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

Elijah Anderson

M. Sheller, J. Urry

Christine C. Rega‐Brodsky, Myla F. J. Aronson, M. Piana et al.

Carolina V. Zuccotti

Abstract Research on the socioeconomic outcomes of migrants and their children in destination societies has long been a central focus for sociologists and economists worldwide. However, this body of work is shaped by two dominant approaches. First, most studies focus on South-North migration; second, they often compare migrants with natives in destination countries. Building on the growing multi-sited and dissimilation approaches, this study uses large-scale harmonized census microdata to enhance our understanding of migration outcomes by comparing migrants across both southern and northern destinations, as well as comparing migrants to natives in their countries of origin. The study examines the labour market outcomes of two South American migrant groups—Bolivian and Peruvian—who have emigrated to two key destinations: Argentina and Spain. Three key takeaways emerge. First, migration can reshape women’s relationship to the labour market. Second, not all migration results in an occupational status downgrade, contrary to expectations from classic assimilation theories. Third, although South–North moves may involve greater legal and cultural challenges, they do not necessarily entail greater labour market disadvantages or lower returns to education compared to South–South moves.

Alfina Modiash, Nany Yuliastuti

Program kampung tematik merupakan inovasi pemerintah yang menonjolkan potensi lokal kampung bertujuan mengangkat kearifan lokal, meningkatkan kesejahteraan masyarakat dan kualitas lingkungan permukiman.  Kampung Blangkon Potrojayan merupakan salah satu kampung tematik yang berpotensi dalam peningkatan kesejahteraan masyarakat serta mendukung kearifan lokal menjadi sebuah ikonik di Kota Surakarta berupa produk budaya jawa yaitu blangkon. Namun, masih terdapat permasalahan terkait dukungan infrastruktur kawasan maupun kualitas pengelolaan kampungnya. Salah satunya berupa kegiatan promosi yang masih bersifat konvensional serta jaringan jalan yang dipergunakan sebagai tempat menjemur blangkon. Penelitian ini bertujuan untuk mengetahui tindakan pengembangan kampung tematik yang berkelanjutan di Kampung Blangkon Potrojayan. Dengan menggunakan metode kuantitatif berupa analisis skoring untuk mengetahui kondisi eksisting dan tingkat keberlanjutan kampung serta metode Importance Performance Analysis (IPA) untuk mengetahui tingkatan prioritas tindakan yang dapat menjadi usulan perbaikan. Hasil penelitian didapatkan Kampung Blangkon Potrojayan berada pada tingkat cukup berkelanjutan dengan skor 2,21 dimana terdapat 4 atribut yang menjadi prioritas utama dilakukan pengembangan yaitu kondisi jaringan jalan, jenis media promosi, pekerja yang kompeten, keikutsertaan kegiatan pameran. Prioritas pertama tindakan yang perlu dilakukan dalam mengembangkan Kampung Blangkon Potrojayan berupa perlu ditetapkannya lahan khusus penjemuran blangkon komunal yang terdapat di kawasan rencana kampung wisata dalam rangka meningkatkan kenyamanan pergerakan wisatawan dan warga lokal.

Shengao Yi, Xiaojiang Li, Wei Tu et al.

As extreme heat events intensify due to climate change and urbanization, cities face increasing challenges in mitigating outdoor heat stress. While traditional physical models such as SOLWEIG and ENVI-met provide detailed assessments of human-perceived heat exposure, their computational demands limit scalability for city-wide planning. In this study, we propose GSM-UTCI, a multimodal deep learning framework designed to predict daytime average Universal Thermal Climate Index (UTCI) at 1-meter hyperlocal resolution. The model fuses surface morphology (nDSM), high-resolution land cover data, and hourly meteorological conditions using a feature-wise linear modulation (FiLM) architecture that dynamically conditions spatial features on atmospheric context. Trained on SOLWEIG-derived UTCI maps, GSM-UTCI achieves near-physical accuracy, with an R2 of 0.9151 and a mean absolute error (MAE) of 0.41°C, while reducing inference time from hours to under five minutes for an entire city. To demonstrate its planning relevance, we apply GSM-UTCI to simulate systematic landscape transformation scenarios in Philadelphia, replacing bare earth, grass, and impervious surfaces with tree canopy. Results show spatially heterogeneous but consistently strong cooling effects, with impervious-to-tree conversion producing the highest aggregated benefit (-4.18°C average change in UTCI across 270.7 km2). Tract-level bivariate analysis further reveals strong alignment between thermal reduction potential and land cover proportions. These findings underscore the utility of GSM-UTCI as a scalable, fine-grained decision support tool for urban climate adaptation, enabling scenario-based evaluation of greening strategies across diverse urban environments.

Gustavo H. Santos, Myriam Delgado, Thiago H. Silva

Location-Based Social Networks (LBSNs) provide a rich foundation for modeling urban behavior through iNETs (Interest Networks), which capture how user interests are distributed throughout urban spaces. This study compares iNETs across platforms (Google Places and Foursquare) and spatial granularities, showing that coarser levels reveal more consistent cross-platform patterns, while finer granularities expose subtle, platform-specific behaviors. Our analysis finds that, in general, user interest is primarily shaped by geographic proximity and venue similarity, while socioeconomic and political contexts play a lesser role. Building on these insights, we develop a multi-level, explainable recommendation system that predicts high-interest urban regions for different user types. The model adapts to behavior profiles -- such as explorers, who are driven by proximity, and returners, who prefer familiar venues -- and provides natural-language explanations using explainable AI (XAI) techniques. To support our approach, we introduce h3-cities, a tool for multi-scale spatial analysis, and release a public demo for interactively exploring personalized urban recommendations. Our findings contribute to urban mobility research by providing scalable, context-aware, and interpretable recommendation systems.

Ricardo de S Alencar, Fabiano L. Ribeiro, Horacio Samaniego et al.

\abstract{Urban scaling theories posit that larger cities exhibit disproportionately higher levels of socioeconomic activity and human interactions. Yet, evidence from developing contexts (especially those marked by stark socioeconomic disparities) remains limited. To address this gap, we analyse a month-long dataset of 3.1~billion voice-call records from Brazil's 100 most populous cities, providing a continental-scale test of urban scaling laws. We measure interactions using two complementary proxies: the number of phone-based contacts (voice-call degrees) and the number of trips inferred from consecutive calls in distinct locations. Our findings reveal clear superlinear relationships in both metrics, indicating that larger urban centres exhibit intensified remote communication and physical mobility. We further observe that gross domestic product (GDP) also scales superlinearly with population, consistent with broader claims that economic output grows faster than city size. Conversely, the number of antennas required per user scales sublinearly, suggesting economies of scale in telecommunications infrastructure. Although the dataset covers a single provider, its widespread coverage in major cities supports the robustness of the results. We nonetheless discuss potential biases, including city-specific marketing campaigns and predominantly prepaid users, as well as the open question of whether higher interaction drives wealth or vice versa. Overall, this study enriches our understanding of urban scaling, emphasising how communication and mobility jointly shape the socioeconomic landscapes of rapidly growing cities.

Haozhe Xie, Zhaoxi Chen, Fangzhou Hong et al.

3D scene generation has garnered growing attention in recent years and has made significant progress. Generating 4D cities is more challenging than 3D scenes due to the presence of structurally complex, visually diverse objects like buildings and vehicles, and heightened human sensitivity to distortions in urban environments. To tackle these issues, we propose CityDreamer4D, a compositional generative model specifically tailored for generating unbounded 4D cities. Our main insights are 1) 4D city generation should separate dynamic objects (e.g., vehicles) from static scenes (e.g., buildings and roads), and 2) all objects in the 4D scene should be composed of different types of neural fields for buildings, vehicles, and background stuff. Specifically, we propose Traffic Scenario Generator and Unbounded Layout Generator to produce dynamic traffic scenarios and static city layouts using a highly compact BEV representation. Objects in 4D cities are generated by combining stuff-oriented and instance-oriented neural fields for background stuff, buildings, and vehicles. To suit the distinct characteristics of background stuff and instances, the neural fields employ customized generative hash grids and periodic positional embeddings as scene parameterizations. Furthermore, we offer a comprehensive suite of datasets for city generation, including OSM, GoogleEarth, and CityTopia. The OSM dataset provides a variety of real-world city layouts, while the Google Earth and CityTopia datasets deliver large-scale, high-quality city imagery complete with 3D instance annotations. Leveraging its compositional design, CityDreamer4D supports a range of downstream applications, such as instance editing, city stylization, and urban simulation, while delivering state-of-the-art performance in generating realistic 4D cities.

Bin Jiang, Qianxiang Yao, Huan Qian et al.

This chapter investigates the concept of living structure - which is defined as a structural hierarchy that has a recurring pattern of an abundance of small substructures compared to larger ones - and the application of such structures in creating livable cities within urban informatics. By integrating practical, scientific, and artistic innovations, living structures provide a theoretical framework for designing healing environments and understanding urban complexity. We conceptualize spaces through hierarchical transformations, calculating livingness (L) as L = S * H, where S is the number of substructures and H is the inherent hierarchy of those substructures. Living structure is governed by the scaling law and Tobler's law, and guided by differentiation and adaptation principles, and it fosters vibrant and engaging spaces that enhance human well-being and a sense of place. Urban informatics, urban planning, and architecture must evolve beyond just understanding and prediction to include purposeful design. This new kind of science integrates the theory of living structure and emphasizes creation and design, thus transforming those disciplines. This chapter looks at environments that have high structural beauty, as defined by the 15 properties that Christopher Alexander proposed, and discusses the application of those properties in architecture, urban informatics, and emerging technologies such as artificial intelligence, with the aim of making built environments more vibrant and conducive to human well-being. Keywords: Livable cities, structural beauty, differentiation, adaptation, architectural design, urban complexity

Francisco Estrada, Veronica Lupi, Wouter Botzen et al.

The social cost of carbon (SCC) serves as a concise gauge of climate change's economic impact, often reported at the global and country level. SCC values are disproportionately high for less-developed, populous countries. Assessing the contributions of urban and non-urban areas to the SCC can provide additional insights for climate policy. Cities are essential for defining global emissions, influencing warming levels and associated damages. High exposure and concurrent socioenvironmental problems exacerbate climate change risks in cities. Using a spatially explicit integrated assessment model, the SCC is estimated at USD$137-USD$579/tCO2, rising to USD$262-USD$1,075/tCO2 when including urban heat island (UHI) warming. Urban SCC dominates, with both urban exposure and the UHI contributing significantly. A permanent 1% reduction of the UHI in urban areas yields net present benefits of USD$484-USD$1,562 per urban dweller. Global cities have significant leverage and incentives for a swift transition to a low-carbon economy, and for reducing local warming.

Z.KH. Sergeeva

One of the key processes determining the development of the modern Kazan agglomeration is the attraction of internal and external migrants. As a center of attraction for student youth, Kazan occupies the fourth position among the major educational centers of Russia. In the article the author presents the results and conclusions of an applied sociological research conducted with students of one of the leading universities of Kazan by the method of focus-group interview in April 2024. The analysis of focus group materials showed that the following aspects of the city's attractiveness (unattractiveness) important for students were named: convenience and accessibility of transport infrastructure; cultural atmosphere, diversity and opportunities of cultural life, development of cultural, leisure and sports infrastructure; development of housing and communal services; the quality of the city's infrastructure. Based on the results of the study, the author argues that in order to develop the city and increase its attractiveness in the eyes of visitors, especially young people. It is necessary to implement innovative infrastructure projects, develop smart city technologies that integrate the Internet of Things, big data and artificial intelligence. Innovative technologies not only improve the quality of life of citizens, but also open up new opportunities for involving citizens, especially young people, in city management and solving public problems. Citizen participation in the life of the city is an important element of a democratic society, contributing to the improvement of the quality of the urban environment and the well-being of residents.

G. Mirzakulova

The growing number of problems experienced by the elderly living in the cities of Kazakhstan, who experience social isolation, are causing a new perspective on the problem. The purpose of the research is to examine the impact of social and spatial isolation on daily activities and the loneliness perception of elderly people living in Kazakhstan cities. 78 senior citizens participated in this study from these three locations; they filled out questionnaires which were then used to collect data regarding their loneliness levels as well as how often they feel cut off from others around them due to where they reside. The responses were analyzed statistically through SPSS software version 27 for Windows which employed both descriptive statistics techniques alongside the correlation analysis method to reveal any possible relationships existing among different variables considered by researchers during the investigation process. It is suggested that in Kazakhstan cities, research is needed to develop comprehensive programs that take into account social status and resource accessibility as well as the necessity for social contacts and support of family ties. Study results can be used to work out effective strategies aimed at preventing and overcoming social isolation among old people living in towns of Kazakhstan thus improving their life quality and creating a friendlier environment for citizens of all age groups. The findings of the research emphasize the importance of purposeful assistance to elderly persons for their social integration to improve their quality of life and makethe urban environment more friendly to all groups of the population.

Magdalena Biernacka, Jakub Kronenberg

Abstract The main goal of this article is to identify and classify institutional barriers which prevent the use of urban green spaces (UGS) at three levels: availability (whether a UGS exists), accessibility (whether it is physically and psychologically accessible, e.g., not fenced off), and attractiveness (whether it is attractive enough for potential users to visit). We reviewed the impacts on UGS provision exerted by different actors (individuals, formal and informal groups, community councils, city authorities, national governmental and non-governmental organizations), along with the relevant institutional foundations of those impacts. As a result, we identified and classified the different barriers for which these actors are responsible in the case of fifteen UGS types in our case study city, Lodz (Łodź) in Poland. The main barriers at different levels concern conflicting interests, physical barriers (private green spaces), and the lack of funds, together with legal and governmental failures (public green spaces). These barriers result from the different actors’ mandates or lack thereof. Our analysis has implications for the operationalization of UGS availability, accessibility and attractiveness, and, in particular, for mapping UGS and setting the relevant indicators and thresholds for UGS availability, accessibility and attractiveness.

P. Diwakar

Rachel M. Adams, Candace M. Evans, Lori Peek

The National Science Foundation-supported CONVERGE facility was established in 2018 as the first social science-led component of the Natural Hazards Engineering Research Infrastructure (NHERI). Headquartered at the Natural Hazards Center at the University of Colorado Boulder, CONVERGE identifies, trains, connects, and funds researchers across disciplines in the hazards and disaster field. This article provides an overview of one of our most widely used tools, the CONVERGE Training Modules. These free, interactive, online trainings are designed for students, early career professionals, and others who are new to hazards and disaster research and practice. Since July 2019, our team has released 10 modules that cover a range of foundational topics in hazards and disaster research, including Institutional Review Board procedures, conducting emotionally challenging research, cultural competence, collecting and sharing perishable data, social vulnerability, and disaster mental health. In addition, CONVERGE offers advanced trainings in specialized topics such as broader ethical considerations for hazards and disaster researchers, reciprocity, gender-based violence in fieldwork, and public health implications of hazards and disaster research. Between July 2019 and November 2022, 6,311 unique users registered for the modules, and these users logged 7,222 module completions. Of the module completions to date, the largest percentage of users completed only one (46.0%) of the available trainings, although a small group of “superusers”—whom we surveyed for this article—have completed all or almost all of the available modules. When asked why they planned to complete the modules at the time of registration, most users indicated that it was to fulfill a classroom or other educational requirement (51.2%), for personal interest/to learn more (9.0%), or to prepare for or to support research (7.1%) or practice-oriented activities (5.8%). In addition to providing more information regarding module users, this article details the development of the technology and discusses the impact and success of this tool for transferring knowledge and skills to the hazards and disaster research and practice community. We conclude with a discussion of future directions for this research-based educational intervention.

Loesje Verhoeven, Jo Ritzen

Are institutional trust and interpersonal trust threatened by globalisation? For nineteen countries in Europe, using a fixed effects model for a panel data set relating globalisation to several economic and social macro variables, like income inequality and diversity, to average institutional and interpersonal trust derived from responses in European Social Surveys, we do not find any significant relation between the relatively moderate globalisation of the first two decades of the 21st century on average interpersonal and institutional trust. At the same time, occurrences of economic decline in a country are negatively related to institutional trust. GDP has a positive effect on both institutional and interpersonal.Combining the macro factors with the individual traits of respondents using pooled repeated cross-sectional data demonstrate the dominance of personal characteristics in individual levels of trust, with only institutional quality emerging as a macro variable which is significantly and positively related to trust, especially for the Socio-Economic Groups 3 to 7 (of the eight groups distinguished). Those who are born in the country exhibit higher levels of interpersonal trust, in particular in the higher SES groups 4–7, but show significantly lower institutional trust for the SES groups 0–2. Age is negatively related to institutional trust for all SES groups, but positively related to interpersonal trust for SES groups 4–7.These findings appear to imply that those who are concerned with the level of institutional trust in the population as a basic requirement for democracy in Europe should focus on the quality of institutions and not on globalisation.

Roberta Cucca, Thomas Thaler

The Covid-19 pandemic and energy, climate, and demographic crises have shown how cities are vulnerable to these impacts and how the access to green and blue spaces has become highly relevant to people. One strategy that we can observe is the strong focus on the resilience discourse, meaning implementing more green and blue spaces in urban areas, such as at previous brownfield quarters. However, social justice implications of urban greening have been overlooked for a long time. The implementation of strategies to improve the quality and availability of the green and blue infrastructures may indeed have negative outcomes as far as housing accessibility is concerned by trigging gentrification processes. Issues related to environmental justice and socio-spatial justice are increasing in contemporary cities and call for a better understanding of the global and local mechanisms of production and reproduction of environmental and spatial inequalities. This thematic issue includes eleven articles with different methodologies, with examples from Europe and North America as well as different lenses of green gentrification. Some articles focus more on the question of costs, benefits, and distributional consequences of various infrastructural options for urban greening. Others, instead, discuss how the strategic urban planning tools and policy processes take into account distributional consequences, with specific attention on participatory processes.

Maosu Li, Fan Xue, Anthony G. O. Yeh

Urban-scale quantification of window views can inform housing selection and valuation, landscape management, and urban planning. However, window views are numerous in high-rise, high-density urban areas and current automatic assessments of window views are inaccurate and time-consuming. Thus, both accurate and efficient assessment of window views is significant in improving the automation for urban-scale window view applications. The paper presents an automatic, accurate, and efficient assessment of window view indices (WVIs) of greenery, sky, waterbody, and construction using 3D color City Information Models (CIMs). The workflow includes: i) 3D semantic segmentation of photorealistic CIM and Digital Surface Model (DSM), and ii) batch computation of WVIs. Experimental results showed the estimated WVIs were more accurate (RMSE < 0.01), and the proposed method was more efficient (3.68 times faster) than Li et al.'s (2022) 2D semantic segmentation. Thus, the proposed method can facilitate large-scale WVI assessment and update in healthy high-rise, high-density urban development.

Yansong Ning, Hao Liu, Hao Wang et al.

Accurate Urban SpatioTemporal Prediction (USTP) is of great importance to the development and operation of the smart city. As an emerging building block, multi-sourced urban data are usually integrated as urban knowledge graphs (UrbanKGs) to provide critical knowledge for urban spatiotemporal prediction models. However, existing UrbanKGs are often tailored for specific downstream prediction tasks and are not publicly available, which limits the potential advancement. This paper presents UUKG, the unified urban knowledge graph dataset for knowledge-enhanced urban spatiotemporal predictions. Specifically, we first construct UrbanKGs consisting of millions of triplets for two metropolises by connecting heterogeneous urban entities such as administrative boroughs, POIs, and road segments. Moreover, we conduct qualitative and quantitative analysis on constructed UrbanKGs and uncover diverse high-order structural patterns, such as hierarchies and cycles, that can be leveraged to benefit downstream USTP tasks. To validate and facilitate the use of UrbanKGs, we implement and evaluate 15 KG embedding methods on the KG completion task and integrate the learned KG embeddings into 9 spatiotemporal models for five different USTP tasks. The extensive experimental results not only provide benchmarks of knowledge-enhanced USTP models under different task settings but also highlight the potential of state-of-the-art high-order structure-aware UrbanKG embedding methods. We hope the proposed UUKG fosters research on urban knowledge graphs and broad smart city applications. The dataset and source code are available at https://github.com/usail-hkust/UUKG/.