The adoption of sustainably produced second generation biofuels will rely heavily on an optimized and integrated biofuel supply chain (SC) system from field to product, and a large amount of land will need to be converted to dedicated bioenergy crops to support sufficient economies of scale. Efficient models are needed to determine the optimal upstream ‘landscape design’ decisions that balance trade-offs with more commonly studied SC decisions. Landscape design optimization, deciding where in the landscape to plant bioenergy crops and how to manage that land (e.g. fertilization), has been shown to improve the environmental impact of farm-scale biomass production (including soil carbon (C) sequestration), but has been studied largely separately from biofuel SC network design (SCND). In this paper we present a model for landscape design optimization and a model/data integration strategy that enables the use of both high spatial resolution crop simulations and simultaneous optimization of the downstream biofuel SC. Using crop simulations that include realistic yield and environmental data, we present an illustrative case study in Michigan, USA and highlight the benefits of the model formulation and insights from simultaneously optimizing the SC and the landscape.