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Over the past two decades, the United States government conducted detailed analyses of the potential of a biobased national energy strategy that produced four unified studies, namely the 2005–2016 US Billion-Ton Study and updates. With each effort, better perspective was gained on the biophysical potential of biomass and the economic availability of these resources on a national scale. It was also apparent that many questions remained, including crop yields, logistical operations, and systems integration across production and harvest. These reports accentuated the need for improving geospatial performance metrics for biomass supply chains. This study begins to address these problems by developing spatially specific data layers that incorporate data on soils, climatology, growth, and economics for short-rotation woody biomass plantations. Methods were developed to spatially assess the potential productivity and profitability of four candidate species Pinus taeda L., Populus deltoides W. Bartram ex Marshall and Populus hybrids, Eucalyptus grandis Hill ex Maiden, and Eucalyptus benthamii Maiden et Cambage for biomass plantations in the eastern United States. Productivity was estimated using the process-based growth model 3PG (Physiological Processes Predicting Growth) parameterized at the resolution of the United States 5-digit zip code tabulation area (ZCTA). Each ZCTA is unique in terms of species suitability, cost, and productive potential. These data layers make available dedicated energy crop analyses for practitioners interested in facility siting scenarios in conjunction with a species growth potential at a particular location. Production systems for SRWC are extremely regionalized given key biophysical and economic factors that determine the potential for acceptable growth and profitability. This analysis points to the return on invested capital being dependent on the site location of a species within its operable range. Large-scale biomass plantation systems are feasible in regions with higher potential internal rate of return. The higher the potential return, the more desirable it is to plant the specific species on the site. Increasing the available feedstock by lowering cost, increasing productivity, and stabilizing logistics would have a similar effect as higher feedstock prices. The modeled growth can be used for further economic evaluation, carbon sequestration studies, and sustainability research.