Urban Mosaic: Visual Exploration of Streetscapes Using Large-Scale Image Data

Urban planning is increasingly data driven, yet the challenge of designing with data at a city scale and remaining sensitive to the impact at a human scale is as important today as it was for Jane Jacobs. We address this challenge with Urban Mosaic,a tool for exploring the urban fabric through a spatially and temporally dense data set of 7.7 million street-level images from New York City, captured over the period of a year. Working in collaboration with professional practitioners, we use Urban Mosaic to investigate questions of accessibility and mobility, and preservation and retrofitting. In doing so, we demonstrate how tools such as this might provide a bridge between the city and the street, by supporting activities such as visual comparison of geographically distant neighborhoods,and temporal analysis of unfolding urban development.Comment: Video: https://www.youtube.com/watch?v=Nrhk7lb3GU

Hybrid cities and new working spaces – The case of Oslo

Recent decades have seen the emergence of hybrid models of living and working associated typologies. These developments have been analysed from the perspective of different disciplines, each with their own interpretation of this phenomenon. Planning and architecture have addressed hybridization as a specific form of interaction between spatio-functional features (such as mixed use, multi-functionality and flexibility) and social features (such as formal and informal interactions and the spontaneous appropriation of spaces) or have sometimes simply focused on the spatio-functional dimension in urban spaces. Studies from other disciplines (e.g. mobility networks, transportation, sociology and information technology) have shown that hybrid spaces cannot exist without access to digitalization technologies. Such technologies are accelerating hybridization processes. This study examines the complex and layered phenomenon of hybridization as a possible combination of (or interaction between) spatio-functional, social and digital features within the planning debate and related fields. Most of the case studies explored by scholars so far have focused on interactions occurring between residential, social and recreational functions, but working functions are playing an increasingly important role. Furthermore, the COVID-19 pandemic has accelerated the development of new forms of hybridity in cities. As a consequence, the rising use of hybrid (on-site and on-line) working practices, planners, policy makers and stakeholders, as well as scholars, have increasingly discussed the concept of hybridization. In this context, various hybrid typologies of urban spaces have materialized in forms such as new working spaces (NWS) which include co-working spaces, incubators, as well as some cafés and multi-functional public libraries, which have recently provided working spaces. This paper focuses on the evolving concept of hybridity from the planning perspective. Based on five hybrid NWS including their surrounding neighbourhoods in Oslo, it provides empirical evidence for an understanding of the phenomenon that may support the development of hybrid spaces and buildings and develops suggestions for planning strategies. © 2022 The Author

Echo State Transfer Learning for Data Correlation Aware Resource Allocation in Wireless Virtual Reality

In this paper, the problem of data correlation-aware resource management is studied for a network of wireless virtual reality (VR) users communicating over cloud-based small cell networks (SCNs). In the studied model, small base stations (SBSs) with limited computational resources act as VR control centers that collect the tracking information from VR users over the cellular uplink and send them to the VR users over the downlink. In such a setting, VR users may send or request correlated or similar data (panoramic images and tracking data). This potential spatial data correlation can be factored into the resource allocation problem to reduce the traffic load in both uplink and downlink. This VR resource allocation problem is formulated as a noncooperative game that allows jointly optimizing the computational and spectrum resources, while being cognizant of the data correlation. To solve this game, a transfer learning algorithm based on the machine learning framework of echo state networks (ESNs) is proposed. Unlike conventional reinforcement learning algorithms that must be executed each time the environment changes, the proposed algorithm can intelligently transfer information on the learned utility, across time, to rapidly adapt to environmental dynamics due to factors such as changes in the users' content or data correlation. Simulation results show that the proposed algorithm achieves up to 16.7% and 18.2% gains in terms of delay compared to the Q-learning with data correlation and Q-learning without data correlation. The results also show that the proposed algorithm has a faster convergence time than Q-learning and can guarantee low delays.Comment: This paper has been accepted by Asiloma

Interfacing the space of flows and the space of places in the platform society: ten years of Airbnb in Florence

Questo articolo prende in prestito i concetti di spazio dei flussi e spazio dei luoghi avanzati da Castells (1996) per sostenere che le piattaforme digitali svolgono il ruolo chiave di interfaccia, di medium, tra lo spazio dei luoghi e lo spazio dei flussi. Le piattaforme digitali, come Airbnb, possono infatti essere considerate come ‘orchestratori di reti’ che gestiscono i flussi di dati e informazioni prodotti dagli utenti (ospiti e Host) attraverso la piattaforma stessa. Per dimostrare come la combinazione di reti e luoghi impatti lo spazio urbano, abbiamo analizzato Airbnb come “un’interfaccia tra comunicazione elettronica e interazione fisica” e dimostrato l’utilità delle idee di Castells per esplorare l’impatto della piattaforma alla scala intra-urbana. Il contributo sviluppa un’analisi spazio-temporale di 12.126 annunci georeferenziati e 651.515 recensioni lasciate dagli utenti di Airbnb sulla piattaforma dal 2010 al 2019 a Firenze (Italia). In questo contesto, le recensioni agiscono come una camera d’eco per lo spazio dei flussi, forgiando alcune aree specifiche della città che soddisfano i requisiti della comunità Airbnb. Inoltre, la progressiva trasformazione di appartamenti privati in nodi della rete turistica globale crea una divisione spaziale sempre più frammentata tra porzioni di città connesse a livello globale e altri spazi geograficamente contigui ma non connessi. Tale processo è geograficamente disomogeneo e riproduce modelli ben noti di concentrazione del valore, in cui i simboli creano una realtà urbana virtualmente contraffatta, destinata ad imitare il luogo proiettato nella piattaforma

Sustainable urban dynamics in coastal cities: A comparative study through digital footprints

This research conducts a comparative urban analysis of two coastal cities with analogous tourism models situated in distinct geographical regions: Balneário Camboriú in Brazil and Benidorm in Spain. The study delves into two critical urban phenomena impacting the sustainability of tourist cities, utilising social network data to gather insights into economic and urban activities (Google Places) and spatio-temporal patterns of citizen presence (Twitter). The spatial analysis explores the municipal and, to a more detailed extent, the coastal strip extending 500 m inland from the coastline, spanning the entire length of each city to their municipal boundaries. The analysis uncovers both similarities and differences between the two destinations, offering insights that could inform future development strategies aimed at fostering sustainable urban environments in these well-established coastal tourist areas.This research has been funded by Consejería de Transformación Económica, Industria, Conocimiento y Universidades. Junta de Andalucía (UMA20-FEDERJA-131) and the University of Alicante (UAFPU2021-52)

An attitude-based reasoning strategy to enhance interaction with augmented objects

This paper describes a mobile-based system to interact with objects in smart spaces, where the offer of resources may be extensive. The underlying idea is to use the augmentation capabilities of the mobile device to enable it as user-object mediator. In particular, the paper details how to build an attitude-based reasoning strategy that facilitates user-object interaction and resource filtering. The strategy prioritizes the available resources depending on the spatial history of the user, his real-time location and orientation and, finally, his active touch and focus interactions with the virtual overlay. The proposed reasoning method has been partially validated through a prototype that handles 2D and 3D visualization interfaces. This framework makes possible to develop in practice the IoT paradigm, augmenting the objects without physically modifying them

Analysis of Large-Scale Traffic Dynamics in an Urban Transportation Network Using Non-Negative Tensor Factorization

International audienceIn this paper, we present our work on clustering and prediction of temporal evolution of global congestion configurations in a large-scale urban transportation network. Instead of looking into temporal variations of traffic flow states of individual links, we focus on temporal evolution of the complete spatial configuration of congestions over the network. In our work, we pursue to describe the typical temporal patterns of the global traffic states and achieve long-term prediction of the large-scale traffic evolution in a unified data-mining framework. To this end, we formulate this joint task using regularized Non-negative Tensor Factorization, which has been shown to be a useful analysis tool for spatio-temporal data sequences. Clustering and prediction are performed based on the compact tensor factorization results. The validity of the proposed spatio-temporal traffic data analysis method is shown on experiments using simulated realistic traffic data

Becoming Gentrifier/d: Aesthetics, Subjectivities, and Rhythms of Gentrification in Seoul, South Korea

Gentrification has been extensively studied beyond Euro-American societies. In particular, previous research of Seoul’s residential gentrification has broadened our understanding of the role of the developmental state and property speculation in urban clearance and renewal. However, little attention has been paid to the contemporary retail gentrification in Seoul that has different aesthetics, subjectivities, and rhythms compared to residential gentrification. In retail gentrification, old urban neighborhoods are no longer demolished but cherished with their nostalgic landscapes and atmospheres. In this context, this dissertation project explores Seochon, a gentrifying neighborhood in Seoul, that was designated as a cultural heritage site in 2010. Since then, this previously underdeveloped neighborhood has become a famous tourist destination for urban adventurers who desire authentic objects, places, and experiences. Combining ethnographic and archival research, this project examines how the cultural politics around authenticity entwine with historic preservation and retail gentrification. Specifically, I address three questions: 1) how the hyperreal simulacra of the past aesthetically assemble Seochon as an authentic urban village, 2) how the fantasy of authenticity endlessly renews the desire for something more authentic while sustaining the paradoxical subjectivities of gentrification, and 3) how the in-betweens on the topological edge of the gentrifier/gentrified embody and enact gentrification in and through the heterogeneous space-times of Seochon. Consequently, the project opens new political possibilities to challenge gentrification-induced displacements by demystifying their physical and psychological processes. In doing so, this project contributes to more nuanced perspectives on Seoul’s gentrification, which has been predominantly identified with state-led, residential urban renewal. At the same time, the project engages with epistemological and ontological limitations in previous gentrification studies through the poststructural lenses of Baudrillard, Lacan, and Deleuze. Specifically, I dismantle the dualistic ideas of good/bad, authentic/inauthentic, and gentrifier/gentrified by analyzing the ever-changing rhythms of gentrification and displacement. Indeed, the paradoxical subjects of gentrification continue to decenter their subjectivities and distort the dynamics of displacement. Thus, they are virtually/actually in-betweens as they become gentrifier and simultaneously gentrified (gentrifier/d). This reconceptualization of ambivalent and mobile subjectivities highlights differences within and beyond the monstrously imagined gentrification while disclosing the potential for the fight against it from its sponge-like inside. Furthermore, this project empirically demonstrates this theoretical reframing based on 13 months of qualitative fieldwork and 47 interviews with 50 participants. I illustrate how the subjects of gentrification place themselves in Seochon by reinventing authenticity and displacing their imagined (in)authentic selves/others. Throughout various cultural politics around what authentic Seochon is, the subjects were ‘becoming gentrifier/d.’ I was one of them as I occupied everyday spaces of the neighborhood, interviewed old-timers and newcomers, participated in a local foodie community, and worked at a hipster-oriented restaurant as a server. Drawing on this autoethnography, the project uncovers the fantasy of authenticity as well as the heterogeneous space-times of gentrification, which are built upon people’s desires, imaginations, embodiments, and performances, including my own. Ultimately, this theoretical and empirical revisit enables us to mirror ourselves onto gentrification and to bear our responsibility in challenging the gentrification-induced displacements that we create

THE ARCHAEOLOGY OF THE POSTINDUSTRIAL: SPATIAL DATA INFRASTRUCTURES FOR STUDYING THE PAST IN THE PRESENT

Postindustrial urban landscapes are large-scale, complex manifestations of the past in the present in the form of industrial ruins and archaeological sites, decaying infrastructure, and adaptive reuse; ongoing processes of postindustrial redevelopment often conspire to conceal the toxic consequences of long-term industrial activity. Understanding these phenomena is an essential step in building a sustainable future; despite this, the study of the postindustrial is still new, and requires interdisciplinary connections that remain either unexplored or underexplored. Archaeologists have begun to turn their attention to the modern industrial era and beyond. This focus carries the potential to deliver new understandings of the industrial and postindustrial city, yet archaeological attention to the postindustrial remains in its infancy. Developments in the ongoing digital revolution in archaeology and within the social sciences and humanities have the potential to contribute to the archaeological study of the postindustrial city. The development of historical GIS and historical spatial data infrastructures (HSDIs) using historical big data have enabled scholars to study the past over large spatial and temporal scales and support qualitative research, while retaining a high level of detail. This dissertation demonstrates how spatial technologies using big data approaches, especially the HSDI, enhance the archaeological study of postindustrial urban landscapes and ultimately contribute to meeting the “grand challenge” of integrating digital approaches into archaeology by coupling reflexive recording of archaeological knowledge production with globally accessible spatial digital data infrastructures. HSDIs show great potential for providing archaeologists working in postindustrial places with a means to curate and manipulate historical data on an industrial or urban scale, and to iteratively contextualize this longitudinal dataset with material culture and other forms of archaeological knowledge. I argue for the use of HSDIs as the basis for transdisciplinary research in postindustrial contexts, as a platform for linking research in the academy to urban decision