City Dashboards and 3D Geospatial Technologies for Urban Planning and Management

Introduction

Data have long been generated about cities to make sense of them, manage services and infrastructure, solve urban problems, and produce urban policy and plans. Indeed, managing data across the data life cycle (generating, handling, storing, analysing, archiving, sharing and destroying) is a key activity of city administrations and other public agencies. Traditionally, data are generated as a by-product of core administrative functions (such as routine bureaucracy), as a core function of infrastructure or service (such as traffic management), or through routine and commissioned surveys (such as household surveys or a census). These data provide key inputs for strategic development planning (such as creating local area plans), assessing proposed planning applications, and operational governance (such as the delivery of services).

Since the early 1990s, and through the adoption of Agenda 21 of the United Nations Conference on Environment and Development (UNCED) in particular, cities have been mandated to systematically monitor sustainable development and adopt evidence-based decision-making. To that end, cities have sought to gather and use available data to compile city indicators (recurrent quantified measures) that enable key aspects of urban life (economy, labour markets, health, education, transport, housing, etc.) to be tracked over time (Innes and Booher, 2000; Maclaren, 1996; Van Assche et al., 2010). New managerialist approaches to the public sector emerged which promoted the use of indicators to monitor the performance of cities and city administrations and track the implementation and consequences of policy initiatives in order to make public services more efficient, effective, transparent, and value for money (Behn, 2014; Kitchin et al., 2015). Urban indicators also enable benchmarking that establishes how well a neighbourhood/city is performing vis-a-vis other locales or against best practices (Huggins, 2009). More recently, the open government agenda, and the drive to create open government data, has sought to make both the underlying data and urban indicators open for the public to scrutinise and use (Kitchin, 2014a). Also, such initiatives often seek to make operational, real-time data (such as environmental sensing, weather sensors, bike share, car park spaces, real-time passenger information) available through various web services and APIs.

These core datasets and indicators provide key inputs for applied urban data analysis intended for both professional audiences (planners, managers, technocrats, policymakers) and for public consumption. One of the key means by which the results of these analyses are disseminated is through city dashboards. Here, a suite of visual devices ranging from numeric displays to analytical charts is used to display indicator data through a common graphic interface. This may also incorporate interactive elements, enabling users to query specific data. More recently, city dashboards have been complemented by the development of 3D geospatial tools that transpose city-data onto three-dimensional landscape representations of the city. In this chapter, we discuss the form of applied data analysis conducted with city dashboards and emerging 3D geospatial tools. We contend that these spatial media provide a valuable means to make sense of often complex data, especially for those that lack the skills to create their own data visualisations, though they are not without critique and shortcomings. We discuss some of those criticisms and indicate ways in which they might be addressed.

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