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

Xingcheng Lu, Yixin Luo, Yiang Chen et al.

Carbon monoxide (CO) is a major atmospheric pollutant with adverse health effects on humans. Moreover, CO can indirectly prolong the lifetime of methane and contribute to global warming. Therefore, understanding the spatial distribution of CO emissions is crucial for designing much-needed strategies to control this pollutant. In this work, a hybrid Weather Research & Forecasting–stochastic time-inverted Lagrangian transport (WRF-STILT)–Bayesian inversion framework was constructed to correct CO emissions over the Greater Bay Area (GBA) for February 2019 and February 2020. After adjusting CO emissions, the average root mean squared error (RMSE), normalized mean error (NME), and correlation coefficient (R) for the simulated CO concentrations in February 2019 and 2020 changed from 0.31 ppm to 0.12 ppm (a 61% reduction), 0.35 to 0.13 (a 63% reduction), and 0.47 to 0.87 (an 85% increase), respectively. The updated CO emissions were then used as input for the Comprehensive Air Quality Model with Extensions (CAMx), a Eulerian model, to further validate the method. The results again indicated that the simulation performance was improved substantially, with a 58% increase in the average R value, a 62% reduction in the RMSE, and a 68% reduction in the NME. This validates the effectiveness of the proposed method in correcting CO emissions. According to the updated emission data, CO emissions over the GBA during the Spring Festival and the COVID-19 lockdown period were 8.3% and 19.6% lower than during normal periods, respectively. These results highlight the importance of accounting for such atypical events in emission estimation and air quality modeling. Analysis of the source areas contributing to CO concentrations in population centers of major GBA cities showed that the average contributions from local emissions and emissions from other GBA cities were 45.5% and 38.8%, respectively. The method developed in this work can be further used for CO adjustment in other regions and contribute to a deeper understanding of the characteristics of this important pollutant.

Kunihiko Fujiwara, Ryuta Tsurumi, Tomoki Kiyono et al.

Three-dimensional urban environment simulation is a powerful tool for informed urban planning. However, the intensive manual effort required to prepare input 3D city models has hindered its widespread adoption. To address this challenge, we present VoxCity, an open-source Python package that provides a one-stop solution for grid-based 3D city model generation and urban environment simulation for cities worldwide. VoxCity's `generator' subpackage automatically downloads building heights, tree canopy heights, land cover, and terrain elevation within a specified target area, and voxelizes buildings, trees, land cover, and terrain to generate an integrated voxel city model. The `simulator' subpackage enables users to conduct environmental simulations, including solar radiation and view index analyses. Users can export the generated models using several file formats compatible with external software, such as ENVI-met (INX), Blender, and Rhino (OBJ). We generated 3D city models for eight global cities, and demonstrated the calculation of solar irradiance, sky view index, and green view index. We also showcased microclimate simulation and 3D rendering visualization through ENVI-met and Rhino, respectively, through the file export function. Additionally, we reviewed openly available geospatial data to create guidelines to help users choose appropriate data sources depending on their target areas and purposes. VoxCity can significantly reduce the effort and time required for 3D city model preparation and promote the utilization of urban environment simulations. This contributes to more informed urban and architectural design that considers environmental impacts, and in turn, fosters sustainable and livable cities. VoxCity is released openly at https://github.com/kunifujiwara/VoxCity.

Chao Zhang, Yechen Li, Neha Arora et al.

Being widely adopted by the transportation and planning practitioners, the fundamental diagram (FD) is the primary tool used to relate the key macroscopic traffic variables of speed, flow, and density. We empirically analyze the relation between vehicular space-mean speeds and flows given different signal settings and postulate a parsimonious parametric function form of the traditional FD where its function parameters are explicitly modeled as a function of the signal plan factors. We validate the proposed formulation using data from signalized urban road segments in Salt Lake City, Utah, USA. The proposed formulation builds our understanding of how changes to signal settings impact the FDs, and more generally the congestion patterns, of signalized urban segments.

Chaikal Amrullah, Daniel Panangian, Ksenia Bittner

The growing demand for detailed building roof data has driven the development of automated extraction methods to overcome the inefficiencies of traditional approaches, particularly in handling complex variations in building geometries. Re:PolyWorld, which integrates point detection with graph neural networks, presents a promising solution for reconstructing high-detail building roof vector data. This study enhances Re:PolyWorld's performance on complex urban residential structures by incorporating attention-based backbones and additional area segmentation loss. Despite dataset limitations, our experiments demonstrated improvements in point position accuracy (1.33 pixels) and line distance accuracy (14.39 pixels), along with a notable increase in the reconstruction score to 91.99%. These findings highlight the potential of advanced neural network architectures in addressing the challenges of complex urban residential geometries.

Dmitrii Serebrennikov, D. Skougarevskiy

Fredua Agyemang

Sustainable Development Goal 11 (SDG 11) focuses on making cities and human settlements inclusive, safe, resilient, and sustainable. Although the goal primarily addresses urban development, its principles also extend to rural areas, but the extent to which South Africa’s legal and policy frameworks empower traditional authorities to contribute to the development of their communities, particularly towards achieving SDG11, remains insufficiently explored. This study investigates how South Africa’s national legislative frameworks on traditional leadership have been applied to support the advancement of SDG 11. It examines the legal provisions within the 1996 Constitution of the Republic of South Africa, and relevant legislation to determine whether these frameworks provide a strong legal basis for promoting SDG 11 through the empowerment of traditional leadership. This study employs a desktop research methodology involving a comprehensive review of relevant laws, policies, and case law. Secondary data were gathered from case studies, journal articles, books, case laws, and credible internet sources. The findings suggest that the traditional authority system is deeply embedded within the South African Constitution, as well as legislative and policy frameworks, and has been effectively leveraged to advance SDG 11. Key insights emphasise the constitutional and legal recognition of traditional authorities and highlight the enforcement of traditional leadership roles and functions through various legal cases, and SDG 11-aligned programmes in South Africa. The areas where the role and functions of traditional leadership intersect with SDG 11 and rural development include security and safety, community participation, land management and sustainable settlements, cultural heritage and community identity, disaster management, and environmental stewardship. The empowerment of traditional leadership in South Africa has significant implications for achieving SDG 11 and rural development. These implications include enhanced local governance and service delivery, increased accountability and transparency, balanced rural-urban linkages, promotion of environmental stewardship, and the fostering of inclusive development. It also strengthens rural resilience, preserves cultural heritage, promotes sustainable resource management, and improves community engagement. However, challenges related to power dynamics, equity, and the need for policy integration and cohesion must be addressed to ensure that traditional leadership empowerment contributes effectively to sustainable development in South Africa.

Chaeyeon Han, Pavan Seshadri, Yiwei Ding et al.

While various sensors have been deployed to monitor vehicular flows, sensing pedestrian movement is still nascent. Yet walking is a significant mode of travel in many cities, especially those in Europe, Africa, and Asia. Understanding pedestrian volumes and flows is essential for designing safer and more attractive pedestrian infrastructure and for controlling periodic overcrowding. This study discusses a new approach to scale up urban sensing of people with the help of novel audio-based technology. It assesses the benefits and limitations of microphone-based sensors as compared to other forms of pedestrian sensing. A large-scale dataset called ASPED is presented, which includes high-quality audio recordings along with video recordings used for labeling the pedestrian count data. The baseline analyses highlight the promise of using audio sensors for pedestrian tracking, although algorithmic and technological improvements to make the sensors practically usable continue. This study also demonstrates how the data can be leveraged to predict pedestrian trajectories. Finally, it discusses the use cases and scenarios where audio-based pedestrian sensing can support better urban and transportation planning.

Maxwell Schrader, Navish Kumar, Esben Sørig et al.

Light goods vehicles (LGV) used extensively in the last mile of delivery are one of the leading polluters in cities. Cargo-bike logistics and Light Electric Vehicles (LEVs) have been put forward as a high impact candidate for replacing LGVs. Studies have estimated over half of urban van deliveries being replaceable by cargo-bikes, due to their faster speeds, shorter parking times and more efficient routes across cities. However, the logistics sector suffers from a lack of publicly available data, particularly pertaining to cargo-bike deliveries, thus limiting the understanding of their potential benefits. Specifically, service time (which includes cruising for parking, and walking to destination) is a major, but often overlooked component of delivery time modelling. The aim of this study is to establish a framework for measuring the performance of delivery vehicles, with an initial focus on modelling service times of vans and cargo-bikes across diverse urban environments. We introduce two datasets that allow for in-depth analysis and modelling of service times of cargo bikes and use existing datasets to reason about differences in delivery performance across vehicle types. We introduce a modelling framework to predict the service times of deliveries based on urban context. We employ Uber's H3 index to divide cities into hexagonal cells and aggregate OpenStreetMap tags for each cell, providing a detailed assessment of urban context. Leveraging this spatial grid, we use GeoVex to represent micro-regions as points in a continuous vector space, which then serve as input for predicting vehicle service times. We show that geospatial embeddings can effectively capture urban contexts and facilitate generalizations to new contexts and cities. Our methodology addresses the challenge of limited comparative data available for different vehicle types within the same urban settings.

Vinicius M. Netto, Otavio Peres, Caio Cacholas

Entropy is arguably one of the most powerful concepts to understand the world, from the behavior of molecules to the expansion of the universe, from how life emerges to how hybrid complex systems like cities come into being and continue existing. Yet, despite its widespread application, it is also one of the most misunderstood concepts across the sciences. This chapter seeks to demystify entropy and its main interpretations, along with some of its explorations in the context of cities. It first establishes the foundations of the concept by describing its trajectory since its inception in thermodynamics and statistical mechanics in the 19th century, its different incarnations from Boltzmanns pioneering formulation and Shannons information theory to its absorption in biology and the social sciences, until it reaches a nascent urban science in the 1960s. The chapter then identifies some of the main domains in which entropy has been explored to understand cities as complex systems, from entropy-maximizing models of spatial interaction and applications as a measure of urban form, diversity, and complexity to a tool for understanding conditions of self-organization and urban sustainability.

Hang Ni, Yuzhi Wang, Hao Liu

Urban regeneration presents significant challenges within the context of urbanization, requiring adaptive approaches to tackle evolving needs. Leveraging advancements in large language models (LLMs), we propose Cyclical Urban Planning (CUP), a new paradigm that continuously generates, evaluates, and refines urban plans in a closed-loop. Specifically, our multi-agent LLM-based framework consists of three key components: (1) Planning, where LLM agents generate and refine urban plans based on contextual data; (2) Living, where agents simulate the behaviors and interactions of residents, modeling life in the urban environment; and (3) Judging, which involves evaluating plan effectiveness and providing iterative feedback for improvement. The cyclical process enables a dynamic and responsive planning approach. Experiments on the real-world dataset demonstrate the effectiveness of our framework as a continuous and adaptive planning process.

Sabira Serikzhanova

The purpose of this article is to identify and comparatively analyze the perception of internal migrants by representatives of the host urban society. In the study, a series of focus groups were conducted in three cities to collect data, namely, Astana, Almaty and Shymkent. Discussion questions focused on the following topics: the image of the city in the minds of residents; urban identity, sense of attachment and urban culture; attitudes towards internal migration and internal migrants; practices of interaction with internal migrants. The article presents some results of the research project IRN AP09058370 “Social integration of internal migrants into the local community of large cities: social networks, social capital and development of urban space”, funded by the Ministry of Education and Science of the Republic of Kazakhstan. The results of the study show that residents of the three cities understand the processes of internal migration, which they regard as a natural phenomenon. In the cities, there is a division into «us» and «them», distancing citizens from internal migrants. The findings can be further used to forecast and adopt certain measures in migration and urban policy.

Prischa Listiningrum, Muhammad Anis Zhafran Al Anwary, A. E. Widiarto et al.

Land is not only defined as an object of ownership by certain community groups, especially indigenous communities. Land has intrinsic value inherent in the way of life and culture, thus affecting the quality of life. This article examines the potential implications of the land acquisiton process in the prospected Nusantara Capital in regards to the fulfillment of the right to an adequate standard of living. It is reviewed by engaging multi-spatial justice within the context of city development and urban transformation with learning lessons from Brasilia and Jakarta. Utilizing a qualitative socio-legal approach, the research employs systematic and structural interpretation of various legal instruments. It incorporates the concept of multi-spatial justice as part of a critical legal geography and urban sociology theory to understand the potential of segregation and gentrification in the Nusantara Capital. The results highlight three key aspects. Firstly, the concept of multi-spatial justice underscores the need to consider diverse spatial entities and their equitable treatment. Secondly, analyzing the State Capital Law reveals both promising and concerning aspects of spatial justice. While it aims to balance development and inclusivity, inconsistencies within the law's provisions raise concerns about potential injustices. Lastly, the study anticipates future inequities between local and urban spatials due to unequal land compensation. These findings emphasize the importance of addressing procedural and substantive fairness in land acquisition, fostering inclusive urban development, and aligning legal instruments with principles of multi-spatial justice.

Alessandro Raffa

Inside a Mediterranean scenario of population asymmetries, this paper talks about and ongoing research that aims to highlight issues, identify a working method and tools able to support sustainable regenerative design strategies for abandoned historical small(er) towns and their landscapes, especially in inlands contexts. With these objectives, the research chooses Basilicata region, in the South of Italy, as emblematic for its structural marginality- morphological, infrastructural, social and economic -, bio-cultural diverse and diffused heritage and its seemingly unreversible depopulation process. Aging, low birth rates and high level of emigration has produced the abandonment of small(er) towns, of rural areas and, by the contrary, an increasing wilderness, changing the millennial settlement structure and impacting on socio-ecological resilience. Inside the theoretical framework of landscape/ecological urbanism and related design- oriented experimentations, the constellation of abandoned small(er) towns are interpreted as urban densities of a performative bio-cultural green infrastructure that could support, through design, the contemporary challenge of sustainable development, with a relational and glocal approach. Small(er) towns regeneration is view inside a more complex, interdisciplinary and holistic frame in which inter-scalarity, flux, dynamic and time variability are crucial. Performative bio-cultural green infrastructure, through the multiplication of public space, could support sustainable processes, in an ecological, economic and social sense. From an applicational point of view, the research intends to build a dynamic atlas for the regeneration of abandoned small(er) towns; the atlas is conceived both as a reading and a design tool able to support polyphonic and open process of sustainable regeneration.

Charlotte Liotta, Vincent Viguié, Quentin Lepetit

Using a unique dataset containing gridded data on population densities, rents, housing sizes, and transportation in 192 cities worldwide, we investigate the empirical relevance of the monocentric standard urban model (SUM). Overall, the SUM seems surprisingly capable of capturing the inner structure of cities, both in developed and developing countries. As expected, cities spread out when they are richer, more populated, and when transportation or farmland is cheaper. Respectively 100% and 87% of the cities exhibit the expected negative density and rent gradients: on average, a 1% decrease in income net of transportation costs leads to a 21% decrease in densities and a 3% decrease in rents per m2. We also investigate the heterogeneity between cities of different characteristics in terms of monocentricity, informality, and amenities.

Claudio Santos, Maryam Hosseini, João Rulff et al.

The growth of cities calls for regulations on how urban space is used and zoning resolutions define how and for what purpose each piece of land is going to be used. Tracking land use and zoning evolution can reveal a wealth of information about urban development. For that matter, cities have been releasing data sets describing the historical evolution of both the shape and the attributes of land units. The complex nature of zoning code and land-use data, however, makes the analysis of such data quite challenging and often time-consuming. We address these challenges by introducing Urban Chronicles, an open-source web-based visual analytics system that enables interactive exploration of changes in land use patterns. Using New York City's Primary Land Use Tax Lot Output (PLUTO) as an example, we show the capabilities of the system by exploring the data over several years at different scales. Urban Chronicles supports on-the-fly aggregation and filtering operations by using a tree-based data structure that leverages the hierarchical nature of the data set to index the shape and attributes of geographical regions that change over time. We demonstrate the utility of our system through a set of case studies that analyze the impact of Hurricane Sandy on land use attributes, as well as the effects of proposed rezoning plans in Downtown Brooklyn.

Wangyang Chen, Abraham Noah Wu, Filip Biljecki

There is a prevailing trend to study urban morphology quantitatively thanks to the growing accessibility to various forms of spatial big data, increasing computing power, and use cases benefiting from such information. The methods developed up to now measure urban morphology with numerical indices describing density, proportion, and mixture, but they do not directly represent morphological features from the human's visual and intuitive perspective. We take the first step to bridge the gap by proposing a deep learning-based technique to automatically classify road networks into four classes on a visual basis. The method is implemented by generating an image of the street network (Colored Road Hierarchy Diagram), which we introduce in this paper, and classifying it using a deep convolutional neural network (ResNet-34). The model achieves an overall classification accuracy of 0.875. Nine cities around the world are selected as the study areas with their road networks acquired from OpenStreetMap. Latent subgroups among the cities are uncovered through clustering on the percentage of each road network category. In the subsequent part of the paper, we focus on the usability of such classification: we apply our method in a case study of urban vitality prediction. An advanced tree-based regression model (LightGBM) is for the first time designated to establish the relationship between morphological indices and vitality indicators. The effect of road network classification is found to be small but positively associated with urban vitality. This work expands the toolkit of quantitative urban morphology study with new techniques, supporting further studies in the future.

Konstantinos Rematas, Andrew Liu, Pratul P. Srinivasan et al.

The goal of this work is to perform 3D reconstruction and novel view synthesis from data captured by scanning platforms commonly deployed for world mapping in urban outdoor environments (e.g., Street View). Given a sequence of posed RGB images and lidar sweeps acquired by cameras and scanners moving through an outdoor scene, we produce a model from which 3D surfaces can be extracted and novel RGB images can be synthesized. Our approach extends Neural Radiance Fields, which has been demonstrated to synthesize realistic novel images for small scenes in controlled settings, with new methods for leveraging asynchronously captured lidar data, for addressing exposure variation between captured images, and for leveraging predicted image segmentations to supervise densities on rays pointing at the sky. Each of these three extensions provides significant performance improvements in experiments on Street View data. Our system produces state-of-the-art 3D surface reconstructions and synthesizes higher quality novel views in comparison to both traditional methods (e.g.~COLMAP) and recent neural representations (e.g.~Mip-NeRF).

Polly Fong, C. Haslam, T. Cruwys et al.

Urban sociology highlights an important role that a city’s social infrastructure, or “third-places,” play in supporting healthy communities. Informed by social identity theorizing, this study explores when and why older adults engage with third-places and how a sense of wellbeing can be derived from their participation. Focus-group interviews were conducted with a sample of community-dwelling older adults (N = 31) to examine the nature of one such third-place, a suburban neighborhood bridge club. Thematic analysis suggests that (a) the socio-spatial context of third-places can both enable and restrict participation, (b) third-places can support positive social identities (as bridge players, club members, locals), (c) enacting these identities in third-places facilitates a sense of wellbeing, and (d) third-places are potential connectors to the wider community. We discuss the policy implications for the development of age-friendly cities and the role of social identity processes in engaging with community groups in third-places.

Willow Lung-Amam

It is now well established that the concentric zone model, developed by Ernest Burgess and elaborated by others in the Chicago School of Sociology to explain the distribution of social groups in metropolitan areas, was wrong. In the past several decades, immigrants have not only moved out of the centers of U.S. metropolitan areas, many have bypassed central cities altogether and settled directly in suburbs. Increasingly, they have done so in nontraditional gateway cities, such as those in the American South and Rustbelt, and in smaller metropolitan or nonmetropolitan areas (Singer et al. 2008). Suburban settlement has also not clearly been associated with immigrants’ “move up” or integration into the so-called Americanmainstream, as Chicago school authors argued. In many rapidly growing metropolitan areas, rising housing prices have pushed many immigrants out of their historic urban neighborhoods. While post-World War II visions of the American Dream may still pull immigrants to suburbia, the communities into which many have settled hardly reflect that dream.While Asian immigrants have high rates of settlement in middle-class, affluent, and white suburban neighborhoods, other immigrants more commonly settle into suburbs with relatively high rates of foreclosure, poverty, segregation, and other measures of disadvantage (Farrell 2016; Logan 2014). These are not the touted “opportunity neighborhoods” that provide pathways to economic mobility. In fact, compared to central city ethnic enclaves, many provide less of the social, cultural and institutional supports that have traditionally promoted the economic advancement of immigrants and their children. Chicago School scholars also failed to account for the politics within suburbs that challenge not only immigrants’ ability to settle within particular communities, but also to achieve their own purposes and pursuits within them. My research on immigrants in suburbia has sought to fill some of these gaps. It has investigated the struggles of educated, professional Asian immigrants to establish a place for themselves within largely white, middle-class suburbs in Silicon Valley. In the Washington, DC suburbs, I have examined how lower-income, primarily Latino and African immigrants have fought to maintain a presence within redeveloping neighborhoods with rising gentrification and displacement pressures.

Nils Fearnley, Espen Johnsson, Siri Hegna Berge

Shared e-scooters may complement public transport by offering a solution to the first/last mile problem by easing, or increasing the radius of, access and egress trips. We have gathered real time e-scooter supply and demand data and performed a web survey of e-scooter users in Oslo, Norway. We find that e-scooters stand out as a popular first/last mile mode to many public transport passengers. E-scooters can play an even stronger such role if the two modes are integrated further.