Urban Development Simulator: An interactive decision support tool for urban planners enabling citizen’s participation.

The Urban Development Simulator is currently under development within the FP7 EU project urbanAPI (2011-2014). The simulation tool is developed for the city of Ruse in remote northern Bulgaria at the Romanian border as a support for the local urban planners and politicians to evaluate high level planning decisions defined as use cases. The tool is developed as generic simulation framework, thus the framework can be applied for other cities too, to generate tailor-made urban planning support tools, if the necessary geospatial data about future planning scenarios and related statistical data describing the socio-economic state and future expectations are available. The tool enables urban planners to estimate the impact of different urban development scenarios and visualises spatial changes through dynamic GIS maps depicting the results of the simulations. It is based on the analysis of geospatial data and uses an Agent-based modelling approach to simulate the development in the city. While other urban development simulation tools usually model urban growth in the urban fringe, the Urban Development Simulator concentrates on intra-urban development, as the City of Ruse turns out as a shrinking city which is starting to recover since the last years – reorganizing the intra-urban structure. The tool has a complex user interface and a web interfaces to interact with the local citizens. Thus different planning scenarios and their effects can be visualized (also in 3D) via the web interface and the opinion of the local residents can be involved into the planning decisions by voting for selected planning decisions as preference of the citizens. The spatial pattern of the preferences serves as an input for the parameterization of the Agent-based model to simulate the development trends within the different areas of the city. Scenarios can be simulated what would be, if the urban planners would follow the citizens’ preferences. This enables the decision makers to adapt their urban development plans by considering the preferences of the citizens. Effects on e.g. the final energy demand and CO2 emissions for residential buildings are further calculated for the different development scenarios. The model runs as a Java web-start application and is hosted on a server at the AIT with remote access for the Ruse users. For the model development the simulation platform MASGISmo (Multimethod Agent-based (ABM) System dynamics (SD), GIS modelling platform) has been applied, a framework originally developed during several prior projects to combine a bottom up agent-based simulation method (ABM) with a top down – system dynamics (SD) approach. This platform is programmed in Java connected to several external tools as a PostgreSQL (PostGIS) database, Vensim a (SD) tool and uses RepastJ as core ABM tool. For the purpose of the Urban Development Simulator the GIS capability of the platform was enhanced with more powerful GIS features, thus new planning scenarios can directly be introduced within the tool by the urban planners. The paper will concentrate on the description of the structure of the Urban Development Simulator, further more explain the participatory citizen’s integration

Decision makers\u27 experience of participatory dynamic simulation modelling: Methods for public health policy

Background: Systems science methods such as dynamic simulation modelling are well suited to address questions about public health policy as they consider the complexity, context and dynamic nature of system-wide behaviours. Advances in technology have led to increased accessibility and interest in systems methods to address complex health policy issues. However, the involvement of policy decision makers in health-related simulation model development has been lacking. Where end-users have been included, there has been limited examination of their experience of the participatory modelling process and their views about the utility of the findings. This paper reports the experience of end-user decision makers, including senior public health policy makers and health service providers, who participated in three participatory simulation modelling for health policy case studies (alcohol related harm, childhood obesity prevention, diabetes in pregnancy), and their perceptions of the value and efficacy of this method in an applied health sector context. Methods: Semi-structured interviews were conducted with end-user participants from three participatory simulation modelling case studies in Australian real-world policy settings. Interviewees were employees of government agencies with jurisdiction over policy and program decisions and were purposively selected to include perspectives at different stages of model development. Results: The ‘co-production’ aspect of the participatory approach was highly valued. It was reported as an essential component of building understanding of the modelling process, and thus trust in the model and its outputs as a decision-support tool. The unique benefits of simulation modelling included its capacity to explore interactions of risk factors and combined interventions, and the impact of scaling up interventions. Participants also valued simulating new interventions prior to implementation in the real world, and the comprehensive mapping of evidence and its gaps to prioritise future research. The participatory aspect of simulation modelling was time and resource intensive and therefore most suited to high priority complex topics with contested options for intervening. Conclusion: These findings highlight the value of a participatory approach to dynamic simulation modelling to support its utility in applied health policy settings