Smart Urban Simulation Tools for Planning Decision Support Need Smart Data and Smart Data Gathering Methods

Urban growth is a challenge for most cities all over the world, especially in less developed countries. This tendency is calling for for smart/innovative instruments to foster sustainable urban development. Decision support for urban planning is required in order to reduce costs and resources to better accommodate new population, willing to move into urban areas. Latin American countries e.g. went from being predominantly rural to predominantly urban within a few decades, leading to high concentrations of urban population. This urban growth is expected to continue leading to severe financial stress for city budgets in order to provide the required infrastructure. AIT - Austrian Institute of Technology has been contracted by the Inter-American Development Bank (IDB) to develop a smart "Urban Infrastructure Development Simulator" (UIDS) - a tool able to performe urban growth simulation and related infrastructure cost estimations, which can be used to support urban planning decisions. In order to enable the cities to make their decisions an Agent-based simulation model has been developed representing the urban growth by estimating dwelling behaviour of the cities´ current residents and future residents coming from urban regions outside the city. The urban growth simulation tool is based on input data of different spatial and temporal resolution. Data from Geographical Information Systems (GIS), remote sensing data as well as statistical data are used to simulate scenarios for future development paths. To support the urban planning process such kind of tools need to have great flexibility concerning their data management, e.g. in providing different possibilities to import new (e.g. more accurate) data to calculate new scenarios. Beyond this common need, questions arise like: What happens if the data is not or only partially available and how might a data gathering process be supported by new tools and methods? This paper will introduce different innovative ways how urban planners might be supported to gain new data, which can be used in tools like the UIDS. The developed approaches enable urban planners to easily introduce important tacit knowledge about their city into the simulation tool. Additionally, a method will be depicted how citizens can be enabled to participate in the collection of such data. The paper will further elaborate on challenges the UIDS team encountered and on solutions to overcome these problems using data of different temporal and spatial resolution. The results depicted in this paper are based on experience gathered whithin several urban growth simulation projects performed for different regions in Europe and Latin America. Smart cities go hand in hand with evolvement and improvement of digital technology. They are a post-industrial reaction to the economic, social and political changes and challenges the world has been facing throughout the last decade - like the demographic change, the financial crisis or scarcity of resources. In cities there are plenty of players with very different tasks and interests. Many of them are trying to own the term "Smart city". There are lots of methods to achieve smartness, and there are lots of approaches to define proper smart indicators that tell us something about the smartness of a city. What are their advantages or disadvantages, which approach may claim to be the right one - and why?