Hasil untuk "Cities. Urban geography"

J. Holston, A. Appadurai

Wenjing Gong, Udbhav Srivastava, Yuchen Wang et al.

Conventional urban indicators derived from censuses, surveys, and administrative records are often costly, spatially inconsistent, and slow to update. Recent geospatial foundation models enable Earth embeddings, compact satellite image representations transferable across downstream tasks, but their utility for neighborhood-scale urban monitoring remains unclear. Here, we benchmark three Earth embedding families, AlphaEarth, Prithvi, and Clay, for urban signal prediction across six U.S. metropolitan areas from 2020 to 2023. Using a unified supervised-learning framework, we predict 14 neighborhood-level indicators spanning crime, income, health, and travel behavior, and evaluate performance under four settings: global, city-wise, year-wise, and city-year. Results show that Earth embeddings capture substantial urban variation, with the highest predictive skill for outcomes more directly tied to built-environment structure, including chronic health burdens and dominant commuting modes. By contrast, indicators shaped more strongly by fine-scale behavior and local policy, such as cycling, remain difficult to infer. Predictive performance varies markedly across cities but remains comparatively stable across years, indicating strong spatial heterogeneity alongside temporal robustness. Exploratory analysis suggests that cross-city variation in predictive performance is associated with urban form in task-specific ways. Controlled dimensionality experiments show that representation efficiency is critical: compact 64-dimensional AlphaEarth embeddings remain more informative than 64-dimensional reductions of Prithvi and Clay. This study establishes a benchmark for evaluating Earth embeddings in urban remote sensing and demonstrates their potential as scalable, low-cost features for SDG-aligned neighborhood-scale urban monitoring.

Rita Dionisio, Tyler McNabb, Edward Challies et al.

Ivan Chofyan, Ina Helena Agustina, Riswandha Risang Aji et al.

Abstract. Food security begins with a world view regarding concerns about food shortages. This indication is also supported by the symptoms of global climate change. The Indonesian government through the 1945 Constitution and the 1996 Rome Declaration stipulates that one of the human rights is the fulfillment of food needs. West Java is part of the Indonesian government and has harmonized regulations for the fulfillment of food. The perspective of food security originating from the world view of science shows the need for support from different paradigms. West Java has a long-rooted cultural heritage of food security. The substantive World View of Food Security Science requires a traditionalism paradigm as a network support towards food security integration. The purpose of the study is to describe the substitution of the traditionalism paradigm for food security. The approach method is carried out through a discourse approach. Data collection through literature studies while analysis is carried out through discourse analysis through text and context of how the traditionalism paradigm builds, articulates and frames food security. The analysis stages identified three interrelated discourses, namely (1) West Java Food Security as part of the scientific world view (2) Traditionalist paradigm showing human manners towards food (3) West Java Food Security within the framework of the traditionalist paradigm.

Negin Nazarian, Andy J Pitman, Mathew J Lipson et al.

Cities are experiencing significant warming and more frequent climate extremes, raising risks for over 90% of Australians living in cities. Yet many of our tools for climate prediction and projection lack accurate representations of these environments. We also lack the observations and datasets needed to evaluate model performance. This paper identifies critical gaps in Australias current capability, showing how they undermine climate impact and risk assessments in cities and may lead to poorly designed adaptation and mitigation strategies. These gaps, and the recommendations to address them, were identified through consultation with experts across research institutes, universities, two ARC Centres of Excellence, federal and state governments, and private agencies. Our recommendations span four key areas: city descriptive datasets, integrated observations, fit for purpose models, and a coordinated community of research and practice. Urgent action is needed to tailor models to Australia's unique urban landscapes and climates. This requires comprehensive, nationally consistent, high resolution datasets that capture the form, fabric, and function of contemporary and future cities. It also requires filling systematic gaps in integrated networks of urban climate observations for evaluation and benchmarking. At the same time, scientific understanding of key urban processes that influence weather and climate must advance, alongside improvements in their representation in physical models. This can be achieved through a national community of research and practice that codesigns and oversees an implementation plan, integrated with infrastructure such as ACCESS NRI and AURIN. Building this capability will enable us to answer critical questions about the interaction between cities and climate, protecting Australias urban populations and ensuring a resilient future.

Yansong Jin, Fei Wang, Quanli Zong et al.

Carla Guillermina García

Con motivo del 75 aniversario de la revista Anales del IAA y en el marco de la mesa homenaje celebrada en septiembre de 2023, este artículo propone algunas reflexiones sobre el desarrollo de esta publicación y su centralidad en la propuesta institucional de Mario Buschiazzo entre 1948 y 1971. Como objetivo general, el texto piensa el proyecto editorial dentro del esquema canónico de las disciplinas humanísticas en la Universidad de Buenos Aires, así como su valorización por parte de la historia de la historiografía. También se enfatiza su capa­cidad de promover aportes decisivos en el área de los estudios americanistas y de constituir un espacio de referencia para comprender el desarrollo de biografías profesionales desde la segunda mitad del siglo XX.

Carolina Gonzalez Redondo

Esta investigación indaga sobre la participación de los desarrolladores inmobiliarios en los procesos de renovación urbana, para ello aborda el caso de la creación del Barrio Parque Donado Holmberg, impulsado por el gobierno local en Villa Urquiza, Buenos Aires, que implicó la expulsión de habitantes vulnerables y la generación de una zona de oportunidad para los actores inmobiliarios. Mediante un abordaje cualitativo se analizan las estrategias de los desarrolladores inmobiliarios; se estudian sus formas de ingreso al proyecto, sus modalidades de gestión del suelo, sus estrategias de diseño y comercialización, así como su articulación con el gobierno local.

Sergei Basik

The current vertical/volumetric turn affected various academic fields, including urban scholarship. This short note broadens the critical literature by applying this emerging perspective on urban toponymic systems in the context of urban governance. Synthesizing the critical toponymic approaches with the notions of volume and verticality of urban space, this paper advanced critical urban governance scholarship, introducing a concept of toponymic verticality. The short note reveals the spatial vertical stratification of the urban toponymic system, its place-making potential, and political-economic functionality. These initial findings can contribute to future research in practical aspects of the politics of “good” urban governance and potentially rethinking the traditional two-dimensional spatiality toward understanding the complexity of the spatial relations in urban landscapes through the verticality of urban place names.

Mohamed R. Ibrahim, Terry Lyons

Air pollution in cities, especially NO\textsubscript{2}, is linked to numerous health problems, ranging from mortality to mental health challenges and attention deficits in children. While cities globally have initiated policies to curtail emissions, real-time monitoring remains challenging due to limited environmental sensors and their inconsistent distribution. This gap hinders the creation of adaptive urban policies that respond to the sequence of events and daily activities affecting pollution in cities. Here, we demonstrate how city CCTV cameras can act as a pseudo-NO\textsubscript{2} sensors. Using a predictive graph deep model, we utilised traffic flow from London's cameras in addition to environmental and spatial factors, generating NO\textsubscript{2} predictions from over 133 million frames. Our analysis of London's mobility patterns unveiled critical spatiotemporal connections, showing how specific traffic patterns affect NO\textsubscript{2} levels, sometimes with temporal lags of up to 6 hours. For instance, if trucks only drive at night, their effects on NO\textsubscript{2} levels are most likely to be seen in the morning when people commute. These findings cast doubt on the efficacy of some of the urban policies currently being implemented to reduce pollution. By leveraging existing camera infrastructure and our introduced methods, city planners and policymakers could cost-effectively monitor and mitigate the impact of NO\textsubscript{2} and other pollutants.

Gergő Pintér

Researchers face the trade-off between publishing mobility data along with their papers while simultaneously protecting the privacy of the individuals. In addition to the fundamental anonymization process, other techniques, such as spatial discretization and, in certain cases, location concealing or complete removal, are applied to achieve these dual objectives. The primary research question is whether concealing the observation area is an adequate form of protection or whether human mobility patterns in urban areas are inherently revealing of location. The characteristics of the mobility data, such as the number of activity records or the number of unique users in a given spatial unit, reveal the silhouette of the urban landscape, which can be used to infer the identity of the city in question. It was demonstrated that even without disclosing the exact location, the patterns of human mobility can still reveal the urban area from which the data was collected. The presented locating method was tested on other cities using different open data sets and against coarser spatial discretization units. While publishing mobility data is essential for research, it was demonstrated that concealing the observation area is insufficient to prevent the identification of the urban area. Furthermore, using larger discretization units alone is an ineffective solution to the problem of the observation area re-identification. Instead of obscuring the observation area, noise should be added to the trajectories to prevent user identification.

Iñigo Delgado-Enales, Joshua Lizundia-Loiola, Patricia Molina-Costa et al.

The increasingly populated cities of the 21st Century face the challenge of being sustainable and resilient spaces for their inhabitants. However, climate change, among other problems, makes these objectives difficult to achieve. The Urban Heat Island (UHI) phenomenon that occurs in cities, increasing their thermal stress, is one of the stumbling blocks to achieve a more sustainable city. The ability to estimate temperatures with a high degree of accuracy allows for the identification of the highest priority areas in cities where urban improvements need to be made to reduce thermal discomfort. In this work we explore the usefulness of image-to-image deep neural networks (DNNs) for correlating spatial and meteorological variables of a urban area with street-level air temperature. The air temperature at street-level is estimated both spatially and temporally for a specific use case, and compared with existing, well-established numerical models. Based on the obtained results, deep neural networks are confirmed to be faster and less computationally expensive alternative for ground-level air temperature compared to numerical models.

Bartosz Naskręcki, Piotr Pokora

This survey focuses on the geometric problem of log-surfaces, which are pairs consisting of a smooth projective surface and a reduced non-empty boundary divisor. In the first part, we focus on the geography problem for complex log-surfaces associated with pairs of the form $(\mathbb{P}^{2}, C)$, where $C$ is an arrangement of smooth plane curves admitting ordinary singularities. Specifically, we focus on the case in which $C$ is an arrangement consisting of smooth rational curves as its irreducible components. In the second part, containing original new results, we study log-surfaces constructed as pairs consisting of a complex projective $K3$ surface and a rational curve arrangement. In particular, we provide some combinatorial conditions for such pairs to have the log-Chern slope equal to $3$. Our survey is illustrated with many explicit examples of log-surfaces.

Godfrey Tawodzera, Jonathan Crush

Abstract South Africa’s major cities are periodically wracked by large-scale xenophobic violence directed at migrants and refugees from other countries. Informal sector businesses and their migrant owners and employees are particularly vulnerable targets during these attacks. Migrant-owned businesses are also targeted on a regular basis in smaller-scale looting and destruction of property. There is now a large literature on the characteristics and causes of xenophobic violence and attitudes in South Africa, most of it based on quantitative and qualitative research in the country’s major metropolitan areas. One of the consequences of big-city xenophobia has been a search for alternative markets and safer spaces by migrants, including relocating to the country’s many smaller urban centres. The question addressed in this paper is whether they are welcomed in these cities and towns or subject to the same kinds of victimization as in large cities. This paper is the first to systematically examine this question by focusing on a group of towns in Limpopo Province and the experiences of migrants in the informal sector there. Through survey evidence and in-depth interviews and focus groups with migrant and South African vendors, the paper demonstrates that xenophobia is also pervasive in these smaller centres, in ways that both echo and differ from that in the large cities. The findings in this paper have broader significance for other countries attempting to deal with the rise of xenophobia.

Anatolii BABIN, Tatiana COLESNICOVA, Sergiu TUTUNARU

The digital competitiveness of regions of EU member states is measured by the Digital Economy and Society Index (DESI), a composite index summarizing the progress made in connectivity, digital skills, internet use by citizens, digital integration of enterprises, farms and digital public services, while at the local government level there is currently no single indicator measured on a regular basis. Based on recent international and national researches, it can be concluded that with the development of digital technology, a significant increase in services and solutions available to citizens digitally is expected. Recent positive experiences of EU member states, which have been analyzed in previous research papers, show that the creation of jobs in agricol sectors in rural areas contributes to increasing household incomes. The objective of our study is to analyze and implement the methods and data sources for calculating DESI indicators at the level of local administrative units in the Republic of Moldova, in the context of the National Program for the European Village, launched in spring 2022. The results of the study will be the development of recommendations for local administrations on the use of the DESI index to coordinate the European evaluation parameters. The value of this work is in reinforcing activities for localisation of smart infrastructure and spatial data taking in consideration the DESI index and innovative products of the national Innovation Centres in innovative economics, stimulating investments in the creation of Smart Villages.

Ruisheng Wang, Shangfeng Huang, Hongxin Yang

Urban modeling from LiDAR point clouds is an important topic in computer vision, computer graphics, photogrammetry and remote sensing. 3D city models have found a wide range of applications in smart cities, autonomous navigation, urban planning and mapping etc. However, existing datasets for 3D modeling mainly focus on common objects such as furniture or cars. Lack of building datasets has become a major obstacle for applying deep learning technology to specific domains such as urban modeling. In this paper, we present a urban-scale dataset consisting of more than 160 thousands buildings along with corresponding point clouds, mesh and wire-frame models, covering 16 cities in Estonia about 998 Km2. We extensively evaluate performance of state-of-the-art algorithms including handcrafted and deep feature based methods. Experimental results indicate that Building3D has challenges of high intra-class variance, data imbalance and large-scale noises. The Building3D is the first and largest urban-scale building modeling benchmark, allowing a comparison of supervised and self-supervised learning methods. We believe that our Building3D will facilitate future research on urban modeling, aerial path planning, mesh simplification, and semantic/part segmentation etc.

Shubham Mante

The world has been experiencing rapid urbanization over the last few decades, putting a strain on existing city infrastructure such as waste management, water supply management, public transport and electricity consumption. We are also seeing increasing pollution levels in cities threatening the environment, natural resources and health conditions. However, we must realize that the real growth lies in urbanization as it provides many opportunities to individuals for better employment, healthcare and better education. However, it is imperative to limit the ill effects of rapid urbanization through integrated action plans to enable the development of growing cities. This gave rise to the concept of a smart city in which all available information associated with a city will be utilized systematically for better city management. The proposed system architecture is divided in subsystems and is discussed in individual chapters. The first chapter introduces and gives overview to the reader of the complete system architecture. The second chapter discusses the data monitoring system and data lake system based on the oneM2M standards. DMS employs oneM2M as a middleware layer to achieve interoperability, and DLS uses a multi-tenant architecture with multiple logical databases, enabling efficient and reliable data management. The third chapter discusses energy monitoring and electric vehicle charging systems developed to illustrate the applicability of the oneM2M standards. The fourth chapter discusses the Data Exchange System based on the Indian Urban Data Exchange framework. DES uses IUDX standard data schema and open APIs to avoid data silos and enable secure data sharing. The fifth chapter discusses the 5D-IoT framework that provides uniform data quality assessment of sensor data with meaningful data descriptions.

José Carpio-Pinedo, Gustavo Romanillos, Daniel Aparicio et al.

Ding Zhang, Hongdu Yi, Yang Chen et al.

Abstract In modern era, the maintenance of public infrastructure often takes up a large share of financial budget for a city. The management of these urban assets is supported by a frequently updated inventory reflecting facility conditions. Traditional methods relying on inspection staff or sensors are faced with two main challenges: comprehensive and standardized data collection; quick and automatic assessment process. In this technical note, we introduce a unified method for condition assessment, purely based on street views and machine learning to develop perception quantification models with pairwise labeling datasets. In this way, the two problems could be solved with automatic and scalable processes, updatable algorithms, and affordable costs The method has been tested in the city of Ulaanbaatar, in which a benchmark covering the assessment of eight types of urban infrastructure (roadway, road curbs, road markings, road signs, sidewalks, catch basins, guardrails, and manholes) is demonstrated.

José Carlos MACÍA ARCE, Francisco José ARMAS QUINTÁ

One of the pillars of the technological revolution that began in the seventies was the development of the Internet. This network has evolved in such a way that it now forms a complex structure that radically changed the social and economic dynamics at the end of century XX. Nowadays, new technologies allow anything from communication and information exchange to the realization of complex financial transactions, all from anywhere in the world and almost instantaneously. In spite of the widespread use of the Internet, there are still territories and inhabitants, mostly emplaced in remote rural areas, who live outside of this technological revolution. By contrast, urban areas enjoy a privileged position in the dissemination of the information society by concentrating most of the telecommunications infrastructure and monopolize the most qualified people. But there are many disparities in terms of diffusion of new technologies and these will transfer, in turn, to the enterprise sector which is the subject of this research. The differences in the use of new technologies and more specifically the use of advanced services on the Internet are related to the sector where the population is employed and its level of training. One of the advanced services offered by the Network is teleworking. Nowadays there are companies that offer their employees the opportunity to develop their professional activities outside their headquarters, using their homes as an alternative or call centers enabled with computers and Internet access. The purpose of this research is the study of the consumption of Internet advanced services by companies in the metropolitan area of Madrid, analyzing the spread of telework in more detail,a potential offered by new technologies and which may modify the current pattern of mobility in the main urban areas because it is from here where big companies are guiding the global economy.