Search Results (355)

Walking benefits older pedestrians but exposes them to traffic crashes. With an aging population, designing age-friendly cities is crucial, yet research on older pedestrian safety at a micro-level is limited. This study aims to reduce older pedestrian–vehicle collisions and create more livable environments through infrastructure policies derived from statistical data analysis. Special attention is focused on collecting a holistic set of infrastructure variables to reflect most of the street built environment elements, which helps policymakers implement short-term safety measures. Using Bayesian Poisson regression, this study analyzes factors contributing to the occurrence of crashes involving older and non-older pedestrians on road segments in Madrid, Spain. The results indicate that different factors affect the occurrence of crashes for all pedestrians versus older pedestrians specifically. Traffic crashes involving all pedestrians are affected by leisure points of interest, bus stops, and crosswalk density. Older pedestrian traffic crashes are influenced by population density, the presence of trees and trash containers, and contour complexity. Proposed measures include relocating trees and trash containers, modifying bus stops, and adding crosswalks and traffic lights. This paper also shows that these countermeasures, aimed at creating age-friendly streets for older pedestrians, are not expected to worsen the road safety of other pedestrians. Full article

In rapid urbanization, the socio-spatial environment between inner-city functional areas faces numerous challenges. Assessing and enhancing the environmental quality of these areas has become an urgent research issue. This study quantitatively evaluates the social-spatial environment of inner-city transitional edges, selecting Chongqing’s Yuzhong District as the case study area. It explores the relationship between spatial environmental factors and social activities. Integrating spatial data, internet “big” data, and field survey data, a multidimensional evaluation of the quality of the social-spatial environment framework is constructed, encompassing four dimensions: connectivity, social function, comfort, and conviviality. Subsequently, a multiple linear regression model is used to explore the main environmental factors influencing social activities on transitional edges. The results show that the density of street trees, lighting facilities, functional density, and functional diversity significantly impact social activities, demonstrating the correlation between the spatial environment of inner-city transitional edges and social activities. Corresponding optimization strategies for each dimension in transitional edges are then summarized. This study provides references for coordinating inner-city functional areas, optimizing urban environments, and promoting sustainability. It can also be applied to a broader range of transitional edge evaluation studies. Full article

The study of light pollution is a relatively new and specific field of measurement. The current literature is dominated by articles that describe the use of ground and satellite data as a source of information on light pollution. However, there is a need to study the phenomenon on a microscale, i.e., locally within small locations such as housing estates, parks, buildings, or even inside buildings. Therefore, there is an important need to measure light pollution at a lower level, at the low level of the skyline. In this paper, the authors present a new drone design for light pollution measurement. A completely new original design for an unmanned platform for light pollution measurement is presented, which is adapted to mount custom sensors (not originally designed to be mounted on a unmanned aerial vehicles) allowing registration in the nadir and zenith directions. The application and use of traditional photometric sensors in the new configuration, such as the spectrometer and the sky quality meter (SQM), is presented. A multispectral camera for nighttime measurements, a calibrated visible-light camera, is used. The results of the unmanned aerial vehicle (UAV) are generated products that allow the visualisation of multimodal photometric data together with the presence of a geographic coordinate system. This paper also presents the results from field experiments during which the light spectrum is measured with the installed sensors. As the results show, measurements at night, especially with multispectral cameras, allow the assessment of the spectrum emitted by street lamps, while the measurement of the sky quality depends on the flight height only up to a 10 m above ground level. Full article

Large-scale gridded population product datasets have become crucial sources of information for sustainable development initiatives. However, mainstream modeling approaches (e.g., dasymetric mapping based on Multiple Linear Regression or Random Forest Regression) do not consider the heterogeneity and multiscale characteristics of the spatial relationships between influencing factors and populations, which may seriously degrade the accuracy of the prediction results in some areas. This issue may be even more severe in large-scale gridded population products. Furthermore, the lack of detailed 3D human settlement data likewise poses a significant challenge to the accuracy of these data products. The emergence of the unprecedented Global Human Settlement Layer (GHSL) data package offers a possible solution to this long-standing challenge. Therefore, this study proposes a new Gridded Population Mapping (GPM) method that utilizes the Multiscale Geographically Weighted Regression (MGWR) model in conjunction with GHSL-3D Building, POI, nighttime light, and land use/cover datasets to disaggregate population data for third-level administrative units (districts and counties) in mainland China into 100 m grid cells. Compared to the WorldPop product, the new population map reduces the mean absolute error at the fourth-level administrative units (townships and streets) by 35%, 51%, and 13% in three test regions. The proposed mapping approach is poised to become a crucial reference for generating next-generation global demographic maps. Full article

The Internet of Things refers to a network of interconnected devices, objects, and systems, that can interact with one another without human intervention. The adoption of IoT technology has expanded rapidly, significantly impacting various fields, including smart healthcare, intelligent transportation, agriculture, and smart homes. This paper focuses on smart street lighting, which represents the core piece of the smart city and the key public service for citizens’ safety. Nevertheless, it poses substantial challenges related to energy consumption, especially during energy crises. This work aims to provide an advanced solution that enables intelligent control of street lighting, enhances human safety, reduces CO₂ emissions and light pollution, and optimizes energy consumption, as well as facilitates maintenance of the lighting network. The solution is twofold: First, it introduces IoT-based smart street lighting referential models; second, it presents a framework for controlling smart street lighting based on the referential models. The proposal uses an IoT-based fuzzy multi-agent systems approach to address the challenges of smart street lighting. The approach leverages the strengths and properties of fuzzy logic and multi-agent systems to address the system requirements. This is illustrated through a testbed case study conducted on a concrete IoT prototype. Full article

Connected cooperative and automated (CAM) vehicles and self-driving cars need to achieve robust and accurate environment understanding. With this aim, they are usually equipped with sensors and adopt multiple sensing strategies, also fused among them to exploit their complementary properties. In recent years, artificial intelligence such as machine learning- and deep learning-based approaches have been applied for object and pedestrian detection and prediction reliability quantification. This paper proposes a procedure based on the YOLOv8 (You Only Look Once) method to discover objects on the roads such as cars, traffic lights, pedestrians and street signs in foggy weather conditions. In particular, YOLOv8 is a recent release of YOLO, a popular neural network model used for object detection and image classification. The obtained model is applied to a dataset including about 4000 foggy road images and the object detection accuracy is improved by changing hyperparameters such as epochs, batch size and augmentation methods. To achieve good accuracy and few errors in detecting objects in the images, the hyperparameters are optimized by four different methods, and different metrics are considered, namely accuracy factor, precision, recall, precision–recall and loss. Full article

This paper addresses the growing importance of efficient street lighting management, driven by rising electricity costs and the need for municipalities to implement cost-effective solutions. Central to this study is the UNI 11248 Italian regulation, which extends the European EN 13201-1 standard introduced in 2016. These standards provide guidelines for designing, installing, operating, and maintaining lighting systems in pedestrian and vehicular traffic areas. Specifically, the UNI 11248 standard introduces the possibility to dynamically adjust light intensity through two alternative operating modes: (a) Traffic Adaptive Installation (TAI), which dims the light based solely on real-time traffic flow measurements; and (b) Full Adaptive Installation (FAI), which, in addition to traffic measurements, also requires evaluating road surface luminance and meteorological conditions. In this paper, we first present the general architecture and operation of an FAI-enabled lighting infrastructure, which relies on environmental sensors and a heterogeneous wireless communication network to connect intelligent, remotely controlled streetlights. Subsequently, we examine large-scale, in-field FAI infrastructures deployed in Vietnam and Italy as case studies, providing substantial measurement data. The paper offers insights into the measured energy consumption of these infrastructures, comparing them to that of conventional light-control strategies used in traditional installations. The measurements demonstrate the superiority of FAI as the most efficient solution. Full article

Urban Vitality (UV) is a critical indicator for measuring sustainable urban development and quality. It reflects the dynamic interactions and supply–demand coordination within urban systems, especially concerning the human–land relationship. This study aims to quantify the UV of Luohe City, China, for the year 2023, analyze its spatial characteristics, and investigate the driving patterns of socio-ecological land functions on UV intensity and heterogeneity under different scenarios. Utilizing multi-source data, including human mobility data from Baidu Location-Based Services (LBSs), Landsat-9, MODIS, and diverse geo-information datasets, we conducted factor screening and comprehensive assessments. Firstly, Self-Organizing Maps (SOMs) were employed to identify typical activity patterns, and the Urban Vitality Index (UVI) was calculated based on Human Mobility Intensity (HMI) data. Subsequently, a framework for quantity–quality–structure assessments weighted and aggregated sub-indicators to evaluate the Land Social Function (LSF) and Land Ecological Function (LEF). Following the screening process, a Multi-scale Geographically Weighted Regression (MGWR) was applied to analyze the scale and driving relationships between UVI and the land assessment sub-indicators. The results were as follows: (1) The UV distribution in Luohe City was highly uneven, with high vitality areas concentrated within the built-up regions. (2) UV showed significant correlations with both LSF and LEF. The influence of LSF on UV was stronger than that of LEF, with the effectiveness of LEF relying on the well-established provisioning of LSF. (3) Artificial Surface Ratio (ASR) and Corrected Night Lights (LERNCI) were identified as key drivers of UV across multiple scenarios. Under the weekend scenario, the Green Space Ratio (GSR) and the Vegetation Quality (VQ) notably enhanced the attractiveness of human activities. (4) The impacts of drivers varied at the urban, township, and street scales. The analysis focuses on factors with significant bandwidth changes across multiple scenarios: VQ, Remote-Sensing-based Ecological Index (RSEI), GSR, ASR, and ALSI. This study underscores the importance of socio-ecological land functions in enhancing urban vitality, offering valuable insights and data support for urban planning. Full article

Understanding a community’s place attachment is vital for effective land-use planning and disaster risk management that aligns with local needs and priorities. This study examines the methodologies employed to grasp these values, emphasising the significance of meaningful participatory approaches. It sheds light on the challenges encountered due to COVID-19 restrictions, which prevented direct face-to-face engagement with community members. To address this issue, researchers devised “digital walking tours” as an alternative to traditional walking transect methods, aiming to investigate the relationship between place attachment and perceptions of the landscape in Patreksfjörður, a small fishing community in the Westfjords, during the pandemic. The evaluation of this method demonstrated its suitability for conducting comprehensive and cost-effective community consultations. Participants expressed enjoyment and found the technology (online video calls and StreetView imagery) user-friendly and engaging. To further enhance the method, several recommendations are proposed, including the integration of virtual tours with in-person methods whenever feasible, incorporating additional sensory input, adopting a slower pace, and offering more opportunities for participants to divert to personally significant locations. Other contextual considerations encompass the use of participants’ native language and the facilitation of digital walking tours with pairs or small groups of participants. Full article

Exploring urban spatial structure plays an important role in promoting urban development, but there is a lack of research on the urban spatial structure of Xinjiang ports. This paper takes the central urban area of Kashi City as the study area and integrates points of interest (POI) data with nighttime light (NTL) data using the Open Street Map (OSM) road network to perform kernel density analysis, two-factor combination mapping, and partition identification. It identifies the spatial structural characteristics of the central urban area and divides it into different functional subdivisions. This research shows that ① the overall distributions of nighttime luminance values and POI kernel density are similar, and the overall distribution pattern gradually weakens from the city centre to the surrounding area. High-value areas are distributed in groups, presenting the spatial structure characteristics of one main area and two subareas. ② The fusion of POI data with OSM road network data identifies urban single functional zones and mixed functional zones and divides different functional zones in a more detailed way, with higher accuracy in identifying functional zones. ③ The coupling of POI and nighttime light remote sensing can better characterise the spatial features of the urban structure, such as large-scale homogeneous areas, urban fringe areas, suburbs and township centres, etc. The fusion of POI and the OSM road network can better characterise single and mixed land use types of urban land use and improve the part of the city that cannot be characterised by POI and night light. The results of this study are conducive to the realisation of rational and functional zoning in Kashi City and provide a reference for promoting urban human–land coordination and sustainable development. Full article

Measuring human perception of environmental safety and quantifying the street view elements that affect human perception of environmental safety are of great significance for improving the urban environment and residents’ safety perception. However, domestic large-scale quantitative research on the safety perception of Chinese local cities needs to be deepened. Therefore, this paper chooses Chaoyang District in Beijing as the research area. Firstly, the network safety perception distribution of Chaoyang District is calculated and presented through the CNN model trained based on the perception dataset constructed by Chinese local cities. Then, the street view elements are extracted from the street view images using image semantic segmentation and target detection technology. Finally, the street view elements that affect the road safety perception are identified and analyzed based on LightGBM and SHAP interpretation framework. The results show the following: (1) the overall safety perception level of Chaoyang District in Beijing is high; (2) the number of motor vehicles and the proportion of the area of roads, skies, and sidewalks are the four factors that have the greatest impact on environmental safety perception; (3) there is an interaction between different street view elements on safety perception, and the proportion and number of street view elements have interaction on safety perception; (4) in the sections with the lowest, moderate, and highest levels of safety perception, the influence of street view elements on safety perception is inconsistent. Finally, this paper summarizes the results and points out the shortcomings of the research. Full article

The present work investigates the physicochemical stability of spray paints when irradiated with artificial solar light (at spectral range 300–800 nm). This research highlights the importance of understanding the materials used in street art and public murals, recognising them as a significant component of contemporary cultural heritage. By examining the stability and degradation of spray paints toward solar light exposure, the study aims to contribute to the preservation of contemporary murals, which reflect current social and cultural narratives. A physicochemical approach was employed for the study of spray paints’ physical and thermal properties, as well as the effect of specific photochemical ageing reactions/processes. The photochemical ageing results were compared with reference (unaged) samples. Specifically, a multi-technique approach was applied using stereo microscopy, scanning electron microscopy (SEM), atomic force microscopy (AFM), contact angle measurement, colorimetry, glossimetry, differential scanning calorimetry (DSC), UV-Vis spectroscopy, attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR), and pyrolysis-GC/MS (Py-GC/MS). The photodegradation of the spray paints occurred from the first 144 h of solar light irradiation, resulting in changes in morphology, colour, gloss, roughness, and wettability. Regarding photochemical stability, ageing seems to affect the binders more than the synthetic organic pigments and the inorganic fillers. In particular, acrylic binders showed small chemical changes, whereas the alkyd, nitrocellulose, and styrene binders underwent severe chemical modification. The results suggest that simulated daylight irradiation prompts the migration of additives toward the surface of the spray paint films. In addition, the results of the analyses on the white spray paints in comparison with the coloured paints (from the same manufacturer) showed that there seems to be an active distinct photoageing mechanism involving titanium dioxide, but the whole issue needs further investigation. Full article

Safety and crime prevention are significant concerns in both urban and rural areas. Crime Prevention Through Environmental Design (CPTED) guidelines provide an architectural strategy to deter criminal activities by implementing strategic design plans, particularly through effective lighting schemes in urban settings. These measures aim to reduce the fear of crime and enhance the overall quality of life. Enhanced street lighting plays a crucial role in environmental crime prevention by lowering both actual crime rates and the perceived risk of criminal activity in built environments. Current recommendations emphasize installing lighting in poorly lit areas for safety; however, assessing road surface luminance solely based on existing streetlights is insufficient. The research underscores that well-illuminated streets with uniform lighting and higher illuminance levels enhance pedestrian safety and comfort. In addition, this study proposes standardized illumination levels specifically for outdoor facial recognition to aid in identifying potential offenders. It outlines the critical vertical illuminance range and Color Rendering Index (CRI) values necessary for this purpose. Furthermore, metrics like the Brightness Index and Safety Index were developed to enhance night-time security and illustrate their correlation with crime rates. Ultimately, this research introduces quantitative lighting standards to enhance the effectiveness of CPTED guidelines, contributing to efforts to reduce crime incidence. Full article

The growing demand for Location-based Augmented Reality (LAR) experiences has driven the integration of Visual Simultaneous Localization And Mapping (VSLAM) with Google Street View (GSV) to enhance the accuracy. However, the impact of the ambient light intensity on the accuracy and reliability is underexplored, posing significant challenges in outdoor LAR implementations. This paper investigates the impact of light conditions on the accuracy and reliability of the VSLAM/GSV integration approach in outdoor LAR implementations. This study fills a gap in the current literature and offers valuable insights into vision-based approach implementation under different light conditions. Extensive experiments were conducted at five Point of Interest (POI) locations under various light conditions with a total of 100 datasets. Descriptive statistic methods were employed to analyze the data and assess the performance variation. Additionally, the Analysis of Variance (ANOVA) analysis was utilized to assess the impact of different light conditions on the accuracy metric and horizontal tracking time, determining whether there are significant differences in performance across varying levels of light intensity. The experimental results revealed that a significant correlation (p < $0.05$) exists between the ambient light intensity and the accuracy of the VSLAM/GSV integration approach. Through the confidence interval estimation, the minimum illuminance $434 \mathrm{lx}$ is needed to provide a feasible and consistent accuracy. Variations in visual references, such as wet surfaces in the rainy season, also impact the horizontal tracking time and accuracy. Full article

Background: Visual impairment is a global problem and, regardless of the cause, it substantially impacts people’s daily lives. Navigating towns and cities can be one of the most difficult tasks for someone with a visual impairment. This is because our streetscapes are often inaccessible for navigating safely and independently by people with a visual impairment. Barriers include street clutter, bollards, pavement parking, and shared spaces. Methodology: Participants with varying levels of diabetic retinopathy (DR) and retinitis pigmentosa (RP) were recruited. Each participant completed a clinical visit and a 1-mile walk. Participants discussed confidence, anxiety, difficulty, and any barriers encountered while completing the walkaround. Participants completed quality of life (RetDQol), diabetes distress scales, and a study questionnaire. They also underwent retinal imaging and visual function testing. Retinal imaging and visual function results were compared with confidence, difficulty, and anxiety levels during the walkaround using Spearman’s correlation. Results: Thirty-three participants took part in the study, 22 with diabetes and 11 with RP. Results showed that average confidence was correlated with visual acuity, RetDQol, mean visual fields, and vertical peripheral diameter visual fields. Average difficulty was associated with visual acuity, RetDQol, dark adaptation, mean visual fields, percentage of the retina, and both horizontal and vertical diameter visual fields. In addition, some of the barriers discussed were pavement issues, bollards, parked cars, uneven pavements, alfresco dining, light levels, and street features such as tree roots, poles, A-boards, and street clutter. Conclusions: People with RP and treated DR faced common barriers while navigating the walkaround. The removal of these common barriers would make our streetscapes more accessible for all and will allow for more independence in those with visual impairments. Full article