Urban Problems Research Articles

The role of eco-attraction in the intention to conduct low-carbon actions: a study of visitor behavior in urban forests

The role of eco-attraction in the intention to conduct low-carbon actions: a study of visitor behavior in urban forests

A Bayesian Spatial Model to Correct Under-Reporting in Urban Crowdsourcing

Decision-makers often observe the occurrence of events through a reporting process. City governments, for example, rely on resident reports to find and then resolve urban infrastructural problems such as fallen street trees, flooded basements, or rat infestations. Without additional assumptions, there is no way to distinguish events that occur but are not reported from events that truly did not occur--a fundamental problem in settings with positive-unlabeled data. Because disparities in reporting rates correlate with resident demographics, addressing incidents only on the basis of reports leads to systematic neglect in neighborhoods that are less likely to report events. We show how to overcome this challenge by leveraging the fact that events are spatially correlated. Our framework uses a Bayesian spatial latent variable model to infer event occurrence probabilities and applies it to storm-induced flooding reports in New York City, further pooling results across multiple storms. We show that a model accounting for under-reporting and spatial correlation predicts future reports more accurately than other models, and further induces a more equitable set of inspections: its allocations better reflect the population and provide equitable service to non-white, less traditionally educated, and lower-income residents. This finding reflects heterogeneous reporting behavior learned by the model: reporting rates are higher in Census tracts with higher populations, proportions of white residents, and proportions of owner-occupied households. Our work lays the groundwork for more equitable proactive government services, even with disparate reporting behavior.

Путь эстетика в искусстве (К юбилею Е.Н. Устюговой)

<span lang="EN-US">The article is dedicated to E. N. Ustyugova, a famous Russian scientist, specialist in the field of aesthetics and philosophy of culture. The article indicates the main areas of research by E. N. Ustyugova, including: the </span><span lang="EN-US">history of aesthetics, </span><span lang="EN-US">the history of artistic styles, the art and aesthetics of the Russian avant-garde, environmental aesthetics, ethical and aesthetic problems of modern urbanism, the city as a unity of the ecology of nature and the ecology of culture, etc. It is noted that E. N. Ustyugova is a constant organizer and participant of such significant scientific events </span><span lang="EN-US">as the Russian Aesthetic Congress, </span><span lang="EN-US">the scientific conference “Kaganov Readings” (Institute of Philosophy of St. Petersburg State University), the international scientific conference “Polylogue and synthesis of arts: history and modernity, theory and practice” (St. Petersburg State Conservatory named after N. A. Rimsky-Korsakov), scientific and practical seminar “Current Aesthetics” (Institute of Philosophy of St. Petersburg State University) and many others. The article is based on impressions from the author’s personal acquaintance with Professor E. N. Ustyugova in the period from 2009 to the present.</span>

Revisiting Equity in Urban Operations Management 50 Years Later: What do City Planners Have to Say?

The persistent inequities in American cities—long recognized and lived by black and Hispanic people and other minorities, the poor and working class, and others disadvantaged by urban systems—have been vaulted into the broader public consciousness over the past decade. Lessening entrenched urban inequalities is now at the top of the national policy agenda, suggesting a need and opportunity for more urban operations management. On what issues and how might this work occur? Operations management was deeply intertwined with urban planning in research and practice from the 1950s through the 1970s, at which point the fields diverged. To build a case for what perspectives and approaches a modern urban operations management agenda might employ to address inequity, I synthesize historical and contemporary planning theory with the debates among reflective operations scholars in the 1950s-1970s over work on cities. Modern operations scholars can look to planning, and especially to recent major shifts in its thinking on race and class, to address urban operations that disadvantage some city residents and overly advantage others. This urban operations agenda should be empirical, equity-oriented, and community-focused in order to best resonate with planners and the city residents they serve. In reengaging with planners to tackle the modern range of urban policy problems, operations analysts have a chance to contribute practical clarity on how cities work and can be made more livable for all residents.

Türkiye’de Büyükşehirlerde Kent İçi Ulaşım Sorunları ve Çözüm Önerileri: Ankara İli Örneği

Kent içi ulaşım, insanların bir yerden başka bir yere güvenli, hızlı ve emniyetli bir şekilde taşınması açısından önemlidir. Her geçen gün artan nüfus ile birlikte ulaşım talebinin ve araç sayısının artması sonucunda trafik sıkışıklığı, hava ve gürültü kirliliği, trafik kaza sayısının artması gibi problemleri de beraberinde getirmektedir. Bu çalışmada Türkiye’de kent içi ulaşım sorunları konusunda literatür araştırması yapılarak Adana, Bandırma, Bitlis, İzmir, Eskişehir, Isparta ve İstanbul şehirleri incelenmiştir. Büyükşehir belediyelerinde yaşanan sorunların Ankara ile benzer sorunlar içerdiği tespit edilmiştir. Ankara İli’ndeki kent içi ulaşım sorunları incelenerek çözüm önerilerinde bulunulmuştur. Çalışma kapsamında Ankara’da 125 kişi ile anket çalışması yapılmıştır. Anket sonucuna göre, Ankara’da kent içi ulaşımda sorunlar öncelik sırası olmak üzere, %50,4 oranı ile trafik sıkışıklığı ve park etme zorlukları ilk sırada, %18,4 oranı ile toplu taşımanın yetersizliği ikinci sırada, %7,2 oranı ile yolculuk süresinin uzun sürmesi üçüncü sırada, %5,6 oranı ile planlama sorunları dördüncü sırada, %4,8 oranı ile ulaşım altyapı sorunları ve yetersizliği beşinci sırada, % 3,2 oranı ile finansman sorunları altıncı sırada, %2,4 oranı ile toplu taşımanın konforsuz ve güvensiz olması ise yedinci sırada yer almaktadır. Ankara’da kent içi ulaşım sorunlarına çözüm önerisi öncelik sırasına göre birinci sırada %22,4 oranı ile kişisel hareketlilik için bisiklet yollarını ve kullanımının artırılması, %19,2 oranı ile toplu ulaşımın daha cazip hale getirilmesi ikinci sırada, %14,4 oranı ile kent içi ulaşımda entegrasyon ve koordinasyonun sağlanması üçüncü sırada, %12,0 oranı ile sürdürülebilir ulaşım ana planının yapılması dördüncü sırada, %6,4 oranı ile tek tip bilet sistemini (elektronik bilet sistemi) otobüs, minibüs, taksi ve raylı sistemler tümünde uygulanması beşinci sırada, %4,8 oranı ile park yerlerinin artırılması ise altıncı sırada yer almaktadır. Kent içi ulaşımda sorunlara çözüm önerileri; otomobil kullanımını caydırıcı önlemler alınması, ulaşım türlerinde koordinasyon ve entegrasyon sağlanması, toplu ulaşımın daha cazip hale getirilmesi için politikalar geliştirilmesi, ulaşımın çok yönlü yapısı dikkate alınarak planlar yapılması şeklinde sıralanabilir.

Parametric analysis of the influence of climatic factors on the formation of traditional buildings in the city of Al Najaf

Abstract One of the key variables that can affect energy consumption in a building is the shape of the structure. The current study aims to balance the using solar radiation (lighting, heating, and cooling) and energy consumption by analyzing climatic factors’ effect on building formation systems’ standards. The research shows the mechanism of reaching optimal solutions in building performance problems using evolutionary algorithms as a reliable strategy. By examining the formation of compact fabric elements, the mass of the building on the site is compared with the parametric model adapted to the context to find out the negatives and positives according to the heat gain for each. The research relied on analytical and descriptive methods to clarify the determinants. The analysis included three main axes, the urban characteristics, the urban climatic compatibility in the study area, and parametric analysis. According to the results, shaped building blocks can simultaneously enhance indoor daylight levels and energy performance. Using the framework as a reference model can increase the chances of solving complex urban design problems earlier and recommend sustainable building designs.

Does Grit Compensate for Family Background Disadvantage in Predicting Mental Health Difficulties? A Longitudinal Study of Chinese Migrant and Urban Children.

The significant population of Chinese rural-to-urban migrant children has sparked considerable domestic and international concern regarding their disadvantaged family circumstances and their escalating prevalence of internalizing and externalizing problems. Derived from the resource substitution hypothesis, non-cognitive factors such as personality traits may act as "substitution" resources for educational outcomes of children from less privileged families. Yet, the compensatory role of personality traits as substitution resources in children's mental health has received limited attention, including that of migrant children. This study examined the interplay of trait-like grit and family SES on emotional and conduct problems among Chinese migrant and urban children. The current sample consisted of 770 migrant children (Mage = 10.45 and SDage = 0.68 years; 38.4% girls) and their 222 urban counterparts (Mage = 10.34 and SDage = 0.46 years; 45.5% girls). Moderated polynomial regressions with response surface analysis on a two-wave data with an interval of over six months showed that grit served as a "substitution" resource for the less socioeconomically advantaged children. The compensatory effect of perseverance of effort on urban children's emotional problems and that of consistency of interest on migrant children's conduct problems were visualized. Moreover, the two compensatory effects were found to be robust and unique, even after children's effortful control, a grit-related construct, was taken into account. These findings not only support the resource substitution hypothesis, but also underscore the protective role that grit plays in children under less privileged environments.

Upgrading informal areas through sustainable urban development principles

Informal areas are considered one of the biggest urban problems worldwide; it was estimated in 2018 that 29% of the world’s urban population lived in informal areas (The world bank, Population living in slums, 2022). This research aimed to identify a set of criteria and principles that are the basis for sustainable development in informal areas to achieve a better quality of life for the community. After conducting a literature review of the sustainable development principles, indices, and sustainable development interventions within informal areas, the research links them to set informal areas’ sustainable development principles. Then, by relying on the experts’ questionnaires and their analysis through SPSS, the researchers utilized the experts’ input to define each principle’s relative weight. Additionally, the research applied the extracted principles to the Boulaq El Dakrour case study to assess the sustainability of previous developments undertaken in the area with community participation.

An artificial fish swarm optimization algorithm for the urban transit routing problem

The Urban Transit Routing Problem (UTRP) is an NP-hard discrete problem that deals with the design of routes for public transport systems. It is a highly complex, multiply constrained problem, while the evaluation of candidate route sets can prove both challenging and time-consuming, with many potential solutions rejected on the grounds of infeasibility. Due to its difficulty, metaheuristic methods, such us swarm intelligence algorithms, are considered highly suitable for the UTRP. The suitability of these methods heavily relies on the correct adaptation of the chosen method for a discrete-space problem, the initialization procedure, and the solution evaluation method. In this context, this study proposes an artificial fish swarm optimization algorithm for the efficient solution of the UTRP, presenting a novel discrete-space adaptation of the former. The results are subsequently compared to 14 other algorithms, including evolutionary, swarm intelligence and hyper-heuristic implementations, using Mandl’s widely used and accepted benchmark. Comparison of the produced solutions with published results on Mandl’s benchmark network, shows that the developed algorithm yields superior results to the existing techniques, yielding very high shares of direct trip coverage, which is vital for transit systems to attract riders and contribute to urban sustainability. A new indicator for operator cost calculation is also developed and integrated into our analysis, offering insights on the trade-offs between user and operator costs. Differences in generated solutions, influenced by the weighting factor value, can result in variations of up to 13% in direct trip coverage and 1.5 minutes in average travel time.

Predicting the longitudinal patterns of housing affordability stress: Evidence from the Korea Welfare Panel Study

As housing costs increase faster than salary and wage growth worldwide, housing affordability stress (HAS) becomes an increasingly crucial urban problem. However, little evidence exists on under what preconditions HAS experiences are likely to be persistent. This study examines the predictors of chronic forms of HAS experiences in the Korean housing market, characterized by a unique tenure system represented by Jeonse renting (i.e., renting only with a security deposit) and severe regional disparities between the Capital region and the rest of the country. After classifying the longitudinal patterns of HAS between 2011 and 2020, we examine under which preconditions between 2007 and 2010 households were likely to experience chronic forms of HAS. The results reveal that certain combinations of household income, housing tenure choice, and location of residence significantly heighten the probability of experiencing chronic forms of HAS. This study contributes to the literature by highlighting the importance of the longitudinal view of HAS experiences and expanding knowledge about the potential mechanisms that drive chronic forms of HAS.

First mile and last mile analysis using users’ perceived quality of Jakarta Mass Rapid Transit (MRT Jakarta) North-South Corridor Phase 1

To address urban problems caused by high usage of private vehicles, it is important to understand how MRT Jakarta as a new public transportation mode in Jakarta, could support the mobility needs of its users not only within MRT stations but also throughout the entire journey from origin to destination. This study aims to analyze the socio-demographic characteristics of MRT Jakarta users, the first mile and last mile spatial mobility pattern, and the perceived quality of overall journey using MRT Jakarta. An online questionnaire was employed to collect data directly from MRT Jakarta users, encompassing socio-demographic information, spatial mobility patterns, and users’ evaluations on several influencing factors. The study concludes that improving the quality of the first mile segments can significantly improve the overall journey quality using MRT Jakarta.

The Difficulties and Explorations of Old Community Retrofitting Based on the Sponge City Concept - The case of 240 community in the old urban area of Xi'an

The rapid development of China's urban modernization has become an important driving force for the flourishing of various economic, social and cultural sectors. At the same time, the process of urbanization has led to the serious phenomenon of "urban diseases", particularly urban water problems. To effectively mitigate the negative impacts of urban floods and droughts, China has proposed a nature-based solution - the sponge city concept. Furthermore, urban renewal initiatives and the Old Urban Renewal Programme (OURP) are vital components in sustainable development to ensure quality urban development and enhance residents' health and well-being.

Smart Healthcare Management Model for Proactive Patient Monitoring

The rapid development of Artificial Intelligence (AI) is leading urban centers to employ AI technologies to improve efficiency and solve urban problems. This research proposes a Centralized System Model for Smart Cities (CSMSC) that centralizes AI-oriented data acquisition, processing, and decision-making. CSMSC uses real-time sensor networks for data collection, sophisticated AI algorithms for nuanced data interpretation, and unified storage for streamlined information management. Additionally, CSMSC integrates AI-based analyzers to autonomously produce alerts, evaluate their urgency, and decide upon suitable responses, enabling quick and targeted city interventions. The paper combines field evidence with theoretical frameworks to highlight the transformative potential of cognitive sensing and machine learning in smart city development. Recent studies have shown that AI on edge is revolutionizing the infrastructure of smart cities by bringing advanced intelligence and real-time analytics closer to the data source. AI on edge enables real-time decision-making, reduces latency, optimizes bandwidth usage, and enhances privacy and security. The potential benefits of using data analytics in smart cities are significant, and future research should focus on developing new algorithms and tools to analyze data and explore new IoT and machine-learning applications.

Principles of revitalization of peripheral urban areas

The article examines the principles of revitalization of peripheral urban areas, problems and potential for their development. An overview of European and Russian experience in the renovation of industrial zones is presented. It explores ways to transform and revitalize areas that often suffer from decline and lack of socio-economic development, and examines various methods and strategies that can be used to attract investment and improve the quality of life in peripheral areas. The article draws on research conducted in various countries and cities to identify common principles and best practices.

Представления жителей о городской среде и запросы на ее изменение в регионах ресурсного типа (на примере г. Кемерово)

The article examines residents' perceptions of the urban environment in a resource-type region. The ideas are identified, and key requests for changing the urban environment are analyzed. The purpose of the article is to identify the ideas of the urban environment and analyze the key requests of residents to change it. Depending on the experience of interaction with the urban environment, general and personalized requests are formed. The presented study, includes a questionnaire survey and the focus group interview with the residents of Kemerovo. The focus group interview was attended by such groups of citizens as “Schoolchildren”, “Old-timers of the city”, a group of representatives of the cultural and educational sphere of the city, “City activists”. As a result, ideas about the history of the city, the problems of the territory, the uniqueness of the city and the future of the city are highlighted. The ideas about the city are formed under the influence of various factors, such as an age, an occupation, a level of education, etc. “Schoolchildren” perceive the city as a place of birth and study; “Old-timers” do it through the prism of their experience, including professional; “Historians, cultural experts” see the city as a reflection of history, and “Urban activists” see a space for the changes and the implementation of their projects. In the minds of Kemerovo residents, industry is an important part of the city; on the other hand, the transition to new sectors of development is important for residents. It was revealed that residents, even when articulating a request to change the urban environment, prefer to play passive roles in the process of solving urban problems. Kemerovo residents are aware of the problems of the urban environment, but are not ready for concrete actions to solve them.

Enhancing Urban Data Analysis: Leveraging Graph-Based Convolutional Neural Networks for a Visual Semantic Decision Support System.

The persistent increase in the magnitude of urban data, combined with the broad range of sensors from which it derives in modern urban environments, poses issues including data integration, visualization, and optimal utilization. The successful selection of suitable locations for predetermined commercial activities and public utility services or the reuse of existing infrastructure arise as urban planning challenges to be addressed with the aid of the aforementioned data. In our previous work, we have integrated a multitude of publicly available real-world urban data in a visual semantic decision support environment, encompassing map-based data visualization with a visual query interface, while employing and comparing several classifiers for the selection of appropriate locations for establishing parking facilities. In the current work, we challenge the best representative of the previous approach, i.e., random forests, with convolutional neural networks (CNNs) in combination with a graph-based representation of the urban input data, relying on the same dataset to ensure comparability of the results. This approach has been inspired by the inherent visual nature of urban data and the increased capability of CNNs to classify image-based data. The experimental results reveal an improvement in several performance indices, implying a promising potential for this specific combination in decision support for urban planning problems.

Two-step AI-aided Bayesian source identification of urban-scale pollution

Poor air quality produces detrimental effects worldwide; hence, it is vital to thoroughly characterize air pollution sources and effectively address and mitigate such effects. Due to the complexity of the underlying physical processes, and uncertainties in the available observations, the air pollution source identification problem is typically cast within a Bayesian inversion framework. The latter incorporates prior knowledge and observations to characterize a release event through the posterior distribution of the source parameters. In this study, we rely on two-dimensional (2D) pollutant concentration distributions as observations, and adopt the Wasserstein (W2) distance to model the likelihood probability distribution for given emission parameters. Since the posterior distribution is estimated via random sampling that involves many forward model runs, the Bayesian framework can be computationally prohibitive for realistic urban air pollution problems that are driven by computationally demanding micro-scale flow simulations. Furthermore, computing the W2 distance is resource-intensive . In this context, we develop a computationally efficient Bayesian framework by following (i) a two-stage approach that reduces the cost of the Bayesian inversion, and (ii) an artificial intelligence (AI) approximation of the W2 distance. In the two-stage approach, a low-resolution dispersion model is run in the first stage to propose representative samples of emission parameters for final selection by the original high-resolution model in the second stage. In addition, we approximate the W2 distance using a deep neural network (DNN) to achieve an appreciable reduction in the computational cost with negligible loss in the inversion performance. We design numerical experiments to test the sensitivity of the inverse solution to the characteristics of the approximative model. The results indicate that pairing the two-stage approach with the DNN approximation of the W2 distance preserves the quality of the inverse solution, while achieving at least threefold reductions in the computational cost.

Study on the Spatial Arrangement of Urban Parkland under the Perspective of Equity—Taking Harbin Main City as an Example

The connotation and measurement standard of “fairness” in parkland planning is closely related to the level of urban development and residents’ needs, with solid realism and dynamics, and it is still a complex problem to control accurately in planning. Therefore, to conduct a more comprehensive study, taking the main urban area of Harbin as an example, this paper combined urban development background and practical problems at different stages and, based on POI and AOI data, divided the connotation of “equity” in park green space planning into two levels: “spatial equity” and “social equity”. Based on these two levels of fairness, the research framework of urban park green space layout is constructed. Kernel density estimation and GIS-based network analysis were used to study the spatial layout and accessibility of urban parkland. The ability to match supply and demand for parkland in the study area as a whole was analyzed using a gridded two-step moving search method, as well as the degree of equity in the enjoyment of urban parkland by vulnerable groups including the elderly and children using the Lorenz curve with the Gini coefficient, the share index, and the entropy of the locality. The results show that: (1) the parkland is concentrated in the seven main urban areas of the two–two junctions, and the cohesion distribution trend is outside the distribution. (2) Motorized vehicles have the best 15-min accessibility for travel, but it still does not cover all the parkland. (3) Supply and demand within the region are unsatisfactory, with the area with the strongest supply and demand capacity for parkland accounting for only 3.19% of the total area. (4) The Gini coefficient of parkland enjoyed by the residents of Harbin city center is 0.407, with a massive gap in the overall distribution. In addition, the share index of vulnerable groups of the elderly and children all have share indices below 1, and the results of the analysis of locational entropy indicate that the level of street park green space resources enjoyed by these two groups belongs to the low socio-spatial equity pattern, which is not balanced. This study investigates the spatial layout of urban parkland from two equity levels, which can provide new ideas for the equity study of urban green space planning.

Integrating Machine Learning in Urban Pedagogy: Addressing Homelessness in Skid Row

This paper investigates the application of machine learning in urban and architectural education, with a focus on addressing homelessness in Skid Row, Los Angeles. It presents a case study of an urban design studio utilizing data-driven methods to propose transitional housing solutions, emphasizing the importance of design in the context of social justice. The study explores the use of machine learning and digital cartography for a detailed analysis of Skid Row’s dense homeless population, offering students a thorough insight into urban challenges. The research also identifies the complexities involved in integrating these technologies into educational frameworks, including issues with data accuracy, technical hurdles, and ethical considerations. The paper concludes by advocating for an interdisciplinary, data-informed, and socially conscious approach in architectural and urban design education, highlighting its necessity in preparing students to effectively tackle contemporary urban problems.

Cause Identification and Coupling Relationship Analysis of Urban Problems: A Case Study of Poor Parking Convenience

As the size and complexity of cities around the world increase, various types of urban problems are emerging. These problems are caused by multiple factors that have complex relationships with each other. Addressing a single cause blindly may result in additional problems, so it is crucial to understand how urban problems arise and how their causes interact. The study utilizes the Grey Decision-Making Trial and Evaluation Laboratory (Grey-DEMATEL), in conjunction with the Grey Interpretative Structural Model (Grey-ISM), to construct a hierarchical structure that examines the relationships between the causes of urban problems, thereby revealing the root causes and developmental mechanisms of urban problems. The Grey Matrix Cross-Reference Multiplication Applied to Classification (Grey-MICMAC) method was employed to clarify the influence and position of each cause. The Poor Parking Convenience (PPC) in Wuhan, China, is taken as a case study. The findings reveal the following: (1) the proposed method effectively identifies the key causes and processes of urban problems; (2) the insufficient management of roadside parking areas and impractical allocation of temporary parking spaces are the two main causes of PPC in Wuhan City. This method would be helpful to urban managers in discovering the causes of urban problems and formulating corresponding policies, to ultimately contribute towards healthy urban and sustainable development.