Gen*: a generic toolkit to generate spatially explicit synthetic populations |
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| Authors: | Kevin Chapuis Patrick Taillandier Misslin Renaud Alexis Drogoul |
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| Institution: | 1. UMI 209 UMMISCO, IRD/UPMC, Bondy, France;2. MIAT, University of Toulouse, INRA, Castanet-Tolosan, France;3. Identite et differenciation de l’espace de l’environnement et des societes, Université de Rouen, Mont Saint Aignan, France;4. ICTLab, USTH, VAST, Hanoi, Vietnam |
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| Abstract: | Agent-based models tend to integrate more and more data that can deeply impact their outcomes. Among these data, the ones that deal with agent attributes and localization are particularly important, but are very difficult to collect. In order to tackle this issue, we propose a complete generic toolkit called Gen* dedicated to generating spatially explicit synthetic populations from global (census and GIS) data. This article focuses on the localization methods provided by Gen* that are based on regression, geometrical constraints and spatial distributions. The toolkit is applied for a case study concerning the generation of the population of Rouen (France) and shows the capabilities of Gen* regarding population spatialization. |
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| Keywords: | Synthetic population spatialization social simulation multi-agent model |
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