Urban Informatics

Urban trees play a key role in reducing greenhouse gas emissions, cleaning air, promoting physical activity, and improving mental health. However, it is still largely unknown how the density and species of urban street trees may impact local public health. This study demonstrates how open data mining and large-scale spatial data integration can contribute to deeper insights into the effects of urban forestry. We analyze the impact of the spatial distribution of street trees by species in New York City by combining crowd-sourced tree census data-which includes geolocation, species, size, and condition for each of 652,169 street trees-with pollen activity, allergen severity, land use, housing conditions, and neighborhood demographic data. We further integrate neighborhood asthma hospitalization and emergency department visit rates and air quality data (PM2.5) to investigate how street trees impact local air quality and the prevalence of acute respiratory illness. Using a geographically weighted regression model, the results indicate that although a greater concentration of trees contributes to better local air quality, species with severe allergenicity can increase local asthma hospitalization rates in vulnerable populations, controlling for other covariates.

This paper applies urban informatics methods and techniques on big data generated from the concentrated environment of the second largest music festival in the world, Roskilde Festival. First, we explain how to utilize relevant dimensions from human geography theories towards mapping a 'Geography of Importance'. Second, we elaborate on methods deployed for collecting both mobile GPS and social media traces that the smart phone generates in physical spaces. Third, we compare and contrast the automatically geocoded presence in space and at events with the intentionally socially tagged consumption of these spaces and events as place-based experiences. In doing so, these two layers of space-based movements and place-based experiences reveal the appropriation of affordances and choices of aesthetic appreciation by the crowd at large of what is subjectively and relatively meaningful, actionable, and valuable.

We describe the Integrated Multimedia City Data (iMCD), a data platform involving detailed person-level self-reported and sensed information, with additional Internet, remote sensing, crowdsourced and environmental data sources that measure the wider social, economic and physical context of the participant. Selected aspects of the platform, which covers the Glasgow, UK, city-region, are available to other researchers, and allows knowledge discovery on critical urban living themes, for example in transportation, lifelong learning, sustainable behavior, social cohesion, ways of being in a digital age, and other topics. It further allows research into the technological and methodological aspects of emerging forms of urban data. Key highlights of the platform include a multi-topic household and person-level survey; travel and activity diaries; a privacy and personal device sensitivity survey; a rich set of GPS trajectory data; accelerometer, light intensity and other personal environment sensor data from wearable devices; an image data collection at approximately 5-second resolution of participants' daily lives; multiple forms of text-based and multimedia Internet data; high resolution satellite and LiDAR data; and data from transportation, weather and air quality sensors. We demonstrate the power of the platform in understanding personal behavior and urban patterns by means of three examples: an examination of the links between mobility and literacy/learning using the household survey, a social media analysis of urban activity patterns, and finally, the degree of physical isolation levels using deep learning algorithms on image data. The analysis highlights the importance of purposefully designed multi-construct and multi-instrument data collection approaches that are driven by theoretical frameworks underpinning complex urban challenges, and the need to link to policy frameworks (e.g., Smart Cities, Future Cities, UNESCO Learning Cities agendas) that have the potential to translate data to impactful decision-making.

This chapter considers the relationship between data and the city by critically examining six key issues with respect city dashboards: epistemology, scope and access, veracity and validity, usability and literacy, use and utility, and ethics. While city dashboards provide useful tools for evaluating and managing urban services, understanding and formulating policy, and creating public knowledge and counter-narratives, our analysis reveals a number of conceptual and practical shortcomings. In order for city dashboards to reach their full potential we advocate a number of related shifts in thinking and praxes and forward an agenda for addressing the issues we highlight. Our analysis is informed by our endeavours in building the Dublin Dashboard.

Urban areas are increasingly playing a bigger role in our societies. “Approximately 359 million people – 72% of the total EU population – live in cities, towns and suburbs. Urban areas face multiple and interconnected challenges related to employment, migration, demography, water and soil pollution, etc. But, they are also engines of new ideas and solutions, dynamic places where changes happen on a larger scale and at a fast pace. Over 70% of the EU’s population lives in towns and cities and this growth is set to continue in the coming years. Many of the social, economic and environmental issues Europe faces have an urban dimension and are most likely to have a larger impact in cities. On the other hand, cities are where the potential for innovation lies to solve these issues.” (1).
The European Union adopted the Pact of Amsterdam on the 30 May of 2016, a new European Urban Agenda (2). This document make official the strategy to improve the cooperation among cities and strengthen the "urban dimension" in EU decision making by assuming cities as priority funds target.
In order to stimulate growth, liveability and innovation in the cities of Europe and to ensure the maximum utilisation of the growth potential of cities to successfully tackle social challenges, the European Commission decided to fixe new working methods with the following objectives:
• To promote, develop, implement and evaluate regulations and legislation in line with local practice in cities, integrating the operative level of Member state with the local entities.
• To support cities in having a better access and utilisation of European funds, shifting the focus from territories to cities.
• To improve the cooperation based on sharing good practices, urban knowledge and innovation.
The United Nations Conference on Housing and Sustainable Urban Development took place this year in Quito, Ecuador (https://habitat3.org/) involving thirty thousand people from 167 countries and from different sectors: mostly local government and majors, but also non- profit, business and academia. The product of this event, happening ones in 20 years, is the New Urban Agenda, an action oriented document that set global standards of achievement in sustainable development. One of the major point of this global summit has been the new positive role accorded to the urbanization and the rethinking of cities as resources centre to exploit for improving the quality of life of the world population and address future challenges. The new role of ICT in shaping the future of cities has been synthetize in:
“We will promote the development of national information and communications technology policies and e government strategies as well as citizen-centric digital governance tools, tapping into technological innovations, including capacity development programmes, in order to make information and communications technologies accessible to the public, including women and girls, children and youth, persons with disabilities, older persons and persons in vulnerable situations, to enable them to develop and exercise civic responsibility, broadening participation and fostering responsible governance, as well as increasing efficiency. The use of digital platforms and tools, including geospatial information systems, will be encouraged to improve long-term integrated urban and territorial planning and design, land
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administration and management, and access to urban and metropolitan services.” New Urban Agenda (3).
It is not surprising that Computer Science is increasingly focusing on urban areas to support solutions towards the above challenges. If firstly Computer Science proposed technological solutions, as witnessed by the Smart Cities trend, nowadays citizens are becoming the centre of the debate. Marcus Foth in the Handbook of Research on Urban Informatics (4) affirms that “information is literally what constitutes a city” highlighting how the role of the physical city is to be a container for information-based human activities.
It is not surprising that Computer Science is increasingly focusing on urban areas to support solutions towards the above challenges. If firstly Computer Science proposed technological solutions, as witnessed by the Smart Cities trend, nowadays citizens are becoming the centre of the debate. Marcus Foth in the Handbook of Research on Urban Informatics (4) affirms that “information is literally what constitutes a city” highlighting how the role of the physical city is to be a container for information-based human activities.
Among the many challenges offered by urban areas we focus on the collaborative management by citizens of commons. A growing literature in sociology, economics, law architecture, etc. recognizes that cities are commons: urban areas are not only private or public, but they belong also to a third dimension of economics where citizens manage and take care of urban spaces and municipalities assume the role of enablers. This trend makes pair with the recognition that citizens play a role in public services and when this role is recognized and supported, it is likely that the services are improved. The Nobel prize Elinor Ostrom has been the economist who introduced in the scientific debate both issues from the ‘90s.
In both cases the point is supporting the cooperation among citizens via a civic platform. The first two requirements for such a platform are self-evident:
1. It must express the geographical dimension of urban spaces.
2. It must offer social network functionalities.
Already these two requirements pose a challenge, since there is no solution combining the two aspects both at a research and commercial level. Moreover, entering in the details of putting these two dimensions together raises a number of further research questions:
1. Since many social networks already exists, which are the requirements requesting for a new one of a different kind?
2. Which kind of entities should populate the urban map? which are the properties of such entities? which are their functionalities? how they are connect the one with the other?
3. Traditional cartography associates different information at different level of details. Current GIS or VGI technology don’t. How to allow users to interact with an urban map at different levels of detail? How to build automatically different scales starting from cartographic data such as OpenStreetMap?
4. Since the platform’s aim is to support cooperation, an explicit management of time is requested. Most social applications and VGI sistems don’t consider time. How to model the temporal dimension of urban entities in an effective and efficient way?
5. How organize the architecture of such a system, which merges social networking functionalities and GIS? Being a platform oriented to citizens, how to involve them in the co-design of the platform so to take advantage of a participatory approach?
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6. Finally, given the general-purpose character of such a platform, how to test it in different settings?
The methodology to answer these questions is not merely theoretical but it resulted in the development of the georeferenced FirstLife civic social network which the candidate worked on and in its testing, in an action-research fashion. In doing this, the candidate lead a team of several programmers and cooperated with the other researchers working on the co-design and testing, under the overall supervision of Prof. Guido Boella within the framework of several funded research projects (see Chapter 8).
Integral part of the thesis is thus the platform itself deriving from the research answering the above research questions. FirstLife is a fully functional prototype developed using precise software engineering methodologies and tested in several scenarios with around 2,000 users.

Due to the complex nature of the urban setting as a network of infrastructure operated as a public good, optimization models are often employed in transportation operations, planning, and logistics. Parameters of these models are often difficult to obtain in a straightforward manner: e.g. public agencies might not have data available from private sector to determine how they operate; travelers exhibit a wide variation in taste, preference, and circumstance in deciding their travel patterns; parameters of networks may only be observed dynamically without an easy way to derive their ergodic properties. With the prevalence of Big Data, it is now possible to use the observed outputs to reverse engineer (even autonomously) the parameters of the models from which only partial input information was available before. In the context of optimization models, this is called “inverse optimization”.
    In this seminar, the concept is introduced along with its applicability to mathematical programming problems: linear programming, integer programming, and nonlinear programming. Each can be applied to specific transportation problems: inverse shortest path problem when travel costs are uncertain but routes are observed; inverse vehicle routing problems to infer activity-based travel behavior from a population of observed travel patterns; inverse traffic assignment problems that work well for freight modeling with incomplete information about transshipment facility parameters. A fixed point prior for a sample population is introduced for regularization. Related ongoing research in activity-based modeling, network design, and urban logistics and how they will enhance the opportunities available from urban Big Data will be discussed.

Big Data is the term being used to describe a wide spectrum of observational or “naturally-occurring” data generated through transactional, operational, planning and social activities that are not specifically designed for research. Due to the structure and access conditions associated with such data, research and analysis using such data becomes significantly complicated. New sources of Big Data are rapidly emerging as a result of technological, institutional, social, and business innovations. The objective of this background paper is to describe emerging sources of Big Data, their use in urban research, and the challenges that arise with their use. To a certain extent, Big Data in the urban context has become narrowly associated with sensor (e.g., Internet of Things) or socially generated (e.g., social media or citizen science) data. However, there are many other sources of observational data that are meaningful to different groups of urban researchers and user communities. Examples include privately held transactions data, confidential administrative micro-data, data from arts and humanities collections, and hybrid data consisting of synthetic or linked data.

The emerging area of Urban Informatics focuses on the exploration and understanding of urban systems by leveraging novel sources of data. The major potential of Urban Informatics research and applications is in four areas: (1) improved strategies for dynamic urban resource management, (2) theoretical insights and knowledge discovery of urban patterns and processes, (3) strategies for urban engagement and civic participation, and (4) innovations in urban management, and planning and policy analysis. Urban Informatics utilizes urban Big Data in innovative ways by retrofitting or repurposing existing urban models and simulations that are underpinned by a wide range of theoretical traditions, as well as through data-driven modeling approaches that are largely theory agnostic, although these divergent research approaches are starting to converge in some ways. The paper surveys the kinds of urban problems being considered by going from a data-poor environment to a data-rich world and ways in which such enquiry have the potential to enhance our understanding, not only of urban systems and processes overall, but also contextual peculiarities and local experiences. The paper concludes by commenting on challenges that are likely to arise in varying degrees when using Big Data for Urban Informatics: technological, methodological, theoretical/epistemological, and the emerging political economy of Big Data.

Social media networks as a structure for virtual-space communication allow every individual to establish, install and even modify the reality of what he or she thinks important. Within the framework of massive data handling as the basis for citizenship building and citizen involvement in urban management, the paper below shows technical and visual documentation and discusses ideas, findings, conclusions and propositions for the devising of a platform that can help establish ties between public sector decision-makers in different areas including urban center modernization and planning based on massive data mined from Twitter. Therefore, the final objective is to offer a collaborative urban development tool that can assist in visualizing the massive and spontaneous self-generated urban data landscape.

In this paper we explore the notion of mobile users’ similarity as a key enabler of innovative applications hinging on opportunistic mobile encounters. In particular, we analyze the performance of known similarity metrics, applicable to our problem domain, as well as propose a novel temporal-based metric, in an attempt to quantify the inherently qualitative notion of similarity. Towards this objective, we first introduce generalized profile structures, beyond mere location, that aim to capture users interests and prior experiences, in the form of a probability distribution. Afterwards, we analyze known and proposed similarity metrics for the proposed profile structures using publicly available data. Apart from the classic Cosine similarity, we identify a distance metric from probability theory, namely Hellinger distance, as a strong candidate for quantifying similarity due to the probability distribution structure of the proposed profiles. In addition, we introduce a novel temporal similarity metric, based on matrix vectorization, to capitalize on the richness in the temporal dimension and maintain low complexity. Finally, the numerical results unveil a number of key insights. First, the temporal metrics yield, on the average, lower similarity indices, compared to the non-temporal ones, due to incorporating the dynamics in the temporal dimension. Second, the Hellinger distance holds great promise for quantifying simi- larity between probability distribution profiles. Third, vectorized metrics constitute a low-complexity approach towards temporal similarity on resource-limited mobile devices.

Transformations in wireless connectivity and location-aware technologies hold the promise of bringing a sea-change in the way transportation information is generated and used in the future. Sensors in the transportation system, when integrated with those in other sectors (for example, energy, utility and health) have the potential to foster novel new ways of improving livability and sustainability.

The end-result of these developments has been somewhat contradictory. Although automation in the transportation environment has become increasingly widespread, the level of involvement and active participation by people, in terms of co-creation and contribution of information, has also increased. As a result, the following two major trends have been observed: (1) increases in Machine-to- Machine (M2M) communications; and (2) increases in the variety and volume of User-Generated Content.

In this transportation paradigm, the pervasive use of Information and Communication Technologies will serve as the foundation for mobility intelligence towards an “ubiquitous information-centered mobility environment”. However, many technical and operational questions, as well as social, management and legal challenges present themselves in the transformation to this vision. The book presents a non-technical review of research and initiatives and a discussion of such opportunities and challenges.

Population wellness and quality of life are the results of complex urban biophysical and socioeconomic dynamics. This article explores this novel domain and introduces a broader context of urban data landscape and health indications. It also provides a specific project narrative as an exemplar-NYC PollenScape-describing its background, data, methods, and findings. A more general discussion of sociotechnical challenges in integrated data analytics for urban health follows. The paper concludes with a summary of key takeaways, current limitations, and future work.

Urban informatics is positioned to offer unique insights into complex urban processes through use of big data and pervasive computing. This paper examines the rise of urban informatics as a field of expert urban knowledge, with a focus on the particular visions and epistemologies of the city embedded within the field. By exploring its emergence over the past decade, and reflecting on connections with previous eras of urban computing, the article explores questions about the kind of city that is occupied, resolved and reformed by urban informatics and associated lab-style data sciences.

The purpose of this paper is to consider the role of ICT within the formalisation programme put forward by Recife’s City Council to regulate the informal trade that pervades the city’s popular squares and streets. This formalisation takes shape by issuing formal licenses to give informal workers ‘permission’ to sell pre-determined items at specific sites. Drawing on Foucault we will argue that ICT is a formalising technology, which serves this formalising regime to control, discipline and survey informal traders. We will argue that the technology’s disciplinary intent was shaped by: a) the ways by which the socio-political context, rather than a technical rationality, affected how both control and surveillance were performed and disciplinary decisions were enacted; b) how its appropriation by licensed workers facilitated the reach of the regime’s surveillance but in some cases also sabotaged the programme’s disciplinary intents, c) how the information system reinforced the marginalization of informal workers and strengthened the position of the municipality.

We describe the Integrated Multimedia City Data (iMCD), a data platform involving detailed person-level selfreported and sensed information, with additional Internet, remote sensing, crowdsourced and environmental data sources that measure the wider social, economic and physical context of the participant. Selected aspects of the platform, which covers the Glasgow, UK, city-region, are available to other researchers, and allows knowledge discovery on critical urban living themes, for example in transportation, lifelong learning, sustainable behavior, social cohesion, ways of being in a digital age, and other topics. It further allows research into the technological and methodological aspects of emerging forms of urban data. Key highlights of the platform include a multi-topic household and person-level survey; travel and activity diaries; a privacy and personal device sensitivity survey; a rich set of GPS trajectory data; accelerometer, light intensity and other personal environment sensor data from wearable devices; an image data collection at approximately 5-second resolution of participants' daily lives; multiple forms of text-based and multimedia Internet data; high resolution satellite and LiDAR data; and data from transportation, weather and air quality sensors. We demonstrate the power of the platform in understanding personal behavior and urban patterns by means of three examples: an examination of the links between mobility and literacy/learning using the household survey, a social media analysis of urban activity patterns, and finally, the degree of physical isolation levels using deep learning algorithms on image data. The analysis highlights the importance of purposefully designed multi-construct and multi-instrument data collection approaches that are driven by theoretical frameworks underpinning complex urban challenges, and the need to link to policy frameworks (e.g., Smart Cities, Future Cities, UNESCO Learning Cities agendas) that have the potential to translate data to impactful decision-making. energy data, or new technologies supporting crowdsourcing and usergenerated text, image, video, audio content, have either extended the ability to address existing research questions in new ways, For example, while earlier research utilized vehicle-based GPS to monitor traffic and transportation networks (Sen, Thakuriah, Zhu, & Karr, 1997; Sethi, Bhandari, Koppelman, & Schofer, 1995), the proliferation of cellphones and wearable devices that individuals can carry with them, allow passive monitoring of daily activities in minute detail leading to new research questions in mobility, health, and wellbeing (Appelboom et al.,

The model of urban entities to build a temporal indexing system for co-existing services and activities in the city is based on the development of time-features and time-based solutions for data management and retrieval in complex changing environments, considering the relation between spatial and time attributes, the time granularity organized in a scale theory, the multidimensionality and sematic of time. Starting from the model, this work present a pragmatic solution to build a global calendar of the city to represent real-time and fast retrieve a big dataset of entries. The presented solution on based on the extension of CRON expressivity on the basis of ICalendar basic features in order to switch from Point-Based CRON Expressions to Interval-Based CRON Masks.

The memory of loss in Asia’s leading global cities has been shaped by recurrent projects of urban renewal, which have sought to deliver economic prosperity and social order at the expense of longstanding spaces and practices. Singapore’s Golden Jubilee in 2015, which commemorated its triumphant postcolonial development, was accompanied by the proliferation of public expressions of nostalgia across a variety of media platforms. Amid the rise of the participatory culture of media convergence, this paper examines how nostalgic longing is no longer necessarily articulated as an antagonistic critique of the precarious present of neoliberal capitalism, which withdraws into a timeless image of a congenial past. Departing from this conventional understanding of nostalgia in the scholarship of Singapore, it explores how the ruling government since independence has reconfigured its dissemination of historical and cultural knowledge to manage its transition from a global city defined by rapid growth to a smart nation reliant on perpetual adjustment by cultivating a form of citizenship centred on entrepreneurship and innovation. Through immersive spatialisation, commissioned mobile video games oblige players to internalise the protocols of knowledge and agency of the Singapore Story, the official narrative of economic success and national progress. Two other state-run interactive digital platforms, the National Library’s online archive the Singapore Memory Project and the National Museum’s art installation 'The Story of the Forest', are designed to cultivate a new openness to the inevitability of iteration in urban informatics. Helping to assuage popular anxiety over the constancy of change and the failure of risk-taking, the latter frames perpetual adjustment as a vital component of the cosmic cyclicality of deep time, in which vanished realities are recreated with different permutations.

Exploring the spatial coupling relationship between cultural relics and historic sites and their surroundings can provide reasonable suggestions for the layout and development of commercial facilities and hold crucial significance for improving the management and maintenance of cul-tural relics and historical sites, as well as enhancing their attractiveness to the public. We chose District III of Shaoxing City as the research area based on the point of interest and road network data. This study analyzed the scale and accessibility of cultural relics and historic sites (CRHSs) as well as their surrounding commercial facilities, and then objectively evaluated their spatial layout and coupling relationship by employing kernel density estimation, standard deviation el-lipse, network analysis, inverse distance weight and the spatial correlation analysis method. The results show that: (1) from the perspective of spatial layout, the distribution of CRHSs has a posi-tive and strong correlation with the distribution of road networks; (2) there are noticeable varia-tions in the number of industrial facilities surrounding various CRHSs, closely related to the pro-tection grade of CRHSs; (3) the accessibility of commercial facilities surrounding CRHS varies significantly—commercial facilities surrounding CRHSs located within central District III of Shaoxing City have good accessibility, whereas those of the peripheral areas have comparatively poor accessibility; and (4) the accessibility of commercial facilities surrounding CRHSs in differ-ent administrative districts varies, showing an extremely uneven pattern.

Pedestrian activity and mobility are key factors for transportation modeling, public health, and city planning. Traditionally, city agencies conduct manual counts by location and time as a proxy of pedestrian volume in surrounding area. With increasing data sources in the urban domain, particularly open city data, social media, wireless networks, new methods, and data analytics approaches are needed to extract deeper insights on pedestrian activity, volume, and mobility. This paper utilizes a dataset of pedestrian counts conducted by the New York City Department of Transportation (DOT) from 2007 to 2015, and integrates these data with geocoded public transit, land use, building, and streetscape information. Based on 100 locations defined by DOT, the study further explores correlations between pedestrian volume and the surrounding localized urban context. Through data mining, visualization, and statistical modeling, this study aims to (1) identify baseline and key indicators of pedestrian volume, and explore potential integration of new data sources with current methodologies; (2) use integrated approaches to exam how pedestrian volume changes by location and time; and (3) use regression models to predict pedestrian volume across other intersections in NYC. The results provide key indicators for pedestrian volume estimation without conducting manual counts. Overall, this study demonstrates a novel approach in utilizing new data sources and generating deeper analytical insights to understand the determinants and predictors of pedestrian activity. International Conference on Sustainable Infrastructure 2017 303 © ASCE International Conference on Sustainable Infrastructure 2017 Downloaded from ascelibrary.org by New York University on 10/31/17. Copyright ASCE. For personal use only; all rights reserved. INTRODUCTION Pedestrian activity is a key factor in urban planning, transportation management, public health, and many locational decisions affecting development and land use. Analytical insights on local pedestrians are valuable for city agencies and business owners, so they can better estimate demand, allocate resources, and improve operations. However, it is challenging to capture pedestrians and analyze their activity, due to the spatial-temporal complexity of urban mobility. Many city agencies conduct manual counts by location and time as a proxy for pedestrian volume in surrounding areas. Such counting methodologies are labor intensive, costly, and only provide a small sample size without validation. Increasing urban data and computing power enable measuring and quantifying a location based on its surrounding urban context-essentially characterizing and defining a "place". This study explores a novel approach to quantify places based on rich, yet initially fragmented and siloed urban data at high spatial resolution, and identifies potential drivers of pedestrian activity. It uses biannual pedestrian count data from NYC Department of Transportation (DOT) to analyze pedestrian volume with surrounding physical, environmental, and socio-cultural urban features. The study begins with a literature review on measuring pedestrian activity and its drivers. The data section describes data collection and wrangling process for pedestrian count data and ancillary datasets in the urban domain. The methodology section elaborates on the details of our indicator development for urban contextual features and the regression models. We then present our findings and discuss the contributions and limitations of this exploratory study.

INTERCHANGING brings together a collection of design
projects and interdisciplinary perspectives on policy,
planning, design, and management issues that currently
– and are set to – shape and influence our expectations
and experiences of urban public transport environments.
With consideration of a range of social trends, but also
emerging responsive and sustainable technologies, the
essays and design projects presented here reimagine, in
various ways, a public transport Interchange of the Future
better suited to address the complexities and conditions
of 21st century urban digital life.

This article examines the dreams and wishes of young-adult city residents regarding future ICT development, comparing its findings with two visions of ICT development offered by large-scale urban agendas, namely ‘smart cities’ and ‘ubiquitous computing.’ The article explores how the visions of ordinary city inhabitants contest or resonate with grand visions of urban future, and investigates alternative agendas that might be built upon those visions. The research site, the city of Oulu in northern Finland, offers a concrete example of a ‘future city’ in which many ideas relating to ‘smart’ and ‘ubiquitous’ urban space have been put into practice. The results indicate there is an urgent need to address questions pertaining to control, agency, and resistance in designing further technology for cities and to employ design practices that enable the creation and implementation of bottom-up visions.

This paper examines the role that public transport last mile problems play in mode choice decisions of commuters, while controlling for trip, built environment, and decision maker related variables. Last-mile problems arise due to lack of adequate connectivity between transit stops and trip origin or termination points. The paper is motivated by previous literature which has pointed out that high-quality public transit needs to consider end-to-end connectivity from trip origins to destinations. In contrast to previous work on transit last mile problems which has focused on physical distance and sidewalks to transit stops, we consider a wider range of area factors including transit availability, job accessibility, parking costs, the quality of the pedestrian environment and risks to pedestrians from vehicular traffic, and social characteristics such as street-level crime. Using a discrete choice model, our goal is to unpack ways in which such factors contribute to the last mile problem in home-based work trips, while controlling for these wider range of factors as well as the usual variables such as cost and trip time that inform mode choice. We find that the prevalence of non-domestic violent crimes reduces the odds of using all types of non-motorized alternatives as well as transit that is accessed either by walking or driving. Using compensating variation to measure welfare changes, we show that there are significant benefits that could be brought to transit service users

Mobile and locative media are systems of technologically mediated communication providing the opportunity to relate physical environments with digital information in order to create " hybrid " spatial experiences, which may function as the context for cultural activities. This has led to new ways of creating, representing and communicating meaning in relation to space and consequently to emergent artistic practices. At the same time, the emerging field of urban informatics addresses novel ways of interacting with our cities and their digital content. Mobile sound art, at the intersection of these technological innovations, deals with the urban environment as a musical interface and employs mobile devices that offer new possibilities for artists to actively involve their audiences. This paper focuses on the soundwalk, as a subspecies of mobile sound art, and attempts to shed light on the relationship between sonic artistic practices and the everyday mobile communication experience by investigating specific examples of this art form.

Previous epidemic management research proves the importance of city-level information, but also highlights limited expertise in urban data applications during a pandemic outbreak. In this paper, we provide an overview of city-level information, in combination with analytical and operational capacity, that define urban intelligence for supporting response to disease outbreaks. We present five components (movement, facilities, people, information, and engagement) that have been previously investigated but remain siloed to successfully orchestrate an integrated pandemic response. Reflecting on the coronavirus disease (COVID-19) outbreak that was first identified in Wuhan, China, we discuss the opportunities, technical challenges, and foreseeable controversies for deploying urban intelligence during a pandemic. Finally, we emphasize the urgency of building urban intelligence through cross-disciplinary research and collaborative practice on a global scale.

As data-driven approaches are introducing and establishing a new set of economic, social and cultural values, we have started to question some of our age old assumptions, conceptions and practices about our built habitat. One of the most profound implications is the transformation of the AEC (Architecture, Engineering and Construction) industry from a document based to an information based business. Both the impact and scale of this transformation will become more dramatic with the increase in global data traffic two thirds of which is predicted to move on to cloud computing systems by 2016 (Cisco Global Cloud Index, 2011-2016). This implies the introduction of even more complex and diverse interactions (e.g. through internet of things) between buildings, infrastructures and humans. Such developments have already made significant impact in other industries and are likely to be a step change in how we build and operate in the near future. “Data” is not new to our industry, however what is new is the amount of data that is currently available to us and our improved capacity to share, capture, measure, compile, process and translate data into meaningful and actionable information. Although the potentials are vast, Architectural/Engineering practice and Construction sector are slow to adopt the data-driven approaches. The IDDF (Intelligent Data-Driven Design Futures) symposium brought together some of the world-leading thinkers, practitioners and innovators from the Built Environment and Urban Informatics research and practice to explore what “data-integrated” future might hold for our sector. The presentations and discussions challenged our “business as usual” mode of thinking and highlighted diverse insights and perspectives for more agile and adaptive solutions for the future, and in discovering sustainable modes of imagining, creating and working intelligently. With this document we aim to summarize the presentations and discussions, and highlight some of the diverse insights and perspectives we captured from this day-long symposium.

Recent increases in the use of and applications for wearable technology has opened up many new avenues of research. In this paper, we consider the use of lifelogging and GPS data to extend fine-grained movement analysis for improving applications in health and safety. We first design a framework to solve the problem of indoor and outdoor movement detection from sensor readings associated with images captured by a lifelogging wearable device. Second we propose a set of measures related with hazard on the road network derived from the combination of GPS movement data, road network data and the sensor readings from a wearable device. Third, we identify the relationship between different socio-demographic groups and the patterns of indoor physical activity and sedentary behaviour routines as well as disturbance levels on different road settings.

The paper presents a comparison between aims, theories and practices in city planning and in the use of web-based technologies in urban activities to highlight the different instances of the two macro-domains in conceptualizing city dynamics and elaborating solutions to address urban challenges. The analysis had been structured by considering the three key dimensions constituting the pillars of Urban Informatics: people, city and technology. The analysis had been developed focusing first on the misalignments between current web-based technologies and city planning, then moving to the identification of their convergences. Building on this analysis, the paper outlines three future directions to rethink the integration and future design of web-based technologies in city planning actions as planning support systems to manage the production and use of city data, the orchestration of local activities , and the integration of city plans with distributed urban initiatives.

As more people tweet, check-in and share pictures and videos of their daily experiences in the city, new opportunities arise to understand urban activity. When aggregated, these data can uncover invaluable local insights for local stakeholders such as journalists, first responders and city officials. To better understand the needs and requirements for this kind of aggregation tools, we perform an exploratory study that includes interviews with 12 domain experts that utilize local information on a daily basis. Our results shed light on current practices, existing tools and unfulfilled needs of these professionals. We use these findings to discuss the requirements for hyper-local social media data aggregation tools for the study of cities on a large scale. We outline a list of key features that can better serve the discovery of patterns and insights about both real-time activity and historical perspectives of local communities.

This report provides a summary of the organization, program, and outcome of the Dagstuhl Seminar titled "Do-it-yourself networking: an interdisciplinary perspective". We first motivate our interest in wireless networks operating outside the public Internet and the selection of the most relevant areas of expertise. Then we describe the process of bringing together a balanced group of representatives from these areas, and the evolution of the seminar over time. An overview of the interactions during the work in groups on specific application areas and explorations of the concept of failure, edited collectively by the members of the different groups, summarizes the main outcomes of the seminar. Finally, we identify some important lessons learned for facilitating interdisciplinary collaborations and conclude with our plans toward building a DIY networking community of researchers and activists.

Developing a civic social network requires to consider users meeting in real life, collaborating on digital entries related to real urban entities. This makes necessary to think about collaboration tools in a new perspective: ensuring the participation of users with different levels and forms of legitimacy to represent complex relations among entities, and ensuring the accountability of each contributor. We present a set of technical solutions allowing the collaboration on complex entities, keeping interactions simple, and representing multiple perspectives about shared entities.

Die Zersiedelung von Landschaft involviert zwei wichtige Faktoren: Erstens, die Erhöhung des Verkehrsaufkommens, sowie zweitens eine Beeinträchtigung (bis hin zur Schädigung) der Natur. Dies sind die Hauptkritikpunkte im Kontext nachhaltiger, dauerhafter (robuster) Planung. Folgend einer Studie von Newman and Kenworthy (1989) zur Beziehung zwischen Siedlungsdichte und Energieverbrauch, galt lange das Modell der kompakten Stadt als Ansatz gegen die Zersiedelung von Landschaft. Betrachtet man das Kompakte-Stadt-Modell seitens der Haushalte, konsumieren diese (mit unterschiedlicher Gewichtung) nicht nur urbane Service- und Freizeiteinrichtungen sowie Arbeitsplätze, sondern streben zudem nach einem effizienten Zugang zu Grünraum und Freizeitangeboten. Verschiedenen Studien haben gezeigt, dass Haushalte in Vorstädten und -orten oft eine geräuscharme und ruhige Wohnumgebung in Form von Einfamilienhäusern bevorzugen (Département Stratégies d´Opinion/Société 2007). Dies wiederum negiert eine räumliche Verdichtung. Es ist nicht verwunderlich, dass politische Maßnahmen, welche das Kompakte-Stadt-Modell favorisieren, sich als weniger effizient in Folge der weit verbreiteten Referenz zum Einfamilienhaus als angenommen erwiesen haben. Breheny (1977) hingegen unterstreicht, dass die verschiedenen Typen von Vororten ein Ansteigen in Wohnkosten, Verkehrsüberlastung und -stau und eine reduzierte Zugänglichkeit zu Freizeitaktivitäten induzieren. Schwanen et al. (2004) zeigte auf, dass Haushalte ihre Wohnstandortwahl im Hinblick auf die Zugänglichkeit verschiedener Service- und Freizeiteinrichtungen optimieren. Die über-kompakte Stadt kann dagegen zeitlich konzentrierte hohe Verkehrsströme für den Zugang zu Grünraum und Freizeitarealen generieren, sondern die Wahl des Wohnstandortes insofern beeinflussen, dass Baugründe (von Jungfamilien) bevorzugt werden, welche entfernter vom Zentrum liegen. Zudem kann übermäßige Kompaktheit und Verdichtung ökologische Probleme in Form von z.B. dem Fehlen von Frischluft-/Klimaschneisen hervorrufen.
Aus diesem Grund wird nach einer planerischen Lösung gesucht, welche einerseits die Zersiedelung steuern und des Weiteren das gegegensätzliche Zwillingspaar von Grünraum/bebautem Raum in Form einer hocheffizienten Methode verweben kann. Diese Lösung muss zudem dynamische Aspekte der Stadt sowie die Minimierung von Verkehrskosten und Emission bei gleichzeitiger Vermeidung von zusätzlichen Versiegelungen von Frei- und Agrarflächen leisten.
Basierend auf der Beobachtung, dass der urbane Raum auf dem Prinzip der fraktalen Geometrie fundiert (Batty und Longley 1994; Batty 1994, 2006; Pumain 1997, 2006; Frankhauser 1994; Gaibax 1999; Thomas 2004, 2007, 2008) scheint es interessant zu untersuchen, in welchem Ausmaß fraktale Geometrie verwendet werden kann, um den räumlichen Antagonismus von Zersiedelung und Kompaktheit zu lösen (cf. Frankhauser 2008; Czerkauer-Yamu und Frankhauser 2010, 2011; Czerkauer-Yamu 2012; Tannier 2012).
Rufen wir uns in Erinnerung, dass fraktale Objekte multiskalar und selbstähnlich sind (cf. Mandelbrot 1977). Das Attribut „multiskalar“ definiert die Existenz eines hierarchischen Ordnungsprinzips – das Vorhandensein gleicher Elemente auf verschiedenen Maßstabsebenen (von urbanisiertem Raum und Freiraum). Dieses Ordnungsprinzip folgt einer fraktalen Logik. Es basiert auf Kaskaden selbstähnlicher Elemente auf unterschiedlichen Maßstabsebenen mit inhärenter unterschiedlicher Aufmerksamkeit auf Details. In einem urbanen Kontext ist dies z.B.: Stadt, Quartier, Block, Haus; oder: Autobahn, Stadtautobahn, Durchgangsstraße, Hauptstraße, Seitenstraße, Wohnstraße und Pfad. Der Vorteil einer „starken“ Hierarchie ist effizientes, funktionales System, das auf natürliche Weise mit fraktalen Strukturen (bebaute Fläche, Straßennetzwerk) verknüpft ist. Jede Stadt beinhaltet hierarchische Strukturen als Kombination von Planungs- und Selbstorganisationsprozessen mit einer mehr oder weniger Konsolidierung
(bottom-up und top-down Prozesse).

Building alteration and redevelopment play a central role in the revitalization of developed cities, where the scarcity of available land limits the construction of new buildings. The adaptive reuse of existing space reflects the underlying socioeconomic dynamics of the city and can be a leading indicator of economic growth and diversification. However, the collective understanding of building alteration patterns is constrained by significant barriers to data accessibility and analysis. We present a data mining and knowledge discovery process for extracting, analyzing, and integrating building permit data for more than 2,500,000 alteration projects from seven major U.S. cities. We utilize natural language processing and topic modeling to discover the thematic structure of construction activities from permit descriptions and merge with other urban data to explore the dynamics of urban change. The knowledge discovery process proceeds in three steps: (1) text mining to identify popular words, popularity change, and their co-appearance likelihood; (2) topic modeling using latent Dirichlet allocation (LDA); and (3) integrating the topic modeling output with building information and ancillary data to discover the spatial, temporal, and thematic patterns of urban redevelopment and regeneration. The results demonstrate a generalizable approach that can be used to analyze unstructured text data extracted from permit records across varying database structures, permit typologies, and local contexts. Our machine learning methodology can assist cities to better monitor building alteration activity, analyze spatiotemporal patterns of redevelopment, and more fully understand the economic, social, and environmental implications of changes to the urban built environment.

Developing a civic social network requires to consider users meeting in real life, collaborating on digital entries related to real urban entities. This makes necessary to think about collaboration tools in a new perspective: ensuring the participation of users with different levels and forms of legitimacy to represent complex relations among entities, and ensuring the accountability of each contributor. We present a set of technical solutions allowing the collaboration on complex entities, keeping interactions simple, and representing multiple perspectives about shared entities.

This paper assesses non-traditional urban digital infomediaries who are pushing the agenda of urban Big Data and Open Data. Our analysis identified a mix of private, public, non-profit and informal infomediaries, ranging from very large organizations to independent developers. Using a mixed-methods approach, we identified four major groups of organizations within this dynamic and diverse sector: general-purpose ICT providers, urban information service providers, open and civic data infomediaries, and independent and open source developers. A total of nine types of organizations are identified within these four groups. We align these nine organizational types along five dimensions that account for their mission and major interests, products and services, as well activities they undertake: techno-managerial, scientific, business and commercial, urban engagement , and openness and transparency. We discuss urban ICT entrepreneurs, and the role of informal networks involving independent developers, data scientists and civic hackers in a domain that historically involved professionals in the urban planning and public management domains. Additionally, we examine convergence in the sector by analyzing overlaps in their activities, as determined by a text mining exercise of organizational webpages. We also consider increasing similarities in products and services offered by the infomediaries, while highlighting ideological tensions that might arise given the overall complexity of the sector, and differences in the backgrounds and end-goals of the participants involved. There is much room for creation of knowledge and value networks in the urban data sector and for improved cross-fertilization among bodies of knowledge.

Urban logistics systems consist of networked infrastructure or vehicle fleets serving the flow of travelers, goods, energy, or information in an urban context, e.g. public transit, freight and energy distribution, or road networks. A smart system is one that can adapt to changes in the environment and is aware of the behavioural needs of its users. This seminar addresses a question asked by policymakers in an age of ubiquitous data, urbanization, and need for sustainability: once we have an “instrumented city” setting where continuous streams of data are available, how can we make the most use of it? We touch upon two solutions and new questions that they bring.
The first is to introduce flexibility in the design of transportation networks. The basic network design problem is introduced along with its limitations. The static problem is modified to a stochastic dynamic programming formulation using approximate dynamic programming solution methods from real option theory to overcome the “curse of dimensionality”. This approach allows system designs to be viewed as options over time instead of as commitments, which explicitly incorporate the value of flexibility under uncertainty.
The second is incorporating user awareness. Systems designs often neglect the behavioral responses of users. We introduce the concept of an “activity-based network design problem”, where the design of a network is not based on pre-defined OD demand, but instead outputs the demand as a consequence of the network design and the users’ inherent preferences for activities.
Ongoing research and challenges are highlighted. Foremost among these challenges are the need to design and evaluate transport service systems at an urban level (e.g. if bike-sharing were incorporated by the City of Toronto as an extended service of the TTC, how would people’s travel patterns adjust and adopt the service? How would parking prices be affected?); the need to visualize these changes in a portfolio framework (as interacting assets that change value over time visualized in a GIS platform); and the need to validate service design strategies and operational business models using mobile device-based test beds.

Synthetic aperture radar (SAR) and interferometric SAR (InSAR) are state-of-the-art radar remote sensing technologies and are very useful for urban remote sensing. The technologies have some very special characteristics compared to optical remote sensing and are especially advantageous in cloudy regions due to the ability of the microwave radar signals used by the current SAR sensors to penetrate clouds. This chapter introduces the basic concepts of SAR, differential InSAR, and multi-temporal InSAR, and their typical applications in urban remote sensing. Examples of applying the various InSAR techniques in generating DEMs and monitoring ground and infrastructure deformation are given. The capabilities and limitations of InSAR techniques in urban remote sensing are briefly discussed.