Although simulation models of socio-spatial systems in general and agent-based models in particular represent a fantastic opportunity to explore socio-spatial behaviours and to test a variety of scenarios for public policy, the validity of generative models is uncertain unless their results are proven robust and representative of 'real-world' conditions. Sensitivity analysis usually includes the analysis of the e ect of stochasticity on the variability of results, as well as the e ects of small parameter changes. However, initial spatial conditions are usually not modified systematically in socio-spatial models, thus leaving unexplored the e ect of initial spatial arrangements on the interactions of agents with one another as well as with their environment. In this article, we present a method to assess the e ect of variation of some initial spatial conditions on simulation models, using a systematic geometric structures generator in order to create density grids with which socio-spatial simulation models are initialised. We show, with the example of two classical agent-based models (Schelling's model of segregation and Sugarscape's model of unequal societies) and a straightforward open-source workflow using high performance computing, that the e ect of initial spatial arrangements is significant on the two models. We wish to illustrate the potential interest of adding spatial sensitivity analysis during the exploration of models for both modellers and thematic specialists.

The aim of this paper is to present a model of interaction between transport and land use which aims at endogenously integrates the provision of transportation infrastructure and its effects on land use, with a long term perspective (Lowry, 1964, Wegener, 2004, Levinson, 2011, Bretagnolle, 2014, Mimeur et al., 2015). LUTECIA (Land Use, Transport, Evaluation of Cooperation, Infrastructure provision and Agglomeration effects) model puts emphasis on multiscale processes of urban growth, in the context of the emergence of Mega-City Regions (MCR, Hall & Pain, 2006). It allows us, in this exploratory phase, to characterize via simulation the conditions of development of polycentric metropolises. Nevertheless, we argue that such approaches are all the more necessary that we are in a period of multiple transitions that classical modelling tools have difficulty to capture.