The need to reduce the use of chemical inputs in agricultural ecosystems requires studying integrated ecological processes and developing new tools helping to manage them. In particular, designing landscape management strategies is a new way to improve the efficiency of services provided by biodiversity as biological control or pollination. Individual-based models are useful to better understand how pests and predatory or pollinator insects interact with agricultural landscapes and to study the potential effects of habitat management strategies. We developed an individual-based model simulating the dynamics of an agricultural landscape from GIS data, taking into account crop rotations and crop phenology which have an important impact on the life cycles of populations of insects. The spatiotemporal stochasticity is simulated using typical land-cover rotations applied by farmers and crop phenology directly set by the user according to his needs. Spatiotemporal patterns are calculated from an initial real agricultural landscape and plausible land-cover rotations. We used the Gama simulation platform which has strong built-in functions for spatial data treatment and aggregated population dynamics. The landscape model was applied to a case-study located in a long term social ecological research site in southwestern France. We describe the characteristics of the model and present some outputs in terms of visualization, spatio-temporal crop dynamics and possible uses in relation with ecological studies. This model is built to be applicable to any agricultural landscape and to be linked to almost any population dynamics.