risks in flooded homes. These findings highlight the spatial variability and complex sources of heavy metal contamination in stormwater, underscoring the need for targeted interventions in vulnerable communities. Full article

To address the limitations of conventional social force models in simulating high-density pedestrian crowds, this study proposes an enhanced model that incorporates visual perception constraints, group-type labeling, and collective avoidance mechanisms. Pedestrian trajectories were extracted from a bidirectional commercial street scenario using OpenCV, with YOLOv8 and DeepSORT employed for multiple object tracking. Analysis of pedestrian grouping patterns revealed that 52% of pedestrians walked in pairs, with distinct avoidance behaviors observed. The improved model integrates three key mechanisms: a restricted 120° forward visual field, group-type classification based on social relationships, and an exponentially formulated inter-group repulsive force. Simulation results in MATLAB R2023b demonstrate that the proposed model outperforms conventional approaches in multiple aspects: speed distribution (error < 8%); spatial density overlap (>85%); trajectory similarity (reduction of 32% in Dynamic Time Warping distance); and avoidance behavior accuracy (82% simulated vs. 85% measured). This model serves as a quantitative simulation tool and decision-making basis for the planning of pedestrian spaces, crowd organization management, and the optimization of emergency evacuation schemes in high-density pedestrian areas such as commercial streets and subway stations. Consequently, it contributes to enhancing pedestrian mobility efficiency and public safety, thereby supporting the development of a sustainable urban slow transportation system. Full article

In the 21st century, Saudi cities have witnessed a high rate of private car ownership, averaging 1.38 vehicles per family. This has significantly increased demand for parking in residential areas, leading to unregulated parking behaviors that negatively affect street and sidewalk infrastructure. Although some research has been conducted in Saudi Arabia on illegal parking in commercial streets, research on unregulated parking in residential streets remains underexplored. This study investigates the impact of unregulated parking behavior on street and sidewalk infrastructure in residential districts with apartment zones in Jeddah, Saudi Arabia, determining the extent to which current sidewalk strips have been modified to extend on-street parking, create front setbacks for parking, and provide access to ground-floor private parking and residential building entrances. We selected six typical apartment building zones and mapped parking behavior through direct observations, processing collected data through ArcGIS. Our findings reveal negative impacts, resulting in significant parts of sidewalks, front setbacks, and streets being used for parking, thereby creating unhealthy and unsafe residential areas for walking and other physical activities. This study offers a comprehensive understanding of the unregulated parking problem and its subsequent impact on residents’ quality of life, particularly in terms of walking accessibility and safety. Full article

This study investigated the perceptions of AAW among educators (n = 47), students (n = 359), and aquaculture sector stakeholders (n = 34) in key aquaculture regions of South and South-Central Vietnam. Using a mixed-methods survey, perception scores, understanding of core welfare concepts, curricular coverage, and willingness to pay (WTP) for higher-welfare products were assessed. Although perception scores were high across surveyed groups, only 5.57% of students identified most of the Five Freedoms of Animal Welfare, while 17.0% showed no understanding of welfare. This highlighted a gap between awareness and understanding, leading to the development of the Awareness Depth Gap Framework. A small but statistically significant negative correlation (Kendall–Theil –Sen slope = −0.28, p < 1.25 × 10⁻¹²) indicated that greater AAW curricular inclusion was associated with stronger welfare attitudes. Willingness to pay modest premiums (6–10%) for higher-welfare products increased non-linearly with higher perception scores among educators and students. In contrast, aquaculture sector stakeholders appeared to prioritise economic factors over welfare. These results highlight the need for structured AAW curricula and community collaborative education to close knowledge gaps. This study provides the first empirical insights into AAW perceptions across the education and aquaculture sectors in Vietnam. Full article

This study examines how platformized e-commerce logistics reshapes urban land use at the neighborhood scale, using Shanghai as an empirical case. It argues that last-mile logistics infrastructure operates through two intertwined mechanisms: as physical service nodes that generate localized pedestrian flows sustaining neighborhood retail, and as neighborhood-level execution points within a digitally coordinated logistics system that produces citywide substitution pressures and restructures commercial spaces, particularly community-oriented shopping malls. Theoretically, the study advances platform and logistics urbanism by reconceptualizing last-mile infrastructure as a dual-role urban system with scale-dependent land-use effects. Methodologically, it combines street-segment regression analysis with shopping-mall case studies to link logistics proximity to fine-grained spatial outcomes. Empirically, the findings reveal complementary effects for street retail alongside accelerated restructuring and functional repurposing in community malls—patterns not captured by uniform displacement models. Planning analysis further identifies a governance mismatch in Shanghai’s 2017–2035 Master Plan, underscoring the need for platform-responsive planning to address emerging hybrid commercial–logistics spaces. Full article

Recognizable and distinctive streets are essential not only for navigation but also for fostering place identity and therefore socio-environmental sustainability in cities. The recognition depends on both high-level visual features (e.g., buildings, trees, etc.) and low-level ones (e.g., colors, spatial frequencies, etc.). While the former has been examined extensively, the latter remains less understood. This study addresses this gap via a multi-disciplinary perspective, by exploring how low-level visual features influence attention and cognitive processing during street recognition using an eye-tracking device. In the experiment, participants were expected to recognize Huaihai Road in China from other historic, tree-shaded, commercial streets with similar appearance (e.g., the Champs-Élysées in France, Omotesando in Japan, and Shaanxi South Road and Fuxing Middle Road in China). Results showed that removing mid-to-high spatial frequencies significantly improved recognition accuracy, while the absence of color led to a notable decline in accuracy. Markedly, the presence or absence of trees did not significantly affect recognition accuracy, suggesting that trees may be not vital for street recognition. These findings underscore the importance of global visual cues and color in the recognition process and provide practical computational design insights for urban distinctiveness and cultural sustainability. Full article

In historic and cultural districts characterized by the coexistence of residential and commercial functions, street spaces play a pivotal role in shaping urban cultural continuity and local identity. They simultaneously support the daily lives and emotional attachment of residents while accommodating the tourism activities of visitors. Despite this dual significance, the distinct functional and experiential expectations of residents and tourists have resulted in multidimensional perceptual differences, which have not been sufficiently addressed in previous studies yet are crucial for enhancing street space quality. Using the Sajinqiao Historic and Cultural District in Xi’an, China, as a case study, this research develops a perceptual evaluation system for street spaces and applies an enhanced IPA-KANO model to examine variations in explicit importance, attribute performance, and implicit importance between residents and tourists. Findings indicate that residents attach greater importance to religious sites, community facilities, and cultural belonging, whereas tourists prioritize transport accessibility, iconic architecture, and commercial vibrancy. Both groups expressed relatively low satisfaction with several key cultural experience elements. Based on these results, this study proposes targeted optimization strategies for elements identified as highly important yet underperforming, providing a practical framework for balancing heritage conservation with contemporary tourism development in such integrated urban environments. Full article

Public spaces in peri-urban towns are becoming key focal points of urban regeneration in China due to their geographic advantages, resource endowments, and diverse populations. Substantial investments have been made to improve residents’ living environments and well-being. As over-commercialized urban centers increasingly face congestion and homogenization, the distinctive landscapes and authentic everyday life of peri-urban towns are attracting growing attention from tourists. Understanding both residents’ and visitors’ perceptions of these public spaces is therefore essential for successful regeneration. This study examines Nanquan Street, which lies ina peri-urban heritage town in Wuxi, Jiangnan region, China. Drawing on user-generated content from major Chinese social media platforms (Xiaohongshu and Dianping) and field observations guided by the AEIOU framework, a three-stage grounded theory approach was employed to identify the key factors influencing user satisfaction. The analysis identified twelve sub-dimensions grouped into three overarching categories: foundational preconditions, social developmental factors, and spatial-operational factors, which collectively shape sustained satisfaction in Peri-urban heritage towns. By translating the satisfaction model into sustainable design strategies, this study proposes a set of renewal pathways applicable not only to Nanquan Street but also to similar peri-urban towns facing comparable challenges. Emphasizing multi-user experience, low-intervention strategies, and contextual adaptability, this research contributes to theoretical understandings of sustainable renewal in peri-urban towns. It provides actionable guidance for balancing everyday life, cultural heritage, and sustainable tourism development. Full article