Urban Research Research Articles

A Comparative Study on IoT Based Traffic Management System

Abstract: The continuous growth of the global population has led to a rapid increase in vehicle production, resulting in an exponential growth of vehicles on the roads. This surge contributes to severe traffic congestion, particularly during peak rush hours in metropolitan cities. Urban planners, city officials, and researchers are increasingly concerned about effective traffic management to ensure safety and economic efficiency. Addressing this issue, Intelligent Transportation Systems (ITS) integrate existing technology with current infrastructure to alleviate congestion. This paper focuses on a comparative study of various traffic control methods, specifically the Traffic Light System (TLS), which includes Radio Frequency Identification (RFID), dynamic and static TLS, and the Internet of Things (IoT).

Rationale and plan for a focus on First Nations urban health research in Australia.

Rationale and plan for a focus on First Nations urban health research in Australia.

A Review of The Routledge Handbook of Urban Design Research Methods

This book review critically examines <em>The Routledge Handbook of Urban Design Research Methods</em>, edited by Hesam Kamalipour, Patricia Aelbrecht, and Nastaran Peimani (2023, 1st edition). The book offers an extensive exploration of urban design research, organized under five thematic parts: “agency,” “affordance,” “place,” “informality,” and “performance.” Each part delves into the complexities and nuances of urban design research, integrating a diverse range of methodologies and case studies from different perspectives. This review explores the book’s comprehensive approach, noting its efforts to combine theoretical frameworks with methodological insights and its inclusion of a wide range of topics while highlighting the book’s strengths in addressing current issues in urban design research. The review maintains a critical approach, providing a balanced overview of the book’s contribution to urban design literature.

The Collective Realms in the Chinese City: Towards an Alternative Framework for Public Space

A western discourse of public space, originating in ancient Greece and Rome, has been widely used in architectural and urban research in China and is constantly contested in this geographical and cultural context. The contestation often stems from the cultural differences in understanding and operating the collective realms in Chinese and western cities, which is manifested through the distinctive features of their public spaces. This essay frames an alternative perspective on public space in the Chinese context by exploring the cultural, social, and spatial constructions of collective realms in the Chinese city.Starting from the conceptual origin of the ‘public’ in Chinese philosophy, this paper elaborates on three culturally grounded ideas related to collective patterns of space creation and practice – the relational circle, the realm of strangers, and the marketplace – and examines how these ideas are articulated by architectural and urban archetypes and in urban developments in Chinese cities.

Promoting Economic Empowerment Through Effective Implementation and Linking Social Capital in Urban Agriculture Programs

Promoting Economic Empowerment Through Effective Implementation and Linking Social Capital in Urban Agriculture Programs

Inventory of the urban flora of Budapest (Hungary) highlighting new and noteworthy floristic records.

The systematic urban floristic research of Budapest was started in 2018 by the authors with detailed methodology. One scope of the research was to gain knowledge on the plant taxa appearing in Budapest and to compile the inventory of the urban flora of Budapest. We have provided the inventory of the urban flora of Budapest, which includes distribution data for all 973 taxa found in Budapest between May 2018 and May 2023. We also provided new detailed occurrence data for 49 species in Budapest. Seven of them are new to the adventive flora of Hungary (Campanulaportenschlagiana Roem. & Schult., Clinopodiumnepeta (L.) Kuntze, Chasmanthiumlatifolium (Michx.) H.O.Yates, Cyrtomiumfortunei J.Sm., Linariamaroccana Hook.f., Talinumpaniculatum (Jacq.) Gaertn.), three were rediscovered in Hungary (Glebioniscoronaria (L.) Cass. ex Spach, Lagenariasiceraria (Molina) Standl., Sisymbriumirio L.) and 18 were recorded for the first time in Budapest. We also provided data for two data-poor (Artemisiascoparia Waldst. & Kit., Polygonumrurivagum Jord. ex Boreau) species and we documented the major expansion of six species.

Holistic wild bee management in urban spaces

Projects promoting bees in urban areas are initiated in cities around the world but evidence-based conservation concepts at a city-wide scale are scarce. We developed a holistic approach for assessment of bee and flowering plant diversity in a medium-sized city. In addition to standard mapping approaches in bee hotspots, we initiated citizen science projects for participative urban bee research to be able to collect comprehensive bee data across the entire city. We identified 22 hotspots of bee diversity, analyzed connectivity between those hotspots and evaluated the impact of flower patches planted in collaboration with the municipal gardens department as stepping stones for oligolectic bee species throughout the city. Participation by urban citizens in bee identification trainings was high (c. 630 persons) but their subsequent contribution through observation reports was relatively low (1,165 records by 140 observers). However, we identified a total of 139 bee taxa, seven of them only discovered by citizen scientists. Total species richness was higher in extensively managed orchards than in semi-natural and wasteland areas. Half of the stepping stone flower patches were occupied by the target oligolectic bee species in the year of planting. After 3 years, all but two species could be confirmed. We suggest a 5-step concept for bee management in cities: (1) identification of bee hotspots combined with standardized surveys, especially of rare species; (2) training of citizen scientists at two different levels for comprehensive surveys in all parts of the city: (a) half-day introductions to wild bee diversity, ecology and conservation in order to create more awareness and (b) 2-weeks workshops for in-depth training of a small number of dedicated citizen scientists; (3) extensive management of existing habitats and special conservation programs for very rare species; (4) creation of high-value habitats which take into account the varied resource needs of bees within flight ranges of only a few hundred meters; (5) creation of stepping stone habitats as floral and nesting resources, integrating educative and participative aspects.

Review of Research on Urban Social Space and Sustainable Development

Urban social space and sustainable urban development are both prominent areas of research in urban studies. The development of a city is closely tied to the development of its social space. The level of sustainable development in a city can be assessed by examining the evolution of its urban social space. Therefore, the two are highly interconnected in a close relationship. However, the social dimension of sustainable development has always received the least attention compared to the economy and the environment. Therefore, this paper examines urban transformation and urban spatial structure, social composition, the activity space and living space of urban residents, the social integration of urban residents in urban communities, and urban planning. This paper provides a comprehensive literature review of research on urban social space and sustainable development. On the one hand, this literature review thoroughly examines the correlation between urban social space and sustainable urban development. On the other hand, it broadens the perspectives of urban research, highlights the key role of social dimensions in sustainable urban development, and helps to draw the attention of academics to this topic. In addition, this literature review may provide policymakers with more comprehensive information on urban social space and sustainable development.

Predicting solar radiation in the urban area: A data-driven analysis for sustainable city planning using artificial neural networking

Predicting solar radiation in cities using the Artificial Neural Network model (ANN) is a pioneering step in transforming future-oriented city planning using solar energy. This research harnesses vast datasets to forecast the average annual solar radiation, considering minimal urban information across various urban attributes, including coordinates (X, Y, Z), average height, inhabited and non-occupied areas, and the Azimuth angle. Our method employed parametric design and remote sensing to generate this dataset and then used the ANN model to make predictions and simulations. Urban attributes of 20 cities were examined, including Casablanca, Abu Dhabi, Cape Town, Dublin, Havana, Melbourne, Rome, Singapore, Nairobi, Mumbai, New York, Nagoya, Sao Paulo, Tehran, Madrid, Toronto, Antananarivo, Beijing, Lisbon, and Paris. This data-driven approach trains our ANN model to discern complex and nonlinear relationships between independent and dependent variables and thus enables our model to predict solar radiation in urban cities. Our data training results indicate that the output (the minimum solar radiation each year of the cities) can be predicted using the study input variables with a loss of 0.01, a mean squared error of 0.01, and an R2-squared value of 85%. Such predictions can refine urban designs of buildings, public spaces, and various urban infrastructures to optimize solar energy use, reducing environmental impacts and fossil fuel reliance, thus aiding climate change mitigation and sustainability. Our findings underscore the integral association between solar radiation and sustainable urban evolution, giving urban planners and researchers sustainable strategies for advancing energy efficiency and ecological equilibrium.

The Economic Politics of Anti‐Displacement Struggle: Connecting Diverse and Community Economies Research with Critical Urban Studies on the Carpenters Estate, London

AbstractThis article explores the economic politics of anti‐displacement struggle, bringing into conversation critical urban studies and diverse and community economies research. It draws on my research and collaboration with a community planning group which emerged from residents’ and businesses’ struggle against displacement on the Carpenters Estate in Newham, London in 2012/13. My analysis makes visible the ways in which anti‐displacement struggle both animates and limits the production of new economic subjectivities, language, and possibilities for collective action. Ideas and tools from diverse and community economies research—lightly held and adapted for specific struggles and contexts—can help to support and strengthen these messy and fragile economic politics. The article advances diverse and community economies research on antagonism and the diversity of capitalism and contributes to re‐orienting critical urban research towards the production of economic alternatives.

Unveiling the roles of public bike systems: From leisure to multimodal transportation

As bike-sharing systems gain popularity, understanding their roles in urban transportation, such as the first/last mile problem and the replacement of public transit, is crucial to comprehensively promote urban transport systems. Due to the Internet of Things (IoT) technique, copious data from public bike trips worldwide are available to urban researchers. In this study, we examine how public bikes function not just as a means of transportation, but also for leisure. The leisure function was ignored in previous empirical studies using data mining techniques, an oversight that could skew results in places like Seoul where leisure trips constitute a significant portion of the trips. We investigate when, where, and to what degree bike-sharing serves as a leisure tool and substitutes for, integrates with, or complements the public transit system. We propose an integrated data-mining approach to identify the above four categories of public bike trips. Our method combines multiple sources of real-world data, the distributed density-based spatial clustering of applications with noise (DBSCAN), and spatial feature engineering. The results reveal that the distribution of each category shows substantial spatial–temporal heterogeneity. Longitudinal analysis reveals that the use of public bicycles as a transportation mode primarily contributes to the growth observed from 2018 to 2021, compared to use for leisure. The determining factors and non-linear functions of each type of bike trip were interpreted by explainable machine learning methods, Shapley additive explanations (SHAP), and partial dependence plot (PDP). We discovered that lower slopes, higher residential densities, and more commercial neighborhoods consistently attract users across all categories. Additionally, rivers and green areas attract more leisure trips, while areas with denser transit routes see more substitution trips and fewer complementary trips. By understanding the characteristics, spatial–temporal distribution, and determining factors of public bike trips across these four categories, city planners and operators can tailor services to meet the diverse needs of citizens, fostering a more convenient, sustainable, and accessible urban transport system.

A Comprehensive Bibliometric Analysis of Urban Renewal Research during 2012–2022

Rapid urban development has promoted economic development, but it has also created social problems. Urban renewal provides an important means of achieving sustainable urban development. After 2012, it became a research hotspot with people-oriented and organic renewal concepts. To understand the research trends in urban renewal during 2012–2022, a comprehensive bibliometric analysis was conducted to identify research progress, fields, hotspots, and trends. The core collection is based on the Web of Science (WoS) database, with a total of 2692 publications. The volume of publications, journal of publication, country, institution, research scope, and keywords were selected as the object of analysis. The results reveal that since 2012, the volume of urban renewal articles has been gradually increasing, reaching a maximum of 417 in 2022. China is the largest and most influential country in terms of the number of articles published, but the cooperation between institutions and authors is not strong. The research hotspots can be summarized as the connotation and practice of urban renewal, approaches to urban renewal, and sustainable urban development. Future directions for research are identified as including an innovative multi-corporate governance model, community-based renewal, further exploration of sustainable renewal practices, and interdisciplinary applications of urban renewal.

The relationship between urban transformation and sustainability: a bibliometric analysis and exploring existing trends

ABSTRACT Urban transformation and sustainability research are current issues in the construction industry. This study aims to comprehend the past and current trends in the relationship between urban transformation and sustainability through a literature review and bibliometric analysis, focusing on the themes that these studies concentrate on and determining the main subjects addressed within these themes. The study examined research articles that mention the concepts of “urban transformation” and “sustainability” in their title, abstract and keywords, published between 2002–2022 in the Scopus database. A total of 86 articles were analyzed in detail. The findings have clearly indicated 3 main issues of paramount importance: (1) Developing countries must prioritize sustainability in urban planning to align with global trends. (2) Collaborative initiatives involving diverse stakeholders are not just beneficial but essential for advancing sustainable urban development. (3) Integrating environmental, climate, and energy aspects into the framework of urban transformation and sustainability is not merely advantageous but crucial. This study contributes to the body of knowledge on urban transformation by providing a general framework and a systematized understanding of the issues related to urban transformation and sustainability. Furthermore, it is expected to raise awareness among implementers and policymakers regarding sustainable urban transformation issues that have emerged in recent years.

Identification and characterization of urban polycentric structure based on points of interest in Shenyang, China

AbstractAnalyzing the spatial agglomeration and characteristics of urban functional elements and effectively identifying the polycentric pattern of a city can provide a scientific basis for urban planning. This study, on the basis of point‐of‐interest (POI) data, designs a weighted overlay‐analysis method that is based on functional categories, spatial agglomeration, and POI weights to identify the spatial‐agglomeration pattern and polycentric urban structure of Shenyang, China. Our results show that Shenyang has a significant polycentric urban structure. The POI elements in the municipal center in the second ring road show concentration and a contiguous distribution pattern. The POI element distribution near the city is scattered, and the spatial distribution of hotspots is uneven. The urban centers in the city planned by the government and those that we have identified differ. Because of the remote location and insufficient support facilities, the municipal subcenters and district centers do not play the role of decentralization as intended. Further strengthening the overall industrial planning and transportation apparatus is necessary in order to enhance the outward radiation and inward attraction of municipal subcenters. Our weighted overlay method realizes effective identification of the polycentric urban structure and can provide relevant reference for urban research and planning.

Enhancing economic competitiveness analysis through machine learning: Exploring complex urban features.

Urban economic competitiveness is a fundamental indicator for assessing the level of urban development and serves as an effective approach for understanding regional disparities. Traditional economic competitiveness research that relies solely on traditional regression models and assumes feature relationship theory tends to fall short in fully exploring the intricate interrelationships and nonlinear associations among features. As a result, the study of urban economic disparities remains limited to a narrow range of urban features, which is insufficient for comprehending cities as complex systems. The ability of deep learning neural networks to automatically construct models of nonlinear relationships among complex features provides a new approach to research in this issue. In this study, a complex urban feature dataset comprising 1008 features was constructed based on statistical data from 283 prefecture-level cities in China. Employing a machine learning approach based on convolutional neural network (CNN), a novel analytical model is constructed to capture the interrelationships among urban features, which is applied to achieve accurate classification of urban economic competitiveness. In addition, considering the limited number of samples in the dataset owing to the fixed number of cities, this study developed a data augmentation approach based on deep convolutional generative adversarial network (DCGAN) to further enhance the accuracy and generalization ability of the model. The performance of the CNN classification model was effectively improved by adding the generated samples to the original sample dataset. This study provides a precise and stable analytical model for investigating disparities in regional development. In the meantime, it offers a feasible solution to the limited sample size issue in the application of deep learning in urban research.

Psychometric soundness and predictive factors of the NCAST Parent-Child Interaction Teaching Scale in urban Chinese population.

Quality of parent-child interaction in early childhood functions as a critical indicator of nurturing care and is strongly associated with short-term and long-term development (health, cognition, language, social emotion, well-being, etc.). NCAST PCI Teaching Scale (PCI-TS), a video-based assessment regarded as a gold standard to measure PCI, has been widely used worldwide. However, its psychometric soundness among the urban Chinese population is unclear. This study assesses the PCI-TS's reliability and validity and explores predictive factors among urban Chinese parent-child dyads. PCI-TS was adopted to code mother-child interaction among urban Chinese dyads recruited during the children's regular health checks in local maternal and child health centres. Reliability was evaluated by internal consistency (Cronbach'α coefficient) and test-retest reliability (Pearson correlation) with an average interval of 18 days. Score distribution of each subscale and total scale were compared with NCAST Database and Canadian community sample by single sample t-test. Criteria-related validity was conducted by Infant-Toddler Home Observation Measurement of the Environment (Pearson correlation). Predictive factors was performed by multiple linear regression. Four hundred and twenty-nine eligible mother-child dyads were included for data analysis among the 466 recruited samples. Four qualified local paediatricians accomplished video coding with an average agreement of 86%. The PCI-TS has strong reliability among the Chinese population with the Cronbach'α coefficients of the Caregiver-Infant total score, Caregiver total and Infant total scores of 0.81, 0.81 and 0.74, respectively; an acceptable test-retest reliability (r = 0.73, p < 0.01); and moderate correlation with IT-HOME, ranging from 0.53 to 0.62. Child age, birth weight, maternal education, full-time housewife, living with grandparent(s) and living space were predictive factors on PCI-TS in the Chinese population. PCI-TS showed good psychometric properties for measuring mother-child interactions among urban Chinese dyads, offering clinicians and researchers a practical tool to evaluate PCI objectively. Child age, maternal education and living space were beneficial factors, while full-time mothers and living with grandparent(s) were risk factors.

Distinct diurnal and nocturnal flower visitor communities provide pollination services in urban gardens

Abstract Urban gardens are considered a key tool for mitigating biodiversity and plant‐pollinator interaction loss due to their ubiquity in urban landscapes and the variety of resources they provide. To date, most urban garden pollination research has focused on diurnal pollination, omitting a potentially important group—nocturnal pollinators. To assess the diversity and pollination activity of both diurnal and nocturnal flower visitors in urban gardens, I monitored arthropods on focal inflorescences of Eupatorium perfoliatum, a common Michigan‐native species, for 24‐h cycles and recorded the number and duration of visits. I also measured diurnal and nocturnal communities' pollination services using a temporal floral visitation exclusion experiment. Flowers averaged nearly twice as many visits during the day as compared with night within 24‐h cycles, but nocturnal visit durations were 2.5‐fold longer on average. Day and night floral visitor communities were distinct, with day visits being dominated by Diptera, ants and other Hymenoptera, and night visits being carried out most frequently by ants, Dermaptera and Hemiptera. In the floral visitor exclusion experiment, plants open to only nocturnal visits produced larger seeds, whereas plants open to only diurnal visits trended towards producing more seeds, signalling a potential trade‐off between seed quantity and size among visitor communities. Overall, diurnal and nocturnal floral visitor communities were distinct, and nocturnally pollinated plants had reproductive output comparable to diurnally pollinated treatments. Given the emphasis on diurnal pollinators in most pollination studies, it is possible that relevant plant‐pollinator interaction information may be missed in cases where anthesis spans both day and night.

What Constitutes Engaged Dialogue in Urban Research? Thoughts From a Long Time “Outside-Insider”

In this plenary for the new journal Dialogues in Urban Research, I discuss what constitutes (and should constitute going forward) engaged dialogue in urban research. Engaged dialogue is the process of working collaboratively with groups of people, whoever they are, in relation to particular issues that affect them, to understand those issues better. So what does engaged dialogue in urban research look like? Who is engaging with who, where, why, and how? Has it changed over time? Most, if not all, urban research engages beyond academia, but that engaged dialogue rarely makes it into the pages of academic journals in an inclusionary way. Who usually takes part in conversations on urban research in journals, but also who does not (or is less likely to), and who should? In a new world of publishing and government-funded research that is promoting open access, making research more publicly accessible and inclusive, there has been much less discussion of those engaged in the dialogue that is published. And, if academics do publish with nonacademics it is not usually in an academic journal; this is not inclusive, indeed it is exclusionary.

Understanding the neighborhoods’ in-between spaces on spatial perception, social interaction, and security

This study reflects on the impact that the neighborhoods' in-between spaces have on: spatial perception, social interaction, and security. These sites, characterized by their abandonment and deterioration, can also be seen as crucial spaces of opportunity for cities, in the architectural, urban and landscape research. This paper aims to analyze the socio-spatial relationships in the neighborhoods’ in-between spaces and examine the impact of in-between space configuration on urban habitability. The investigation draws on a survey of perception to residents about the requirements for a suitable social interaction in these spaces. This study was developed in a neighborhood in the city periphery, characterized by their social dynamics and location in a nature conservation area. The findings indicate that the appropriation process, activities, and collective practices are dependent on the spatial legibility, in this case when this increases, gives rise to improve the habitability and the rehabilitation of the in-between space. Furthermore, the lack of design on in-between spaces substantially affects the use of these spaces and the social interaction among residents.

Use of machine learning in understanding transport dynamics of land use and public transportation in a developing city

Rapid urbanization has resulted in problems with pollution, traffic congestion, and public transportation in cities worldwide. Much urbanization research disproportionately focuses on cities in developed countries, where data is easier to obtain, to the detriment of cities in developing countries. To help address this gap, our work proposes a machine learning methodology that explores how land use patterns contribute to predicting an aspect of public transportation in growing cities (aggregate public vehicle speeds), with Cauayan City in the Philippines as the test case. We trained gradient-boosting tree models with road properties, day and time, and land use data as features to predict vehicle speeds on various roads in the city. Among various feature combinations used in training, the best model used road, time, and land use features over a range buffer radii of 50 to 1000 m, yielding an R2 of 0.676 (0.003) and a root mean squared error of 6.61 (0.03) kph. Apart from predicting speeds, Shapley's additive explanation (SHAP) values show that proximity to dense residential and commercial areas decreases predicted vehicle speeds. Our approach uses interpretable machine learning models to obtain insights about urban transportation in developing cities.