Hasil untuk "Urban groups. The city. Urban sociology"

Adeb Ali Ebrahim

The primary drivers of agricultural land depletion in Taiz be diagnosed quantitatively in this study, proposing for the first time a replicable conflict-sensitive urban management model. The overarching objective is to bridge the critical gap between sustainable urban expansion and the preservation of agro-ecological systems in fragile, data-scarce contexts. A combination of unplanned sprawl, crisis, and ineffective governance, Taiz City's rapid urbanization between 2000 and 2024 resulted in a 35% loss of agricultural land. This study proposes that governance reduces the primary causes of conflict escalation and the severity of sprawl. This study combines GIS spatial analysis (Landsat 8/9 and support vector machine classification), regression modeling, and global case comparisons (Medellín and Mumbai) to assess land-use trends. The findings indicate that governance diminishes the effects (β = −0.50, p < 0.01), sprawl (β = 0.85, p < 0.01), and conflict (β = 0.002, p < 0.05) explain 85% of the variance in losses. By 2024, 3.2 million residents' food security was at risk because of the urbanization of 60% of peri-urban fertile lands. Vertical expansion, tenure regularization and GIS planning will reclaim 20% of land by 2030.

Mingya Duan, Michael Urban

Many common Skyrme functionals present ferromagnetic instabilities or unrealistic density dependence of the spin-dependent Landau parameters. To solve these problems, we consider the Skyrme interaction as a density-functional rather than a density-dependent two-body force. This allows us to adjust the spin-dependent terms of the new extended Skyrme functionals of our previous paper [M. Duan and M. Urban, Phys. Rev. C 110, 065806 (2024)] independently without altering the properties of spin saturated matter. The parameters of the spin-dependent terms are determined by fitting the Landau parameters $G_0$ and $G'_0$ in neutron matter and symmetric nuclear matter and the effective-mass splitting of up and down particles in spin polarized matter to the results of microscopic calculations. Using the new parametrizations, called Sky3s and Sky4s, the spin-related properties of nuclear matter are in good agreement with the microscopic results. As an application, we compute response functions and neutrino scattering rates of neutron-star matter with the new functionals having realistic effective masses and Landau parameters.

Linh Do-Bui-Khanh, Thanh H. Nguyen, Nghi Huynh Quang et al.

As Electric Vehicle (EV) adoption accelerates in urban environments, optimizing charging infrastructure is vital for balancing user satisfaction, energy efficiency, and financial viability. This study advances beyond static models by proposing a digital twin framework that integrates agent-based decision support with embedded optimization to dynamically simulate EV charging behaviors, infrastructure layouts, and policy responses across scenarios. Applied to a localized urban site (a university campus) in Hanoi, Vietnam, the model evaluates operational policies, EV station configurations, and renewable energy sources. The interactive dashboard enables seasonal analysis, revealing a 20% drop in solar efficiency from October to March, with wind power contributing under 5% of demand, highlighting the need for adaptive energy management. Simulations show that real-time notifications of newly available charging slots improve user satisfaction, while gasoline bans and idle fees enhance slot turnover with minimal added complexity. Embedded metaheuristic optimization identifies near-optimal mixes of fast (30kW) and standard (11kW) solar-powered chargers, balancing energy performance, profitability, and demand with high computational efficiency. This digital twin provides a flexible, computation-driven platform for EV infrastructure planning, with a transferable, modular design that enables seamless scaling from localized to city-wide urban contexts.

Yingche Liu, Mengyang Li

The massive digital footprints generated by bike-sharing systems in megacities like Shanghai offer a novel perspective on the urban socio-economic fabric. This study investigates whether these daily mobility patterns can quantitatively map the city's underlying social stratification. To overcome the persistent challenge of acquiring fine-grained socio-economic data, we constructed a multi-layered analytical dataset. We annotated 2,000 raw bike trips with local economic attributes, derived from a novel data enrichment methodology that employs a Large Language Model (LLM), and integrated contextual features of the built environment. A Random Forest model was then utilized as an interpretable framework to determine the key factors governing the relationship between mobility behavior and local economic status. The analysis reveals a compelling and unambiguous finding: a neighborhood's economic level, proxied by housing prices, is the single most dominant predictor of its bike-sharing patterns, substantially outweighing other geographic or temporal factors. This economic determinism manifests in three distinct ways: (1) a spatial clustering of resources, a phenomenon we term the \textit{club effect}, which concentrates mobility infrastructure and usage in affluent areas; (2) a functional dichotomy between necessity-driven, utilitarian usage in lower-income zones and flexible, recreational usage in wealthier ones; and (3) a nuanced inverted U-shaped adoption curve that identifies the urban middle class as the system's primary user base.

Saannidhya Rawat

We exploit quasi-random variation around the multi-threshold criteria used to classify Census Towns (CTs) and focus on settlements near the thresholds that are likely to obtain statutory recognition. Using a local fuzzy regression discontinuity design and a multi-threshold criteria, we show that meeting the CT eligibility in 2001 raises the probability of statutory recognition by 2011. Instrumenting statutory recognition with CT eligibility, we estimate the effects of ULB status on local public goods provision: government schools increase by 13.86 (primary), 7.72 (middle), and 4.89 (secondary) units, healthcare infrastructure expands by 2.53 hospitals and 3.00 family welfare centers, and financial access deepens with 4.09 cooperative banks and 2.84 agricultural credit societies. Community amenities also improve, while sports infrastructure declines by 5.71 facilities, consistent with reallocation of urban land. The corresponding reduced-form estimates are directionally consistent and indicate that crossing the CT eligibility frontier improves public goods provision. Our findings indicate that timely municipalization of emerging urban areas can expand provision of public goods.

علی اکبر سالاری پور, آرمان حمیدی, عالیه فریدی فشتمی et al.

امروزه بخش بزرگی از رفتارهای محیط زیستی شهروندان تحت تأثیر ارتباط و میزان دلبستگی آن‍ها با شهر است. به‌طوری‌که دلبستگی به مکان و شهر مؤلفه‌ای حیاتی در پرورش شهروندان حامی محیط‌زیست محسوب می‍گردد. پژوهش حاضر از نوع توصیفی- کمی می‍باشد. جهت جمع‍آوری اطلاعات باهدف سنجش تأثیر میزان دلبستگی به شهر و همچنین خصوصیات فردی شهروندان، بر بروز رفتارهای حامی محیط زیستی در میان شهروندان، تعداد 402 پرسشنامه از طریق ساکنین شهر رشت تکمیل شده است. داده‍های به‌دست‌آمده از پرسشنامه‍ها به‌صورت کمی وارد نرم‌افزار SPSS شده و سپس با استفاده از نرم‌افزار Smart PLS3 به مدل‌سازی و تجزیه‌وتحلیل یافته‍ها پرداخته شده است. نتایج پژوهش نشان داد که برخلاف انتظار رابطه تأثیرگذاری میان شاخص‍های دلبستگی فردی به مکان، محل تولد، مدت سکونت و میزان تحصیلات بر رفتارهای حامی محیط زیستی شهروندان، وجود ندارد؛ اما از سوی دیگر نتایج مدل‌سازی نمایانگر این موضوع بود که در گام نخست رفتارهای حامی محیط زیستی شهروندان بیش‍ترین ارتباط و اثرپذیری را از دلبستگی اجتماعی شهروندان با مکان یا شهر دارند. سپس در گام بعدی تعدادی از ویژگی‌های فردی شهروندان ازجمله سن و وضعیت تأهل نیز بر رفتارهای حامی محیط زیستی شهروندان تأثیرگذار می‌باشد و رابطه مستقیمی میان آن‌ها برقرار است.

Halil Burak Akdeniz, Sinan Levend, Şaban İnam

Global climate change, one of the most important problems of today, and human activities have negative effects on the sustainability of natural resources. It has become necessary to establish planning and management mechanisms for the sustainable use of drinking water basins within the protection-use balance. Beyşehir Basin, Türkiye was chosen as the study area. The aim of this study is to present a new model approach for the use of Analytical Hierarchy Process and Geographic Information Systems, based on the unique topographic, hydrological, and environmental characteristics of the basin, in the determination of the drinking water basin protection zones. Thirteen criteria, which affect the reaching of the pollutants to the water surface and reflect the topographic, hydrological, and environmental characteristics of the basin, were used in the determination of the protection zones. As a result of the study, it was determined that 2.83% of the basin is in the absolute protection zone, 44.97% in the short-range protection zone, 35.93% in the medium-range protection zone and 16.26% in the long-range protection zone. In the last stage, the conservation areas determined by the current legal regulations for the basin and the protection zones determined by the model approach were spatially and areally compared. According to the results of the comparison, it was determined with the proposed protection model that the absolute protection, the short-range protection, and the medium-range protection zones increased areally, and the spatial distributions of these protection zones were shaped according to the structure of the basin.

Zicheng Fan, Chen-Chieh Feng, Filip Biljecki

Street View Imagery (SVI) has emerged as a valuable data form in urban studies, enabling new ways to map and sense urban environments. However, fundamental concerns regarding the representativeness, quality, and reliability of SVI remain underexplored, e.g. to what extent can cities be captured by such data and do data gaps result in bias. This research, positioned at the intersection of spatial data quality and urban analytics, addresses these concerns by proposing a novel and effective method to estimate SVI's element-level coverage in the urban environment. The method integrates the positional relationships between SVI and target elements, as well as the impact of physical obstructions. Expanding the domain of data quality to SVI, we introduce an indicator system that evaluates the extent of coverage, focusing on the completeness and frequency dimensions. Taking London as a case study, three experiments are conducted to identify potential biases in SVI's ability to cover and represent urban environmental elements, using building facades as an example. It is found that despite their high availability along urban road networks, Google Street View covers only 62.4 % of buildings in the case study area. The average facade coverage per building is 12.4 %. SVI tends to over-represent non-residential buildings, thus possibly resulting in biased analyses, and its coverage of environmental elements is position-dependent. The research also highlights the variability of SVI coverage under different data acquisition practices and proposes an optimal sampling interval range of 50-60 m for SVI collection. The findings suggest that while SVI offers valuable insights, it is no panacea - its application in urban research requires careful consideration of data coverage and element-level representativeness to ensure reliable results.

Lucy Jiang, Jon E. Froehlich, Leah Findlater

Public artwork, from vibrant wall murals to captivating sculptures, can enhance the aesthetic of urban spaces, foster a sense of community and cultural identity, and help attract visitors. Despite its benefits, most public art is visual, making it often inaccessible to blind and low vision (BLV) people. In this workshop paper, we first draw on art literature to help define the space of public art, identify key differences with curated art shown in museums or galleries, and discuss implications for accessibility. We then enumerate how existing art accessibility techniques may (or may not) transfer to urban art spaces. We close by presenting future research directions and reflecting on the growing role of AI in making art accessible.

Johannes Janning, Sophie F. Armanini, Urban Fasel

The rapid development of advanced urban air mobility, particularly electric vertical take-off and landing (eVTOL) aircraft, requires interdisciplinary approaches involving the future urban air mobility ecosystem. Operational cost efficiency, regulatory aspects, sustainability, and environmental compatibility should be incorporated directly into the conceptual design of aircraft and across operational and regulatory strategies. In this work, we apply a novel multidisciplinary design optimization framework for the conceptual design of eVTOL aircraft. The framework optimizes conventional design elements of eVTOL aircraft over a generic mission and integrates a comprehensive operational cost model to directly capture economic incentives of the designed system through profit modeling for operators. We introduce a novel metric, the cross-transportation Figure of Merit (FoM), to compare the optimized eVTOL system with various competing road, rail, and air transportation modes in terms of sustainability, cost, and travel time. We investigate four objective-specific eVTOL optimization designs in a broad scenario space, mapping regulatory, technical, and operational constraints to generate a representation of potential urban air mobility stakeholder-centric design objectives. The analysis of an optimized profit-maximizing eVTOL, cost-minimizing eVTOL, sustainability-maximizing eVTOL, and a combined FoM-maximizing eVTOL design highlights significant trade-offs in the area of profitability, operational flexibility, and sustainability strategies. This underlines the importance of incorporating multiple operationally tangential disciplines into the design process, while also reflecting the diverse priorities of stakeholders such as operators, regulators, and society.

Sanaz Sadat Hosseini, Babak Rahimi Ardabili, Mona Azarbayjani et al.

Urban design significantly impacts sustainability, particularly in the context of public transit efficiency and carbon emissions reduction. This study explores two neighborhoods with distinct urban designs: South End, Charlotte, NC, featuring a dynamic mixed-use urban design pattern, and Avondale, Chattanooga, TN, with a residential suburban grid layout. Using the TRANSIT-GYM tool, we assess the impact of increased bus utilization in these different urban settings on traffic and CO2 emissions. Our results highlight the critical role of urban design and planning in transit system efficiency. In South End, the mixed-use design led to more substantial emission reductions, indicating that urban layout can significantly influence public transit outcomes. Tailored strategies that consider the unique urban design elements are essential for climate resilience. Notably, doubling bus utilization decreased daily emissions by 10.18% in South End and 8.13% in Avondale, with a corresponding reduction in overall traffic. A target of 50% bus utilization saw emissions drop by 21.45% in South End and 14.50% in Avondale. At an idealistic goal of 70% bus utilization, South End and Avondale witnessed emission reductions of 37.22% and 27.80%, respectively. These insights are crucial for urban designers and policymakers in developing sustainable urban landscapes.

Steven Stalder, Michele Volpi, Nicolas Büttner et al.

Cities around the world face a critical shortage of affordable and decent housing. Despite its critical importance for policy, our ability to effectively monitor and track progress in urban housing is limited. Deep learning-based computer vision methods applied to street-level images have been successful in the measurement of socioeconomic and environmental inequalities but did not fully utilize temporal images to track urban change as time-varying labels are often unavailable. We used self-supervised methods to measure change in London using 15 million street images taken between 2008 and 2021. Our novel adaptation of Barlow Twins, Street2Vec, embeds urban structure while being invariant to seasonal and daily changes without manual annotations. It outperformed generic embeddings, successfully identified point-level change in London's housing supply from street-level images, and distinguished between major and minor change. This capability can provide timely information for urban planning and policy decisions toward more liveable, equitable, and sustainable cities.

Irma Dwiyanti, Muhammad Rijal, Wahyu Hidayat

Kampar Regency is one of the regencies with a quit spacious aquaculture area with pisciculture business activities as one of the livelihoods of most of the people. Freshwater fish farming in Kampar Regency includes the pisciculture of karamba or in ponds. The request for freshwater fish production in Riau province is also quite high, such as catfish, carp, tilapia, pomfret and baung fish for daily consumption or industrial needs. The high request for fish production in Kampar regency cannot always be fulfielld. This is due to the failure of aquaculture caused by various factors such as climate, environment, pests and diseases. So to avoid the occurrence of these failures required skilled human resources and adequate facilities. Research and Development Center for Aquaculture which functions as a center for development, research and public education in advancing the community's economy, which includes a research center, laboratory and also commercial functions in the fisheries sector. In designing the Center for Aquaculture Research and Development, the Biophilic architectural approach is used. Biophilic architecture is a good relationship between nature, humans and architecture. The concept of the building takes the concept of "River Water Flow" as an implementation of natural formations by considering the three aspects ofarchitecture Biophilic into a single unit.

Haruki Oshio, Tomoki Kiyono, Takashi Asawa

The design of urban areas and building that utilizes the microclimatic effects of trees is a promising approach for reducing the severe heat stress caused by urban heat islands and global warming. Although trees can reduce heat stress through solar shading during the daytime, their influence on the air temperature under and around them during the nighttime, which is important for nighttime thermal comfort, has not yet been fully elucidated. In this study, we investigated the nocturnal cooling effect of trees in a physical urban space by the coupled numerical simulation of longwave radiative transfer and computational fluid dynamics. To represent the spatial structure of an actual urban space, airborne LiDAR-derived three-dimensional data of leaf area density distribution and building shape were used. The species-specific convective heat transfer coefficient was also considered. An analysis of the calculated sensible heat flux shows that both leaf area density and sky view factor are important factors in the production of cool air. According to the calculated distributions of air temperature and velocity, even under the condition of a certain degree of incident flow, the cooled air can flow down to the space under the crown, accumulate, and then diverge when the wind speed is sufficiently low in the crown owing to the crown drag. Buildings contribute to both the accumulation and dissipation of cool air. The findings of the present study suggest that cool spots can be produced during nighttime by trees planted near streets by devising a suitable arrangement and morphology of trees and buildings.

Nikhaphone Mackhaphonh, Guangshe Jia, Qixiong Xu

Major public projects in Laos are faced with multiple challenges, including project identification and its decision-making. Generally, an identification is an important key identifying the potential needs and requirements for achieving the development goal. However, the process was developed without a formal framework and assurance tools that have been criticized for negative social and environmental consequences as “white elephant projects” over the past few years. Considering this context, the study aimed to develop a conceptual framework to navigate an alternative solution for the right project. Based on contextual analysis and systematic literature review, the proposed framework provided the process of concept development and its assurance that it could be systematically developed in a cause-effect chain of needs. The findings indicate areas that reflect new insights of both strategic performance and a governance system, and reforms the decision-making process in providing new knowledge, new rules, and procedures for effective governance.

Christopher J. Urban, Daniel J. Bauer

We investigate novel parameter estimation and goodness-of-fit (GOF) assessment methods for large-scale confirmatory item factor analysis (IFA) with many respondents, items, and latent factors. For parameter estimation, we extend Urban and Bauer's (2021) deep learning algorithm for exploratory IFA to the confirmatory setting by showing how to handle constraints on loadings and factor correlations. For GOF assessment, we explore simulation-based tests and indices that extend the classifier two-sample test (C2ST), a method that tests whether a deep neural network can distinguish between observed data and synthetic data sampled from a fitted IFA model. Proposed extensions include a test of approximate fit wherein the user specifies what percentage of observed and synthetic data should be distinguishable as well as a relative fit index (RFI) that is similar in spirit to the RFIs used in structural equation modeling. Via simulation studies, we show that: (1) the confirmatory extension of Urban and Bauer's (2021) algorithm obtains comparable estimates to a state-of-the-art estimation procedure in less time; (2) C2ST-based GOF tests control the empirical type I error rate and detect when the latent dimensionality is misspecified; and (3) the sampling distribution of the C2ST-based RFI depends on the sample size.

E. Brigatti, V. M. Netto, F. N. M. de Sousa Filho et al.

In this work, we develop a general method for estimating the Shannon entropy of a bidimensional sequence based on the extrapolation of block entropies. We apply this method to analyse the spatial configurations of cities of different cultures and regions of the world. Findings suggest that this approach can identify similarities between cities, generating accurate results for recognising and classifying different urban morphologies. The hierarchical clustering analysis based on this metric also opens up new questions about the possibility that urban form can embody characteristics related to different cultural identities, historical processes and geographical regions.

Bin Jiang, Ju-Tzu Huang

Sustainable urban design or planning is not a LEGO-like assembly of prefabricated elements, but an embryo-like growth with persistent differentiation and adaptation towards a coherent whole. The coherent whole has a striking character - called living structure - that consists of far more small substructures than large ones. To detect the living structure, natural streets or axial lines have been previously adopted to be topologically represent an urban environment as a coherent whole. This paper develops a new approach to detecting the underlying living structure of urban environments. The approach takes an urban environment as a whole and recursively decomposes it into meaningful subwholes at different levels of hierarchy or scale ranging from the largest to the smallest. We compared the new approach to natural street and axial line approaches and demonstrated, through four case studies, that the new approach is better and more powerful. Based on the study, we further discuss how the new approach can be used not only for understanding, but also for effectively designing or planning the living structure of an urban environment to be more living or more livable. Keywords: Urban design or planning, structural beauty, space syntax, natural streets, life, wholeness

A. P. Neto-Bradley, R. Choudhary, P. Challenor

Access to sustained clean cooking in India is essential to addressing the health burden of indoor air pollution from biomass fuels, but spatial inequality in cities can adversely affect uptake and effectiveness of policies amongst low-income households. Limited data exists on the spatial distribution of energy use in Indian cities, particularly amongst low-income households, and most quantitative studies focus primarily on the effect of economic determinants. A microsimulation approach is proposed, using publicly available data and a Bayesian multi-level model to account for effects of current cooking practices, local socio-cultural context, and spatial effects. This approach offers previously unavailable insight into the spatial distribution of fuel use and residential energy transition within Indian cities. Uncertainty in the modelled effects is propagated through to fuel use estimates. The model is applied to four cities in the south Indian states of Kerala and Tamil Nadu, and comparison against ward-level survey data shows consistency with the model estimates. Ward-level effects exemplify how wards compare to the city average and to other urban area in the state, which can help stakeholders design and implement clean cooking interventions tailored to the needs of households.

Philipp R. W. Urech

Pragmatic planning juxtaposed with conflicting agendas has led to metropolitan territories with little quality for urban life. Rapidly growing urban agglomeration, synchronous with the Great Acceleration of the global society, is causing massive landscape change leading to radical breaks with traditional landscapes. By drawing from the formal properties of the environment that include existing qualities, it is possible to develop solutions that respond to both a broader and more specific context. The method resorts to laser scanning technology to produce three-dimensional point cloud models and use them as a prospective medium to perform informed transformations in the landscape. Laser-scanned 3D models can help take advantage of subtle topographic differences to support water management, capture significant site features, and provide an accurate site inventory that could reduce the cost of displaced terrain and replanted trees. The article discusses how point cloud models can support the site investigation as part of a digital design method in the field of landscape design. The approach engages formal characteristics of a physical landscape and results in a transformative workflow linked to the survey and the analysis of the site. By using modes of visualization and coloring to emphasize shapes, densities, and heights, the model can reveal relevant landscape features and patterns that are otherwise not noticeable. Section 1 introduces the methods used in other disciplines; Section 2 provides explanations about how the methods apply to a case study in landscape design; Section 3 presents the possibilities offered by the approach to integrate formal characteristics of the environment during the design process. Design development based on documented features in the point cloud model increases the control to shape environments that contribute to the process of accumulation occurring in the landscape.