The human system’s responses to climate change and conservation policies are often spatially heterogeneous. However, traditional large-scale environmental models often lack the market linkages and spatial granularity necessary to effectively capture these vital linkages. Understanding these responses requires quantitative geospatial modeling that integrates economic and biophysical variables. However, solving these large-scale models is difficult due to high interconnectivity through markets. To address this computational challenge, this chapter explores the promising potential of SIMPLE-G as an example of gridded quantitative models that connect local decisions about land, water, and agricultural production to regional and global markets.