Urban Challenges Research Articles

Moving Towards a Holistic Approach to Circular Cities: Obstacles and Perspectives for Implementation of Nature-Based Solutions in Europe

Nature-based solutions (NBS) are frequently implemented without taking the system’s perspective into account and with the main focus on technical and economic issues of implementation. This study was conducted to test the hypothesis on the potential synergistic effects between circularity and NBS to holistically tackle urban challenges. The main objective is to establish preliminary insights on the obstacles and perspectives of NBS integration and implementation, through a questionnaire set up by the network of experts gathered within the COST Action CA17133 Circular City. The following research questions arise: (i) what differences exist in the level of NBS application according to the variance of engaged countries; and (ii) what are the main obstacles and perspectives for the NBS implementation in order to holistically tackle urban challenges, enhancing the sustainable connection among urban environment, nature, and human well-being. To go beyond the current state-of-the-art and reflect on the research conducted within the Circular City Action, this study aims to open a multi-geographical academic dialogue across Europe and beyond and to move towards a holistic approach to circular cities. Accordingly, this study is: (1) multi-geographical and context-based, providing input for thirty-three EU countries and four non-EU countries to give an overview of the main obstacles and perspectives of NBS implementation, and (2) approach-directed, aiming to formulate a holistic approach to deal with societal challenges. This document intends to provide qualitative and quantitative insight into the potentials and obstacles of NBS implementation in Europe, as well as to motivate further discussion and research to achieve holistic and sustainable cities.

Social and environmental outcomes of urban street tree bed stewardship

Abstract As projections of exponential urbanization persist, promoting the health of urban populations is one of the most urgent and challenging issues of the 21st century. By taking a planetary health approach and considering the reciprocal relationship between human health and the health of ecosystems, the integration of nature-based solutions into cities can address multiple urban challenges at once. Citizen stewardship of street trees and street tree beds is one such nature-based solution that challenges rapid urbanization while offering a healthier and greener future. Not only does citizen stewardship of street trees play a significant role in tree longevity, but our research suggests that the process of stewardship itself also positively impacts the health and wellbeing of stewards themselves. In this study, we sought to assess the motivations of street tree citizen stewards and the perceived social, environmental, and health effects of stewarding street tree beds in Freiburg, Germany. Based on a questionnaire-based survey and semi-structured interviews with tree stewards, we found that the most common motivations of citizen stewards were modeling positive environmental behavior as well as a desire to help the environment and one’s community. The perceived outcomes included a strong sense of place, a meaningful connection to nature, and the belief that stewarding a street tree bed is good for one’s mental health as well as the environment. Participants also considered street tree beds to be their personal gardens, suggesting that street tree beds may serve as restorative spaces that strengthen public health and social capital while sustaining urban greening. This case study supports and expands the scientific discourse of urban gardening while suggesting that citizen stewardship of street trees and tree beds offers myriad co-benefits for urban ecosystems and public health.

Technology-enhanced environmental learning: A practical guide to educational areas for urban educators

Abstract Mobile applications are utilized by urban educators as a means to encourage environmentally friendly behaviours among city dwellers. To enhance their effectiveness, they should meet the needs of their potential users. This qualitative survey research studied urban population of the Tricity metropolitan area intended identify the perspective of residents regarding the areas that require intervention. It focuses in the potential of mobile applications in promoting pro-environmental education, particularly in areas deemed sensitive by city residents and city users. The research framework is founded on action research. The data collection technique used a survey conducted through a research panel among 821 residents and users of the Tricity metropolitan area. The data was analysed by looking at the relevance of urban challenges and related areas of support. The results of the research were that 12 areas of city functioning perceived as needing improvement were identified and emotionally relevant among the 13 indicators analysed. In conclusion, 12 educational areas of city functioning were identified as relevant for the design of mobile applications related to environmental education. The results may also serve as a basis for developing instructional environmental education for urban educators to support local policies to address the climate crisis and encourage pro-environmental behaviour among urban residents.

Leveraging IoT, AI, and ML for Enhanced Decision-Making in Karnataka’s Smart Citie

The rapid urbanization in Karnataka, characterized by increasing population and infrastructure demands, necessitates innovative solutions to ensure sustainable and efficient urban management. Leveraging the Internet of Things (IoT), Artificial Intelligence (AI), and Machine Learning (ML) offers significant potential to enhance the decision-making capabilities of policy makers in Karnataka’s smart cities. This research paper investigates the effectiveness of these technologies in improving urban governance, focusing on real-time data acquisition, predictive analytics, and informed policy decisions. AI and ML are crucial in the analysis and interpretation of the vast amounts of data generated by IoT devices. AI algorithms process this data to identify patterns, anomalies, and trends, while ML models predict future scenarios based on historical data. For instance, predictive analytics can forecast traffic congestion, energy demand, and potential public health crises, allowing policy makers to deploy preemptive measures. In smart city initiatives, AI-driven insights ensure that resources are allocated efficiently, urban planning is optimized, and public services are enhanced. In conclusion, the integration of IoT, AI, and ML holds transformative potential for enhancing decision-making processes in Karnataka’s smart cities. By providing real-time data, predictive insights, and efficient resource management tools, these technologies enable policy makers to address urban challenges proactively and sustainably.

Sustainable Urban Infrastructure: Innovations in Green Building Technologies and Urban Planning

The burgeoning challenges of rapid urbanization, climate change, and resource depletion necessitate a paradigm shift in urban infrastructure towards sustainability. the intersection of green building technologies and urban planning as pivotal components in fostering sustainable urban development. In recent years, green building technologies have emerged as a cornerstone of sustainable urban infrastructure. From energy-efficient design to the integration of renewable energy sources, these technologies offer solutions to mitigate the environmental impact of urbanization while enhancing residents' quality of life. Furthermore, innovations such as passive design strategies, green roofs, and smart building systems demonstrate the potential to reduce energy consumption and carbon emissions in urban environments.

Coupling Coordination of Multi-Dimensional Urbanization and Ecological Security in Karst Landscapes: A Case Study of the Yunnan–Guizhou Region, China

Globally, karst regions face the dual challenges of urbanization and ecological protection, with the coupling coordination of multi-dimensional urbanization (MDU) and ecological security (ECS) being a necessary condition for achieving sustainable development. This study, based on statistical data on MDU and ECS in the Yunnan–Guizhou Region (the YGR) in China, employs the entropy weight TOPSIS model, degree of coupling coordination (CCD) model, and panel Tobit regression model to explore the coupling relationship between MDU and ECS. The main conclusions are as follows. (1) MDU in the YGR increased from 0.299 to 0.305, indicating low-level and sluggish development. Spatially, it is characterized by a “dual-core” structure centered on Kunming and Guiyang. (2) ECS decreased from 0.456 to 0.423, with a spatial pattern of “high in the east, low in the west”. The impact of human activities on ECS increased from 0.579 to 0.631 due to the increase in social and economic activities. (3) CCD increased to 0.579, achieving moderate coordination. The spatial feature evolved into a tri-cluster pattern of “high–low–high” across the “eastern–central–northwestern” regions. (4) Regression results indicate that annual average precipitation has a “both promoting and limiting” dual effect on CCD. The coefficient for the proportion of afforested land area is 0.205, with a significance level of 5%, suggesting that increasing forest cover is a key measure for improving CCD. The study reveals the factors influencing the evolution of MDU and ECS from a negative to a positive correlation, providing a basis for decisions related to sustainable development for urban and ecological management in karst landscapes globally.

Is smart city low-carbon? Evidence from China

Smart cities were originally conceived to address a myriad of urban challenges arising from rapid urbanization, including energy scarcity, congestion, and environmental degradation. The Chinese government has made substantial efforts to advance smart city initiatives. However, the extent to which the integration of smart technologies contributes to urban sustainability, especially within a high-carbon urbanization paradigm, poses a critical question in light of escalating extreme weather events and worsening global challenges. Urgency is underscored in prioritizing low-carbon strategies within smart city frameworks. This paper presents a Multicriteria Decision Making Network (MCDN) approach to assess and rank the low-carbon levels (LCL) of 36 pilot smart cities in China. Findings reveal that overall LCL among these cities remains relatively modest, with significant disparities attributed to varying economic, social, institutional, cultural, and environmental contexts. The study also delves into the nexus between urban intelligence and LCL, highlighting a discernible positive correlation between a city's smartness and its low-carbon profile. Moreover, empirical evidence suggests that advancements in smart technologies are conducive, albeit to varying degrees, to enhancing urban LCL. In light of these findings, recommendations are made to fortify economic and social advancement, bolster management practices, and foster multi-stakeholder collaboration to propel the coordinated development of smart and low-carbon initiatives in China.

Identification of the Role of Stakeholders in Sustainable City Forests, Case Study of Beringin Medan City Forest, North Sumatra, Indonesia

Management of forest cities becomes an essential strategy in strengthening environmental and social urban areas, particularly in facing the challenge of urbanization. This study aims to analyze stakeholders' roles, contributions, and strategies to increase synergy in the management of Medan Beringin City Forest. The MACTOR analysis method is used to understand the interaction between stakeholders and the factors influencing them. The results show that the involvement of various parties, including government regions, institutions, self-subsistent society, local community, and private sector, is essential in sustainable city management. City Government and Environment and Forestry Service's key roles in collaboration with other institutions are also seeded. Recommendation strategies can strengthen the effectiveness of management of forest cities, not only in Medan but also in other cities facing similar challenges.

Urban Marginalities Throughout History

Throughout history, cities have been hubs for the development of new philosophical, cultural, political, economic, andtechnological ideas, thereby enhancing the quality of life for their inhabitants. However, the concentration of populationsand activities in cities coupled with other socio-economic and political factors have engendered significant challenges,affecting vulnerable social groups in particular, and giving rise to urban marginalities. This study explores the historicaltrajectory of urban marginalities in Western cities. It examines their diverse manifestations from antiquity to the presentday. This is carried out using a historical approach and focusing on three pivotal aspects that mark the evolutionaryexpansion of the Western city. It looks into how the physical drivers for the development of the city can give rise to itsphysical and social impact, which urban marginalities are part of. The research aims to elucidate the multifacetedmechanisms underlying the emergence of urban marginalities, and the many forms under which they manifestedthemselves since ancient times. Such research highlights the importance of understanding the historical context of citieswhen addressing their contemporary urban challenges.

AI-Driven Urban Planning: Enhancing Efficiency and Sustainability in Smart Cities

Urban planning in smart cities is increasingly leveraging artificial intelligence (AI) to enhance efficiency and sustainability. This article explores the integration of AI-driven technologies to optimize various aspects of urban development and management. Smart cities are characterized by their use of advanced technologies to improve quality of life, resource management, and infrastructure efficiency. Traditional urban planning methods often face challenges in adapting to rapid urbanization and dynamic environmental changes. AI presents opportunities to address these challenges by providing data-driven insights and predictive capabilities. This research employs a case study approach, analyzing the implementation of AI in urban planning processes across several smart cities globally. Key methodologies include data analytics, machine learning algorithms, and predictive modeling techniques applied to diverse urban datasets. The study evaluates how AI-driven decision support systems aid in infrastructure planning, traffic management, energy consumption optimization, and environmental sustainability. The findings demonstrate that AI-enabled urban planning significantly enhances efficiency and sustainability in smart cities. AI algorithms optimize traffic flow, reduce energy consumption through predictive maintenance of infrastructure, and facilitate adaptive urban design based on real-time data analytics. Moreover, AI-driven approaches improve decision-making processes by providing stakeholders with actionable insights for informed policy formulation and resource allocation. This article contributes to the evolving field of smart city technologies by showcasing the transformative potential of AI in urban planning. By harnessing AI capabilities, cities can effectively address complex urban challenges and pave the way for more resilient and sustainable urban environments.

Suitability Evaluation of Urban Underground Space Development: A Case Study of Qingdao City

Urban underground space, as an underutilized land resource, holds tremendous potential and value. Efficient and rational development and utilization of this resource are key to addressing current urban challenges. This study takes the main urban area of Qingdao City as an example and establishes a comprehensive evaluation system for the suitability of urban underground space development at different depth levels through the integration of geological, hydrological, and urban planning factors. By utilizing the Analytic Hierarchy Process to assign weights to evaluation criteria within the system, both a multi-objective linear weighting function model and a fuzzy comprehensive evaluation model are employed to assess the suitability of underground space development. The results delineate the distribution of underground space development suitability within the study area. Comparative analysis of the two models reveals that the fuzzy comprehensive evaluation model offers a more detailed and comprehensive reflection of the complexity and diversity of underground space development, providing forward-looking and insightful evaluation results for urban planning and development. The evaluation indicates that certain streets within the main urban area of Qingdao exhibit excellent prospects for underground space development.

A Review of Recent Hardware and Software Advances in GPU-Accelerated Edge-Computing Single-Board Computers (SBCs) for Computer Vision.

Computer Vision (CV) has become increasingly important for Single-Board Computers (SBCs) due to their widespread deployment in addressing real-world problems. Specifically, in the context of smart cities, there is an emerging trend of developing end-to-end video analytics solutions designed to address urban challenges such as traffic management, disaster response, and waste management. However, deploying CV solutions on SBCs presents several pressing challenges (e.g., limited computation power, inefficient energy management, and real-time processing needs) hindering their use at scale. Graphical Processing Units (GPUs) and software-level developments have emerged recently in addressing these challenges to enable the elevated performance of SBCs; however, it is still an active area of research. There is a gap in the literature for a comprehensive review of such recent and rapidly evolving advancements on both software and hardware fronts. The presented review provides a detailed overview of the existing GPU-accelerated edge-computing SBCs and software advancements including algorithm optimization techniques, packages, development frameworks, and hardware deployment specific packages. This review provides a subjective comparative analysis based on critical factors to help applied Artificial Intelligence (AI) researchers in demonstrating the existing state of the art and selecting the best suited combinations for their specific use-case. At the end, the paper also discusses potential limitations of the existing SBCs and highlights the future research directions in this domain.

Advances in Vertical Farming: Opportunities and Challenges

Vertical farming has emerged as a promising solution to address the challenges of food security, sustainability, and urbanization in the 21st century. This innovative approach to agriculture involves growing crops in vertically stacked layers within controlled environments, optimizing space, resources, and yields. Vertical farming represents a significant innovation in agriculture, designed to meet the challenges of urban food production with enhanced efficiency and sustainability. This study examines recent technological advancements in vertical farming, emphasizing methods such as automation. By growing crops in vertically stacked layers within controlled environments, vertical farming maximizes space utilization and minimizes resource consumption. The results indicate substantial improvements in crop yields and quality, along with reduced water and pesticide use. Additionally, the proximity of vertical farms to urban centers shortens supply chains, lowering transportation costs and carbon emissions. The discussion highlights the economic benefits, including year-round production and premium pricing for pesticide-free produce, alongside the challenges of high initial investments and energy demands. The environmental impacts are also considered, noting significant reductions in land use and water consumption compared to traditional farming. This review underscores the potential of vertical farming to contribute to global food security and sustainable urban development, while addressing the need for further research and collaboration to overcome existing barriers. The findings suggest that continued innovation and supportive policies are crucial for the widespread adoption and success of vertical farming practices.

Integrating vertical greenery for complex building patterns towards sustainable urban environment

Rapid urbanization has increased the urban density and functional diversity, exacerbating environmental challenges such as urban heat islands (UHI), increased building energy consumption and carbon emissions, etc., hindering the sustainable urban development. Addressing these challenges requires innovative solutions that could offer the strategic cooling of urban buildings. Vertical greenery, affixed to building façades, offers a promising approach to provide benefits of cooling, energy savings, carbon reduction and urban space saving. However, there is a lack of quantitative design for integrating vertical greenery into complex urban buildings. Therefore, this study conducts a systematic investigation for low-rise, mid-rise, and high-rise buildings incorporating vertical greenery, while performing comprehensive assessments on indoor and outdoor thermal conditions, building energy usage, and carbon emissions. The findings suggest that low-rise buildings benefit from a vertical greenery layout, while mid-rise and high-rise buildings are better suited for a horizontal greenery layout. Compared to scenarios without greenery, buildings with vertical greenery experience a maximum reduction of 0.66 °C in outdoor air temperature and 0.72 °C in indoor air temperature, along with a 5.9 % decrease in energy consumption and carbon emissions. This study addresses urban challenges through a quantified vertical greenery design, offering valuable insights for sustainable urban development.

Optimizing Dijkstra's Algorithm for Managing Urban Traffic Using Simulation of Urban Mobility (Sumo) Software

Among the challenges of urbanization is traffic management as a measure of growth and progress. Recent population growth has resulted in a significant increase in vehicles, causing traffic jams that are challenging for the existing transportation networks. This congestion affects other services, including public transit, airports, road maintenance, and pollution caused by emissions of CO2 and other gases. Furthermore, it doubles the amount of fuel used. This has negative consequences for society as well as economic losses. This paper focuses on an improved Dijkstra algorithm based on traffic congestion levels to address the above problems. Improved Dijkstra algorithm can provide (a) real data collected from the map via OpenStreetMap, (b) Add four features to SUMO(Simulation of Urban Mobility) simulator software (time period, rush-hour, number of vehicles, and routing algorithm), (c) it could know congestion level for roads (d) rerouting vehicles to avoid traffic congestion. Based on the simulation results and analysis presented in the paper, it was found that the proposed improved Dijkstra algorithm increased the performance of the road traffic flow by reducing the number of related vehicles in traffic congestion and average delay time for experiment scenarios.

Development Strategy Based on Combination Typologies of Building Carbon Emissions and Urban Vibrancy—A Multi-Sourced Data-Driven Approach in Beijing, China

When confronting the dual challenges of rapid urbanization and climate change, although extensive research has investigated the factors influencing urban carbon emissions and the practical strategies regarding urban vibrancy, the unclear mutual nexus between them and the development strategy for collaborative optimization requires further in-depth analysis. This study explores the delicate balance between urban vibrancy and low-carbon sustainability within the confines of Beijing’s Fifth Ring Road. By integrating OpenStreetMap, land use, population, and buildings’ carbon emission data, we have developed a reproducible method to estimate total carbon emissions and emission intensity. Furthermore, we have introduced vibrancy index data to distinguish the vibrancy evaluation of residential and non-residential land and applied cross-combinational classification technology to dissect the spatial correlation between urban carbon emissions and urban vibrancy. The results reveal that the four combination typologies show more significant differences and regularity in residential land. Based on the discovery of spatial correlation, this study puts forward corresponding development strategy suggestions for each of these four typologies based on the geographical location and requirements of urban development policies. In conclusion, our study highlights the importance of integrating carbon emissions and urban vibrancy comprehensively in sustainable urban planning and proposes that various land use combinations need targeted development strategies to achieve this goal, which need to consider population, energy, service facilities, and other diverse aspects.

Motivations Influencing Relocation to the Suburbs: The Case of Izmir

The ongoing urbanization trend has led to various challenges including environmental degradation, and decreased welfare among city dwellers. While economic factors have historically been the primary driver of urban migration, recent research suggests that unplanned urbanization and the problems it brings such as decreased green spaces, traffic congestion and air pollution are gaining significance. As a result, a group of people has been relocating from urban to suburban areas, seeking an improved standard of living. This shift reflects a complex interplay of factors including demographic, socioeconomic, and sociocultural shifts. Since the onset of the COVID-19 pandemic, there has been an increased interest in suburban areas due to remote work opportunities and concerns about urban living conditions. This study examines motivations for suburban living in Izmir, Turkey, focusing on Villakent neighbourhood. Through surveys and interviews with residents, it explores demographic characteristics and reasons for choosing suburban life. The research is based on the results of a sample of 123 participants of a survey questionnaire and 15 in-depth interviews. Findings have indicated that the participants’ desire for living in a house with a garden and the discomforting crowds in the city centers was the important factors in suburban relocation. In interviews, it was also revealed that the affordability of housing in the suburbs compared to city centers is also an important factor in choosing to settle in the suburbs. Additionally, the COVID-19 pandemic has had an impact on suburban relocation, and the earthquake risk in Izmir has also increased people's desire to move away from city centers. In the interviews, the preference for Villakent was discussed along with its positive and negative aspects in detail. Policymakers must consider these insights to address urban challenges and promote sustainable urban development.

Navigating urban challenges: Quantifying emergency service accessibility and robustness amid meteorological disasters

The frequent occurrence of meteorological disasters presents a significant challenge to the effective functioning of urban public services. This paper seeks to assess the response capacity of urban emergency services during such disasters by integrating perspectives on accessibility and robustness. Through a case study on emergency medical services (EMS), we develop a framework for evaluating the EMS system in downtown Shanghai under the scenario of typhoon In-Fa. This framework encompasses the calculation of both the accessible area of ambulance vehicles and the accessibility to each resident address. Our findings indicate that under normal conditions, the majority of residential areas in downtown Shanghai can access nearby medical services within 10 min. However, accessibility decreases by 28.85 % and 43.83 % under moderate and severe flooding conditions, respectively. Furthermore, by analyzing changes in the robustness of the service supply network, we identify warning and critical points, offering valuable insights for the formulation of disaster warning and response strategies. This study integrates system-level robustness and address-level accessibility to establish a comprehensive framework for evaluating urban emergency service performance under meteorological disaster scenarios. The proposed approach holds promise for evaluating other types of public services by adapting the framework to account for specific supply and demand dynamics.

Business Models Used in Smart Cities—Theoretical Approach with Examples of Smart Cities

This paper examines business model implementations in three leading European smart cities: London, Amsterdam, and Berlin. Through a systematic literature review and comparative analysis, the study identifies and analyzes various business models employed in these urban contexts. The findings reveal a diverse array of models, including public–private partnerships, build–operate–transfer arrangements, performance-based contracts, community-centric models, innovation hubs, revenue-sharing models, outcome-based financing, and asset monetization strategies. Each city leverages a unique combination of these models to address its specific urban challenges and priorities. The study highlights the role of PPPs in large-scale infrastructure projects, BOT arrangements in transportation solutions, and performance-based contracts in driving efficiency and accountability. It also explores the benefits of community-centric models, innovation hubs, revenue-sharing models, outcome-based financing, and asset monetization strategies in enhancing the sustainability, efficiency, and livability of smart cities. The paper offers valuable insights for policymakers, urban planners, and researchers seeking to advance smart city development worldwide.

Geo-information systems in urban planning: A review of business and environmental implications

In an era where urban landscapes are rapidly evolving, the integration of Geographic Information Systems (GIS) in urban planning emerges as a pivotal tool for sustainable development. This paper delves into the multifaceted role of GIS, exploring its implications in the realms of business and environmental sustainability within urban contexts. The background of the study is rooted in the increasing complexity of urban challenges and the need for innovative solutions to address them effectively. The aim of this paper is to provide a comprehensive analysis of GIS applications in urban planning, focusing on their impact on both business efficiency and environmental stewardship. The scope of the study encompasses an exploration of the historical evolution of GIS, its integration in various urban settings, and the interplay between commercial objectives and environmental sustainability. Employing a methodological framework that includes a thorough review of relevant literature and case studies, the study illuminates the dynamic interplay between technological advancements in GIS and their practical applications in urban planning. This approach facilitates a panoramic view of GIS's multifarious implications, highlighting trends, patterns, and impacts of its adoption in diverse urban scenarios. The main conclusions reveal that GIS is indispensable in modern urban development, adeptly addressing complex urban challenges, particularly in sustainable planning and balancing economic growth with environmental protection. However, the study also uncovers challenges such as the need for improved database construction and comprehensive information services. Recommendations include tailoring policies to local contexts, focusing on multi-scalar GIS-based indicators, and prioritizing sustainable development goals. These strategies are crucial for enhancing the efficacy of GIS in urban planning, leading to more sustainable and well-managed urban environments.