BioSAT Publications
Refereed Journals
Huang, X. J.H. Perdue and T.M. Young. 2012. A spatial index for identifying opportunity zones for woody cellulosic conversion facilities. International Journal of Forestry Research. 2012:1-11. doi:10.1155/2012/106474
Young, T.M., R.L. Zaretski, J.H. Perdue, F.M. Guess, and X. Liu. 2011. Logistic regression models of factors influencing the location of bioenergy and biofuels plants. BioResources. 6(1):329-343. [1.418 IF (2010)]
Proceedings
Young, T.M., J.H. Perdue, A.J. Hartsell, and T.G. Rials. 2011. An economic assessment for biomass in the Southern U.S. using the biomass site assessment tool (BioSAT). In Woody Biomass Utilization: Proceedings of the International Conference on Woody Biomass Utilization, Starkville, MS, August 4-5. 2009. pp. 93-107. Edited by John R. Shelly, Forest Products Society, Madison, WI. ISBN-13:978-1-892529-60-2.
Young, T.M., A.J. Hartsell, J.H. Perdue, D.G. Hodges, R.C. Abt, and T.G. Rials. 2009. A real-time, web-based optimal biomass site assessment tool (BioSAT) – An economic assessment of biomass for the 33 eastern United States. Proc. International Conference on Woody Biomass Utilization. Mississippi State University. Starkville, MS. In Press.
Young, T.M., J.H. Perdue, A. Hartsell, D.G. Hodges and T.G Rials. 2008. Optimal siting for biorefineries using the Biomass Siting Analysis Tool (BioSAT). 2008 Forest Inventory and Analysis Symposium. Oct. 21-23. Park City, UT. USDA Forest Service Proceedings – RMRS-P-56. 42:1-22. http://www.treesearch.fs.fed.us/pubs/33326.
Final Reports
Perdue, J.H., T.M. Young, and T.G. Rials. 2011. The Biomass Site Assessment Tool – BioSAT. Final Report for U.S. Forest Service, Southern Research Station submitted by The University of Tennessee, Knoxville. 282p.
Hodges, D.G., T.M. Young, R.C. Abt, A.J. Hartsell, and J.H. Perdue. 2009. Regional comparative advantage for woody biofuels production. Final Report for US DOT Southeastern Sun Grant Center. The University of Tennessee, Knoxville. 167p.
M.S. Theses
Huang, X. 2010. Bayesian logistic regression models for siting biomass-using facilities. M.S. Thesis. The University of Tennessee. Knoxville. 149p.
Liu, X. 2009. A statistical analysis of key factors influencing the location of biomass-using facilities. M.S. Thesis. The University of Tennessee. Knoxville. 106p. http://trace.tennessee.edu/utk_gradthes/539
Wang, Yingjin. 2008. Comparing linear discriminant analysis with classification trees using forest landowner survey data as a case study with considerations for optimal biorefinery siting. M.S. Thesis. The University of Tennessee. Knoxville. 114p. http://trace.tennessee.edu/utk_gradthes/679
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Updated on 04/26/2012
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