Multiple Criteria Decision Analysis (MCDA) is generally used to support planning and decision making processes, but the sharing of information is often limited by two main factors. First, many users have difficulty reading output data, especially tables, matrixes or databases. Second, the presence of many actors introduces different disciplines, knowledge, interests and languages. This paper shows the contribution that the visualization of spatial data can give to the Analytic Network Process (ANP) (Saaty, 2005; 2001; Saaty, Vargas, 2006). This study aims to use visualization techniques to create a common grammar among actors involved, and a shared basis for generating discussion. To do this we have implemented on-going research on a modelling system which is able to visualize various kinds of data in real time. This modelling system works on generative and parametric features applied to datasets, and is based on McNeelâ€™s â€œRhinocerosâ€ software and its free plug-in "Grasshopper". The starting point of the work described here is an application on a German section of Corridor 24, Genoa-Rotterdam, part of an Interreg IVB NEW Project, called â€œCode24â€. The goal of this ANP application is to rank three scenarios of improvement of the "Betuwe" railway line connecting Oberhausen to the Dutch borders. The research resulted in an academic internal application which allowed us to improve the system for use in real-world focus groups which included the main stakeholders of these territorial transformation projects.
Geo-visualization, Analytic Network Process, Dynamic Maps, Parametric and Generative Modelling
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