Search Results (188)

Wellington, New Zealand, is highly vulnerable to disaster-induced food security crises due to its geography and geological characteristics, which can disrupt transportation and isolate the city following disasters. Urban agriculture (UA) has been proposed as a potential alternative food source for post-disaster scenarios. This study examined the potential of urban agriculture for enhancing post-disaster food security by calculating vegetable self-sufficiency rates. Specifically, it evaluated the capacity of current Wellington’s community gardens to meet post-disaster vegetable demand in terms of both weight and nutrient content. Data collection employed mixed methods with questionnaires, on-site observations and mapping, and collecting high-resolution aerial imagery. Garden yields were estimated using self-reported data supported by literature benchmarks, while cultivated areas were quantified through on-site mapping and aerial imagery analysis. Six post-disaster food demand scenarios were used based on different target populations to develop an understanding of the range of potential produce yields. Weight-based results show that community gardens currently supply only 0.42% of the vegetable demand for residents living within a five-minute walk. This rate increased to 2.07% when specifically targeting only vulnerable populations, and up to 10.41% when focusing on gardeners’ own households. However, at the city-wide level, the current capacity of community gardens to provide enough produce to feed people remained limited. Nutrient-based self-sufficiency was lower than weight-based results; however, nutrient intake is particularly critical for vulnerable populations after disasters, underscoring the greater challenge of ensuring adequate nutrition through current urban food production. Beyond self-sufficiency, this study also addressed the role of UA in promoting food diversity and acceptability, as well as its social and psychological benefits based on the questionnaires and on-site observations. The findings indicate that community gardens contribute meaningfully to post-disaster food security for gardeners and nearby residents, particularly for vulnerable groups with elevated nutritional needs. Despite the current limited capacity of community gardens to provide enough produce to feed residents, findings suggest that Wellington could enhance post-disaster food self-reliance by diversifying UA types and optimizing land-use to increase food production during and after a disaster. Realizing this potential will require strategic interventions, including supportive policies, a conducive social environment, and diversification—such as the including private yards—all aimed at improving food access, availability, and nutritional quality during crises. The primary limitation of this study is the lack of comprehensive data on urban agriculture in Wellington and the wider New Zealand context. Addressing this data gap should be a key focus for future research to enable more robust assessments and evidence-based planning. Full article

Urban traffic congestion poses persistent challenges to mobility, public safety, and governance efficiency in metropolitan areas. This study proposes an intelligent traffic flow forecasting framework based on an extended Long Short-Term Memory (xLSTM) model, specifically designed for real-time congestion prediction and proactive police dispatch support. Utilizing a real-world dataset collected from over 300 vehicle detector (VD) sensors, the proposed model integrates vehicle volume, speed, and lane occupancy data at five-minute intervals. Methodologically, the xLSTM model incorporates matrix-based memory cells and exponential gating mechanisms to enhance spatio-temporal learning capabilities. Model performance is evaluated using multiple metrics, including congestion classification accuracy, F1-score, MAE, RMSE, and inference latency. The xLSTM model achieves a congestion prediction accuracy of 87.3%, an F1-score of 0.882, and an average inference latency of 41.2 milliseconds—outperforming baseline LSTM, GRU, and Transformer-based models in both accuracy and speed. These results validate the system’s suitability for real-time deployment in police control centers, where timely prediction of traffic congestion enables anticipatory patrol allocation and dynamic signal adjustment. By bridging AI-driven forecasting with public safety operations, this research contributes a validated and scalable approach to intelligent transportation governance, enhancing the responsiveness of urban mobility systems and advancing smart city initiatives. Full article

This study investigates the application of the Dueling Double Deep Q-Network (3DQN) algorithm to optimize traffic signal control at a major urban intersection in Danang City, Vietnam. The objective is to enhance signal timing efficiency in response to mixed traffic flow and real-world traffic dynamics. A simulation environment was developed using the Simulation of Urban Mobility (SUMO) software version 1.11, incorporating both a fixed-time signal controller and two 3DQN models trained with 1 million (1M-Step) and 5 million (5M-Step) iterations. The models were evaluated using randomized traffic demand scenarios ranging from 50% to 150% of baseline traffic volumes. The results demonstrate that the 3DQN models outperform the fixed-time controller, significantly reducing vehicle delays, with the 5M-Step model achieving average waiting times of under five minutes. To further assess the model’s responsiveness to real-time conditions, traffic flow data were collected using YOLOv8 for object detection and SORT for vehicle tracking from live camera feeds, and integrated into the SUMO-3DQN simulation. The findings highlight the robustness and adaptability of the 3DQN approach, particularly under peak traffic conditions, underscoring its potential for deployment in intelligent urban traffic management systems. Full article

The concept of the 15-minutes city [15 MC] focuses on providing important services within proximity and accessibility through active travel like walking or biking. While this model is becoming popular in urban planning and academic discourse, its implementation faces challenges in both densely populated developing and developed countries. This study aims to conduct a systematic review of recent literature to (1) identify the core components of the 15 MC model, (2) examine planning tools and strategies used in its implementation, (3) compare successes and challenges across global contexts, particularly in densely populated and resource-constrained areas, and (4) offer practical recommendations for adapting the model to meet local needs. The study reviewed 33 research papers published in the last five years [2019–2024]. Following PRISMA guidelines, a structured screening and selection process was conducted using databases such as Scopus, Web of Science, and Google Scholar. Thematic analysis revealed major challenges for implementing the 15 MC in the Global South, including urban informality, gaps in infrastructure, and complex governance issues. Moreover, the review points out the potential risks of exclusion and gentrification if the specific needs of different contexts are not considered. While high-income countries tend to focus on sustainability and making neighborhoods walkable, developing countries struggle with deeper structural problems that make equitable implementation harder. This study emphasizes the need for locally adaptive frameworks in planning 15 MCs and aims to develop inclusive urban policies that support Sustainable Development Goal 11, which seeks to make cities inclusive, safe, resilient, and sustainable. Full article

The study explores the features of spatiotemporal circles of residents’ daily walking. Through a survey of residents’ walking activity in 16 residential communities, the walking purpose, distance, time, and speed of different residents were analyzed, and the circles of residents’ walking activities in historic and modern districts were identified. It is found that residents’ walking activities showed obvious spatiotemporal and individual differences. Walking activities on weekdays mainly focus on short distances (0.5–1 km) and short duration (5–15 min) for commuting and basic needs, while walking activities on weekends tend to be longer distances (more than 2 km) and longer duration (15–40 min) for leisure purposes. There are significant differences in distance and speed between walking activities in the historic and modern districts, with residents of the historic districts walking a smaller range but more diverse destinations, and residents of the modern districts walking to a wider range but fewer types of destinations. The study provides a scientific basis for multi-circle planning strategies of community life units, and it contributes to the localized adaptation of the “15-minute city” concept by revealing how historical and modern districts shape distinct spatiotemporal circles for walkability in Chinese cities. Full article

Pedestrian safety is explored within the framework of 15 min cities, with a focus on behavioural differences between blind and sighted individuals. Utilising the pedestrian behaviour scale (PBS), self-reported pedestrian behaviours were analysed using a 5-point Likert scale. A sample of six blind pedestrians was compared with 502 sighted individuals, identifying distinct behavioural patterns across four dimensions: transgression, lapses, aggressive behaviours, and positive behaviours. It was found that blind pedestrians reported higher frequencies of positive behaviours and lower frequencies of aggressive behaviours, aligning with previous studies on vulnerable users. The small sample size of blind pedestrians limits statistical generalizability; however, the study highlights the need for inclusive infrastructure and targeted safety measures to mitigate risks for blind pedestrians in urban areas, particularly in the context of the 15 min city. The implications for policy and urban planning are discussed. Full article

This study analyzes biometeorological conditions during summer heat events in 11 cities located in different regions of Poland in the summer months from 2020 to 2024. Heat days (defined as days with a maximum temperature exceeding 30 °C) and heatwaves (defined as at least three consecutive days with a maximum temperature above 30 °C) were identified. Biometeorological conditions were assessed based on the Universal Thermal Climate Index (UTCI) and heart rate (HR), assuming a metabolic heat production of 135 W∙m⁻² for an adult human. The indices were calculated using the BioKlima 2.6 software. The findings reveal that all cities experienced significant thermal stress during heat events. The maximum UTCI values during heat days indicated strong and very strong heat stress. During the most intense heatwaves, assessed using the Heat Wave Severity (HWS) index, these categories of heat stress occurred 20–30% of the time. Simultaneously, the mean daily heart rates exceeded the warning threshold of 90 beats per minute. Differences in biometeorological conditions were found between urban centers and places located outside the center, where strong heat conditions occurred less frequently. The results indicate that biometeorological conditions imposing thermal stress on the human body were present in all Polish cities during the analyzed five-year period. In Warszawa, Wrocław, and Rzeszów, heatwaves and heat stress occurred annually. Full article

In recent years, the 15-minute city (15MC) model has gained significant attention among scholars and practitioners, particularly in the wake of COVID-19. However, limited research has explored how this model can be adapted to high-density, high-rise urban environments characterized by compact land use and mobility challenges. This study addresses this gap by extending the core principles of the 15MC—density, proximity, diversity, and digitalization—with additional context-specific dimensions: mobility choice, walkability and cyclability, public transport proximity, inclusivity, placemaking, and policy integration. Using qualitative research and site observations, we analyze three diverse neighborhoods in Singapore: Clementi, Toa Payoh, and Holland Village. The comparative evaluation reveals the strengths and limitations of applying a vertical, hierarchical, and multilayered planning model in dense urban contexts. The study also highlights the potential of a three-dimensional planning framework that integrates vertical and horizontal spatial structures to optimize accessibility and functionality. The findings contribute to the broader discourse on sustainable urbanism by offering actionable strategies to support the transition toward more accessible, low-carbon, and livable high-density cities. Full article

Driving under the influence of alcohol (DUI) remains a leading cause of accidents globally, with accident risk rising exponentially with blood alcohol concentration (BAC). This study aims to distinguish between sober and intoxicated drivers using driving behavior analysis and driver monitoring system (DMS), technologies that align with emerging EU regulations. In a driving simulator, twenty-three participants (average age: 32) completed five drives (one practice and two each while sober and intoxicated) on separate days across city, rural, and highway settings. Each 30-minute drive was analyzed using eye-tracking and driving behavior data. We applied significance testing and classification models to assess the data. Our study goes beyond the state of the art by a) combining data from various sensors and b) not only examining the effects of alcohol on driving behavior but also using these data to classify driver impairment. Fusing gaze and driving behavior data improved classification accuracy, with models achieving over 70% accuracy in city and rural conditions and a Long Short-Term Memory (LSTM) network reaching up to 80% on rural roads. Although the detection rate is, of course, still far too low for a productive system, the results nevertheless provide valuable insights for improving DUI detection technologies and enhancing road safety. Full article

Disruptive events and the rapid evolution of urban energy systems highlight the need for robust methods to reconstruct critical infrastructure networks. Comprehensive, up-to-date power grid representations are essential for both researchers developing methods for analysing and optimising power systems and first responders requiring approximate data for urgent decisions. However, traditional grid reconstruction approaches often rely on incomplete data, expert knowledge, or closed datasets, limiting their utility during emergencies. This study proposes a novel automated method for reconstructing medium-voltage (MV) power grids. The novelty of the proposed method lies in combining OpenStreetMap energy and land-use data in a unified and automated framework, thereby reducing the need for expert input. The proposed method employs a systematic aggregation of data, an estimation of energy demand, and the application of algorithmic techniques to generate synthetic MV grid models that functionally represent real networks, capturing key topological features. The resulting outputs include visual representations to support decision-makers in simulating "what-if” scenarios and ensuring rapid operational awareness. In a step toward eliminating reliance on proprietary data, our approach broadens access to critical infrastructure insights across diverse urban contexts, contributing to critical infrastructure resilience and potentially supporting both energy system research and crisis management. A case study demonstrates that a medium-sized city’s MV grid can be reconstructed in minutes without expert knowledge or geographically constrained datasets, underscoring the method’s deployment potential and practical value for emergency scenarios. Full article

Over the past two decades, walkability, accessibility, and urban street culture have become major study topics in several areas of contemporary urban research, including urban sustainability, urban economy, healthy cities, and the x-minute city. Due to a plethora of evidence that supports the benefits of an accessible and walkable neighborhood, many countries and cities have put in place urban reform agendas that prioritize accessibility and walkability and promote urban street culture. Saudi Arabia is among those countries, as evidenced by the goals established in Saudi Vision 2030. This study focuses on the City of Hail’s efforts to enhance the walkability of its neighborhoods and the city’s accessibility. This study looks at how the newly constructed pedestrian infrastructure matches people’s expectations and how it influences how people in Hail walk. This study also makes specific suggestions for improvement and identifies ways forward. This study employs a three-fold ‘post-occupancy evaluation’ methodology that includes qualitative interviews, quantitative surveys, and direct observation, focusing on how the community interacts with the new pedestrian streetscapes. This study recommends designing areas in the City of Hail with improved pedestrian rights-of-way, enhancing sidewalk design and continuity, creating pedestrian buffer zones, boosting shade and shelter, and increasing safety and security. The suggested design changes will have the added benefit of strengthening the sense of community of Hail residents while also promoting mixed-use development, which is generally recognized as a more ‘organic’, natural development path that also aligns with Saudi’s heritage architecture, returning Hail’s urban space to its roots. These findings are crucial for shaping city planning in the City of Hail and beyond by emphasizing inclusive strategies that create lively communities where walking is encouraged and enjoyed. Full article

Despite the significant progress in the last few decades, road safety improvement still constitutes an imperative global need. Especially in urban areas, the improvement of road safety is an even more complicated and multi-factor problem. Every minute, a human life is lost in an urban road network in the world. Given that almost all road accidents are preventable, more effective planning toward improving road safety, as a structural element of sustainable urban mobility, is imperative. The aim of the present research is to provide decision support analysts and policy-makers with a decision-support tool that identifies and prioritizes the factors undermining road safety in an urban area, with a view to developing effective policies. For this purpose, a comprehensive inventory of factors that may undermine road safety in an urban area, as well as an inventory of relevant measures and policies, is provided, based on an international literature review. The most important factors and, subsequently, the most effective measures and policies are identified and prioritized through a multi-criteria approach (modified Delphi–analytical hierarchy process (AHP)–technique for order preference by similarity to ideal solution (TOPSIS)). The Greek urban road networks, starting from the second largest city in Greece (Thessaloniki), are selected as a case study. Problems related to limited resources not allowing for systematic surveillance and policing, making arbitrary decisions instead of adopting a scientific decision-aiding methodology, education and mentality issues, infrastructure planning and maintenance, cooperation and coordination between different authorities, and laxity of penalties are highlighted as the most important factors, based on which four sets of measures and policies are identified and prioritized. Full article

Power system stability (PSS) refers to the capacity of an electrical system to maintain a consistent equilibrium between the generation and consumption of electric power. In this paper, the PSS is evaluated for a “hybrid power plant” (HPP) which combines thermal, wind, solar photovoltaic (PV), and hydropower generation in Niigata City. A new method for estimating its PV power generation is also introduced based on NHK (the Japan Broadcasting Corporation)’s cloud distribution forecasts (CDFs) and land ratio settings. Our objective is to achieve frequency stability (FS) while reducing CO₂ emissions in the power generation sector. So, the PSS is evaluated according to the results in terms of the FS variable. Six-minute autoregressive wind speed prediction (6ARW) support is used for wind power (WP). One-hour GPV wind farm (1HWF) power is computed from the Grid Point Value (GPV) wind speed prediction data. The PV power is predicted using autoregressive modelling and the CDFs. In accordance with the daily power curve and the prediction time, we can support thermal power generation planning. Actual data on wind and solar are measured every 10 min and 1 min, respectively, and the hydropower is controlled. The simulation results for the electricity frequency fluctuations are within ±0.2 Hz of the requirements of Tohoku Electric Power Network Co,. Inc. for testing and evaluation days. Therefore, the proposed system supplies electricity optimally and stably while contributing to reductions in CO₂ emissions. Full article

The intersection of environmental justice and urban accessibility presents a critical challenge in sustainable city planning. While the “15-minute city” concept has emerged as a prominent framework for promoting walkable neighborhoods, its implications for environmental exposure inequalities remain underexplored. This study introduces an innovative methodology for assessing air pollution exposure disparities within the context of 15-minute activity zones in New York City. By integrating street-level PM2.5 predictions with spatial network analysis, this research evaluates exposure patterns that more accurately reflect residents’ daily mobility experiences. The results reveal significant socioeconomic and racial disparities in air pollution exposure, with lower-income areas and Black communities experiencing consistently higher PM2.5 levels within their 15-minute walking ranges. A borough-level analysis further underscores the influence of localized urban development patterns and demographic distributions on environmental justice outcomes. A comparative analysis demonstrates that traditional census tract-based approaches may underestimate these disparities by failing to account for actual pedestrian mobility patterns. These findings highlight the necessity of integrating high-resolution environmental justice assessments into urban planning initiatives to foster more equitable and sustainable urban development. Full article

Background: Alberta Cancer Exercise (ACE) is a hybrid effectiveness–implementation study evaluating a cancer-specific community-based exercise program across urban sites in Alberta, Canada. The purpose of this paper is to describe the baseline characteristics of participants. Methods: Adults with any type and stage of cancer, who were undergoing cancer treatment or up to three years post treatment completion, were eligible. ACE was delivered in person at 18 sites across 7 cities in Alberta, with video conferencing introduced during the COVID-19 pandemic. Participants took part in 60 min of mild-to-moderate intensity exercise twice weekly for a 12-week period and were encouraged to increase overall physical activity. Results: From January 2017 to February 2023, 2570 individuals enrolled. Participants were a mean age of 57.8 years, 71.3% were female, 45.4% had breast cancer, and 49.4% were undergoing cancer treatment. At baseline, only 22.4% of participants self-reported meeting recommended physical activity levels, 66.0% were overweight/obese, and 71.4% reported one or more comorbidities. Most participants were below normative levels for the six-minute walk and 30 s sit-to-stand tests, and 75.9% reported fatigue. Conclusion: Participants were largely inactive, unfit, and symptomatic. ACE attracted more females and individuals with breast cancer but was otherwise representative of the Alberta cancer population. Full article