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United States Department of Agriculture

Agricultural Research Service

Mitchell Schull

Research Physical Scientist

photo of Mitchell Schull
Mitchell Schull
Research Physical Scientist
USDA-ARS Hydrology and Remote Sensing Laboratory
Bldg. 007, Rm. 104, BARC-West
Beltsville, MD 20705-2350 USA
Voice: (301) 504-8554
Fax: (301) 504-8931
mitchell.schull@ars.usda.gov


Research Interests:

  • Radiative transfer modeling in vegetation.
  • Radiative effects of canopy structure from leaf to canopy scales.
  • Hyperspectral remote sensing of vegetation canopy biophysical characteristics from leaf to regional scales.
  • Monitoring of carbon, water and energy fluxes from field to regional scales using remotely sensed data.


Education:

  • 2003, B.S. Geography, University of North Dakota, Grand Forks, ND.
  • 2011, Ph.D. Geography and Environment, Boston University, Boston, MA.


Professional Experience:

  • 09/01-05/03: Research technician, Upper Midwest Aerospace Consortium, University of North Dakota, Grand Forks, ND
  • 06/03-07/04: Research Assistant, International Water Management Institute, Colombo, Sri Lanka
  • 09/05-12/10: Research Fellow, Department of Geography and Environment, Boston University, Boston, MA
  • 09/11-12/11: Lecturer, Department of Geography and Environment, Boston University, Boston, MA
  • 12/11-Present: Research Physical Scientist, USDA-ARS-Hydrology and Remote Sensing Laboratory, Beltsville, MD.


Awards:

  • 2007-2010: NASA Earth and Space Science Fellow


Professional Membership:

  • 2005-Present: American Geophysical Union
  • 2005-Present: IEEE
  • 2011-Present: American Meteorological Society


Selected Publications:(please contact the author to determine reprint availability)

( view author's publications/interpretive summaries/technical abstracts since 1999)

Schull, M.A., Knyazikhin, Y., Xu, L., Samanta, A., Latorre Carmona, P., Lepine, L., Jenkins, J.P., Ganguly, S., & Myneni, R.B. (2011). Canopy spectral invariants, Part 2: Application to classification of forest types from hyperspectral data. Journal of Quantitative Spectroscopy & Radiative Transfer, 112, 736-750.

Knyazikhin, Y., Schull, M.A., & Xu, L. (2011). Canopy spectral invariants, Part 1: A new concept in remote sensing of vegetation. Journal of Quantitative Spectroscopy & Radiative Transfer, 112, 727-735.

Ganguly, S., M.A. Schull, A. Samanta, N.V. Shabanov, C. Milesi, R. R. Nemani, Y. Knyazikhin, and R.B. Myneni (2008). Generating vegetation leaf area index earth system data record from multiple sensors. Part 1: Theory. Remote Sensing of Environment, 112, 4333-4343.

Ganguly, S., A. Samanta, M.A. Schull, N.V. Shabanov, C. Milesi, R. R. Nemani, Y. Knyazikhin, and R.B. Myneni (2008). Generating LAI Earth system data record from multiple sensors. Part 2: Implementation, analysis and validation. Remote Sensing of Environment, 112, 4318- 4332.

Schull, M.A., S. Ganguly, A. Samanta, D. Huang, J.P. Jenkins, N.V. Shabanov, J.C. Chiu, A. Marshak, J.B. Blair, R.B. Myneni, Y. Knyazikhin (2007), Physical interpretation of the correlation between multi-angle spectral data and canopy height, Geophysical research letters, vol. 34, doi:10.1029/2007GL031143.

Thenkabail, P.S., M. Schull, H. Turral (2005), Ganges and Indus river basin land use/land cover (LULC) and irrigated area mapping using continuous streams of MODIS data, Remote Sensing of Environment, 95, 317-341.

Y. Knyazikhin, M. A. Schull, P. Stenberg, M. Mottus, M. Rautiainen, Y. Yang, A. Marshak, P. Latorre Carmona, R. K. Kaufmann, P. Lewis, M. I. Disney, V. Vanderbilt, A. B. Davis, F. Baret, S. Jacquemoud, A. Lyapustin, and R. B. Myneni (2013), Hyperspectral remote sensing of foliar nitrogen content, Proceedings of the National Academy of Sciences, vol. 110, no. 3, pp. E185–E192.


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Last Modified: 1/29/2013
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