Public space management has gained rising attention across the world in recent years. However, existing studies have mainly focused on Western countries. The research on public space management in China is scarce. This paper investigates the issues and challenges associated with managing public space and how stakeholders deal with challenges that affect the effectiveness of public space management in the Chinese context. This qualitative research is built on observations and interviews from a specific case, including three groups of stakeholders: the community, the property management company, and the residents. The research found three challenges of the current practice: the difficulty of accepting new policies, the influence of the governance structure, and the process dimensions of management. These challenges are intertwined together and hinder the effectiveness of day-to-day maintenance and long-term management. This paper proposes a benchmark that will contribute to the theoretical development of public space management and will be a valuable tool for similar research across different contexts. The research findings suggest that the coordination and cooperation between different stakeholders and the establishment of a holistic management approach offer the potential for an effective and future-proof public space and environment.
Urbanization. City and country, Political institutions and public administration (General)
Significance Physical access to services and employment opportunities shapes the lives of people everywhere. For 3.4 billion people living in rural locations, the size of nearby urban centers and the associated travel time affect the breadth of services and opportunities available and their accessibility. We identify catchment areas of urban centers of different sizes and how many people gravitate toward each city or town, providing a full spatial representation of the connection between rural areas and urban centers and fresh insights on the diversity of urban–rural systems. The global dataset opens the door to applied research in various disciplines—such as poverty reduction, food systems, health, and education—where a person’s place of residence is an important factor. Using travel time to cities of different sizes, we map populations across an urban–rural continuum to improve on the standard dichotomous representations of urban–rural interactions. We extend existing approaches by 1) building on central place theory to capture the urban hierarchy in access to services and employment opportunities provided by urban centers of different sizes, 2) defining urban–rural catchment areas (URCAs) expressing the interconnection between urban centers and their surrounding rural areas, and 3) adopting a global gridded approach comparable across countries. We find that one-fourth of the global population lives in periurban areas of intermediate and smaller cities and towns, which challenges the centrality of large cities in development. In low-income countries, 64% of the population lives either in small cities and towns or within their catchment areas, which has major implications for access to services and employment opportunities. Intermediate and small cities appear to provide catchment areas for proportionately more people gravitating around them than larger cities. This could indicate that, for countries transitioning to middle income, policies and investments strengthening economic linkages between urban centers and their surrounding rural areas may be as important as investing in urbanization or the rural hinterlands. The dataset provided can support national economic planning and territorial development strategies by enabling policy makers to focus more in depth on urban–rural interactions.
Considering the purpose of the session relating early engineering developments in site response and soil-structure interaction, this paper focuses on the development of studies regarding site-city interaction following the striking site response observations obtained in Mexico City during the 1985 Guerrero-Michoacan event, The first part presents an overview of the investigations on multiple structure-soil-structure interaction, starting with Mexico-city like environments with dense urbanization on soft soils, which later evolved with the concept of metamaterials. Up to now, such investigations have been largely relying on numerical simulations in 2D and 3D media, coupling soft surface soil layers and simplified building models, including also some theoretical developments using various mechanical concepts. They also relied on a number of laboratory experiments on reduced-scale mock-ups with diverse vibratory sources (shaking table, acoustic devices). The latest studies coupled full-scale experiments on mechanical analogs such as forests or wind turbine farms involving sets of resonators with similar frequencies, and numerical simulation to investigate their impact on the propagation of surface (Rayleigh) waves. Almost all such studies converge in predicting lower ground motion amplitude for sites located within the ''urbanized'' area, but none of them can be considered a ''groundtruth'' proof for a real earthquake in a real city. The second part thus takes advantage of the long duration of strong motion observations in the Kanto area thanks to the KiK-net, K-NET and JMA (Shin-dokei) networks, to investigate the possible changes in site response with time. The first results obtained with the event-specific site terms derived from Generalized Inversion Techniques (Nakano et al., 2015) indicate a systematic reduction of the low frequency (0.2 -1 Hz) site amplification, in the central-south Tokyo area. As this frequency band corresponds both to the site frequency (very thick deposits) and to the high-rise buildings, the discussion focuses on the possible relation with the extensive construction in some areas of downtown Tokyo over the last 2 decades.
Generating realistic 3D cities is fundamental to world models, virtual reality, and game development, where an ideal urban scene must satisfy both stylistic diversity, fine-grained, and controllability. However, existing methods struggle to balance the creative flexibility offered by text-based generation with the object-level editability enabled by explicit structural representations. We introduce MajutsuCity, a natural language-driven and aesthetically adaptive framework for synthesizing structurally consistent and stylistically diverse 3D urban scenes. MajutsuCity represents a city as a composition of controllable layouts, assets, and materials, and operates through a four-stage pipeline. To extend controllability beyond initial generation, we further integrate MajutsuAgent, an interactive language-grounded editing agent} that supports five object-level operations. To support photorealistic and customizable scene synthesis, we also construct MajutsuDataset, a high-quality multimodal dataset} containing 2D semantic layouts and height maps, diverse 3D building assets, and curated PBR materials and skyboxes, each accompanied by detailed annotations. Meanwhile, we develop a practical set of evaluation metrics, covering key dimensions such as structural consistency, scene complexity, material fidelity, and lighting atmosphere. Extensive experiments demonstrate MajutsuCity reduces layout FID by 83.7% compared with CityDreamer and by 20.1% over CityCraft. Our method ranks first across all AQS and RDR scores, outperforming existing methods by a clear margin. These results confirm MajutsuCity as a new state-of-the-art in geometric fidelity, stylistic adaptability, and semantic controllability for 3D city generation. We expect our framework can inspire new avenues of research in 3D city generation. Our project page: https://longhz140516.github.io/MajutsuCity/.
The academic community has recognized that digital financial inclusion is an effective way to achieve economic environment-inclusive growth. However, a few scholars have explored the impact mechanisms of digital financial inclusion on economic environment-inclusive growth using microdata in regions with relative poverty. In this context, this study explored the mechanisms through a survey of 413 residents in Gansu Province, China, and studied them based on six variables: technological innovation, financial development, agriculture, water pollution remediation, health, and education. Data analysis indicates that, apart from agriculture, digital financial inclusion actively promotes economic environment-inclusive growth in Gansu through different pathways across the other five variables. Moreover, digital financial inclusion has a more significant impact on technological innovation, education, and health compared to financial development and water pollution remediation. This study first introduces the relatively underdeveloped economic conditions of Gansu, and provides a theoretical and practical review and analysis of digital financial inclusion and economic environment-inclusive growth in the context of digital technology development. Based on the theoretical foundations and the prominent issues in Gansu research variables and hypotheses are proposed. Through data collection and analysis, the study derives analytical results, offering an in-depth discussion of the findings and pathway relationships. Finally, this study summarizes and presents prospects for future research.
Urbanization. City and country, Environmental sciences
Metro operation management relies on accurate predictions of passenger flow in the future. This study begins by integrating cross-city (including source and target city) knowledge and developing a short-term passenger flow prediction framework (METcross) for the metro. Firstly, we propose a basic framework for modeling cross-city metro passenger flow prediction from the perspectives of data fusion and transfer learning. Secondly, METcross framework is designed to use both static and dynamic covariates as inputs, including economy and weather, that help characterize station passenger flow features. This framework consists of two steps: pre-training on the source city and fine-tuning on the target city. During pre-training, data from the source city trains the feature extraction and passenger flow prediction models. Fine-tuning on the target city involves using the source city's trained model as the initial parameter and fusing the feature embeddings of both cities to obtain the passenger flow prediction results. Finally, we tested the basic prediction framework and METcross framework on the metro networks of Wuxi and Chongqing to experimentally analyze their efficacy. Results indicate that the METcross framework performs better than the basic framework and can reduce the Mean Absolute Error and Root Mean Squared Error by 22.35% and 26.18%, respectively, compared to single-city prediction models.
El desarrollo sostenible de áreas pericentrales requiere un modelo de ocupación que fomente la equidad. La participación ciudadana se presenta como elemento clave para sustentarlo a través de relaciones virtuosas entre actores. El objetivo del artículo es destacar el papel de propietarios, residentes –presentes y futuros– en la configuración del tejido social visualizando formas de asociación que viabilicen su participación.
El análisis del contexto físico y social, en el caso de estudio El pericentro sur de Cali, identifica las características de la comunidad que impulsarán la renovación urbana. El conocimiento detallado del contexto, contrastado con experiencias nacionales e internacionales, facilita la estructuración de mecanismos y herramientas que promuevan una participación efectiva y vinculante.
El tejido social consolidado, las formas de asociación variadas y los instrumentos de gestión, planificación y financiación normativamente disponibles son las cualidades que sustentan la renovación de las áreas pericentrales como estrategia de desarrollo urbano sostenible, equitativa y paulatina.
James R. Elliott, Phylicia Xin Yi Lee Brown, Kevin Loughran
One way the U.S. government is responding to the challenges of climate change is by funding the purchase of tens of thousands of flood-prone homes in more than 500 cities and towns across the country. This study provides a nationwide analysis of that program, extending beyond cost-benefit calculations to investigate racial inequities at different scales of local implementation, from county-level adoption, through neighborhood-level participation, to homeowner approval. Statistical analyses indicate that net of local flood damage, population, and incomes, the program disproportionately targets whiter counties and neighborhoods, especially in more urbanized areas where the program now concentrates. Yet it is neighborhoods of color in these areas that have been historically more likely to accept buyouts in greater numbers. The exception is the New York and New Jersey area after Hurricane Sandy. Implications for understanding how racial privilege works through government programs aimed at encouraging environmental adaptation are discussed.
Francisco Betancourt, Alejandro P. Riascos, José L. Mateos
We aim to study the temporal patterns of activity in points of interest of cities around the world. In order to do so, we use the data provided by the online location-based social network Foursquare, where users make check-ins that indicate points of interest in the city. The data set comprises more than 90 million check-ins in 632 cities of 87 countries in 5 continents. We analyzed more than 11 million points of interest including all sorts of places: airports, restaurants, parks, hospitals, and many others. With this information, we obtained spatial and temporal patterns of activities for each city. We quantify similarities and differences of these patterns for all the cities involved and construct a network connecting pairs of cities. The links of this network indicate the similarity of temporal visitation patterns of points of interest between cities and is quantified with the Kullback-Leibler divergence between two distributions. Then, we obtained the community structure of this network and the geographic distribution of these communities worldwide. For comparison, we also use a Machine Learning algorithm - unsupervised agglomerative clustering - to obtain clusters or communities of cities with similar patterns. The main result is that both approaches give the same classification of five communities belonging to five different continents worldwide. This suggests that temporal patterns of activity can be universal, with some geographical, historical, and cultural variations, on a planetary scale.
Md. Salman, Sadika Haque, Md. Emran Hossain
et al.
Achieving food security is a global concern that constitutes a major challenge, particularly for the least developed countries, such as Bangladesh. In the context of globalization, the nation continues to have ongoing food insecurity, particularly in rural areas, despite its overall economic growth and development. This has become a constraint in achieving the Sustainable Development Goals (SDGs) within the established time scale, particularly SDG2 (Zero Hunger). With this consideration in mind, the present study assesses the prevalence of household food in(security) and identifies the factors that influence this among rural farming households in Bangladesh. A sample of 350 farming households was surveyed randomly from the four villages in Mymensingh, Bangladesh. The household food insecurity access scale (HFIAS) was utilized to explore household food security. The results reveal that only 18% of rural farming households were food secure while the remainder were food insecure to some extent. Using a binomial logit regression model, we found that the household head’s educational level, as well as whether the household has a savings account, owns land, receives financial or other forms of support from household members abroad, has larger farm sizes, and practices homestead gardening significantly reduce household food insecurity, whereas a higher number of members in the household increases it. The findings of this study establish a foundational understanding of food security in rural areas by employing contemporary measurement tools and techniques. This addition to the existing knowledge base will assist in the design and implementation of a comprehensive and multifaceted policy outline not only for the rural areas of Bangladesh but also for sustainable development globally.
Cities. Urban geography, Urbanization. City and country
With this volume - Conversations with TeMA - the Journal opens a new editorial line specifically dedicated to promoting and disseminating the discussion between worldwide researchers on specific issues concerning the contents, methods and timing of our work.
This first experience is dedicated to a deepening, in an interview formula, on the future of spatial planning in Italy both from a regulatory and technical-disciplinary perspective, also concerning what is happening in other countries. In line with the aims we had set, we decided to involve, in this first phase, both colleagues working in Italian universities and those working in foreign universities and research centres.
This contribution is by Corrado Zoppi, Full Professor in Urban Planning, University of Cagliari
Transportation engineering, Urbanization. City and country
Significance The pattern of new urban and residential roads represents an essentially permanent backbone that shapes new urban form and land use in the world’s cities. Thus, today’s choices on the connectivity of streets may restrict future resilience and lock in pathways of energy use and CO2 emissions for a century or more. In contrast to the corrective trend observed in the United States, where streets have become more connected since the late 20th century, we find that most of the world is building ever-more disconnected “street-network sprawl.” A rapid policy response, including regulation and pricing tools, is needed to avoid further costly lock-in during this current, final phase of the urbanization process. We present a global time series of street-network sprawl—that is, sprawl as measured through the local connectivity of the street network. Using high-resolution data from OpenStreetMap and a satellite-derived time series of urbanization, we compute and validate changes over time in multidimensional street connectivity measures based on graph-theoretic and geographic concepts. We report on global, national, and city-level trends since 1975 in the street-network disconnectedness index (SNDi), based on every mapped node and edge in the world. Streets in new developments in 90% of the 134 most populous countries have become less connected since 1975, while just 29% show an improving trend since 2000. The same period saw a near doubling in the relative frequency of a street-network type characterized by high circuity, typical of gated communities. We identify persistence in street-network sprawl, indicative of path-dependent processes. Specifically, cities and countries with low connectivity in recent years also had relatively low preexisting connectivity in our earliest time period. We discuss implications for policy intervention in road building in new and expanding cities as a top priority for sustainable urban development.
Urban agriculture (UA) encompasses different practices and dissimilar agendas, not all environmentally and socially savoury, ranging from food security to leisure and recreation. Although there is a wealth of literature on UA, little research has investigated its presence and role in a Chinese global city against the backdrop of unbridled urbanisation. This article focuses on Nanshan District in Shenzhen, a vast, rapidly urbanising region in China. We analyse the social and spatial characteristics of UA and its regulation. Employing a mixed-method approach that combines spatial analysis and in-depth semi-structured interviews, the results demonstrate the coexistence and interaction of diverse types of UA. What emerges is a socio-biologically rich heterogeneity of precarious practices, overlooked by the local authorities, but contributing to stewardship, social development and community engagement, while preserving a precious agricultural heritage. This article presents policy insights and advocates for government involvement in recognising the social significance of UA.
A city is a large human settlement that serves the people who live there, and a smart city is a concept of how cities might better serve their residents through new forms of technology. In this paper, we focus on four major smart city domains according to Maslow's hierarchy of needs: smart utility, smart transportation, smart homes, and smart healthcare. Numerous IoT applications have been developed to achieve the intelligence that we desire in our smart domains, ranging from personal gadgets such as health trackers and smart watches to large-scale industrial IoT systems such as nuclear and energy management systems. However, many of the existing smart city IoT solutions can be made better by considering the suitability of their security strategies. Inappropriate system security designs generally occur in two scenarios: first, system designers recognize the importance of security but are unsure of where, when, or how to implement it; and second, system designers try to fit traditional security designs to meet the smart city security context. Thus, the objective of this paper is to provide application designers with the missing security link they may need to improve their security designs. By evaluating the specific context of each smart city domain and the context-specific security requirements, we aim to provide directions on when, where, and how they should implement security strategies and the possible security challenges they need to consider. In addition, we present a new perspective on security issues in smart cities from a data-centric viewpoint by referring to the reference architecture, the Activity-Network-Things (ANT)-centric architecture, built upon the concept of "security in a zero-trust environment". By doing so, we reduce the security risks posed by new system interactions or unanticipated user behaviors while avoiding the hassle of regularly upgrading security models.
Traffic intersections are the most suitable locations for the deployment of computing, communications, and intelligence services for smart cities of the future. The abundance of data to be collected and processed, in combination with privacy and security concerns, motivates the use of the edge-computing paradigm which aligns well with physical intersections in metropolises. This paper focuses on high-bandwidth, low-latency applications, and in that context it describes: (i) system design considerations for smart city intersection intelligence nodes; (ii) key technological components including sensors, networking, edge computing, low latency design, and AI-based intelligence; and (iii) applications such as privacy preservation, cloud-connected vehicles, a real-time "radar-screen", traffic management, and monitoring of pedestrian behavior during pandemics. The results of the experimental studies performed on the COSMOS testbed located in New York City are illustrated. Future challenges in designing human-centered smart city intersections are summarized.
Urban development is closely linked by a continuous cause - effect alternation of technology that finds its
maximum application in the city, and in particular in the transport system to support the multiple forms
of mobility.
From the historical reading of urban processes, it is in fact possible to extrapolate strengths and
weaknesses, positive and negative externalities, of mobility and recognize the recurring elements in the
evolution of the city form. The aim of the paper is to build a reorganization of knowledge between
literature and comparisons of city forms to extrapolate from the past possible approaches to evaluate the
present on the occasion of multiple and contextual transitions such as energy, digital and ecological
ones.
Transportation engineering, Urbanization. City and country
Ambient particulate matter (PM) pollution of China has become a global concern and has great impact on air quality and human health. This paper adopts the PM2.5 concentration data obtained from 241 newly located observation points in the Bohai Rim Urban Agglomeration (BRUA), as well as economic, urban and industrial working population data in the study area, revealing the spatio-temporal distribution of PM2.5 and its determinants with the help of a spatial data model. The results indicate that: 1) The BRUA was the core area of PM2.5 pollution in China in 2014, the average PM2.5 concentration of which reached 74 μg/m(3), which is 13 μg/m(3) higher than the country average (61 μg/m(3)); 2) The PM2.5 concentration distribution had a characteristic of high in winter and autumn but low in spring and summer, presenting a U-shaped monthly profile and a U-impulse type daily profile; 3) The urban PM2.5 concentrations showed obvious spatial variation and agglomeration. The highest hot-spot was observed in spring, while the lowest was in summer. High concentration cities were mainly located in southern Hebei and western Shandong, and low concentration cities were in the coastal area around the Bohai Sea and the mountainous areas in northern Hebei. High hot-spot areas demonstrated an M-shaped change, with two cycles of advance and retreat from west to east. 4) The Geographically weighted regression (GWR) model shows that the GDP per capita, urbanization rate and construction of the cities were closely related to PM2.5 concentrations in the BRUA.