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United States Department of Agriculture

Agricultural Research Service

Yun Yang

Physical Scientist


/ARSUserFiles/51049/YunYang.jpg Yun Yang
Research Physical Scientist
USDA-ARS Hydrology and Remote Sensing Laboratory
Bldg. 007, Rm. 104, BARC-West
Beltsville, MD 20705-2350 USA
Voice: (301) 504-8354
Fax: (301) 504-8931
Yun.Yang@ars.usda.gov
Research Interests:
  • Evapotranspiration mapping for drought monitoring and water resource management.
  • Multi-sensor data fusion for improvements of spatiotemporal sampling.
  • Dissolved Organic Carbon (DOC) simulation using regional hydro-ecological models.

Education:

  • 2004 B.S. (Geography) Beijing Normal University, Beijing, China.
  • 2012 M.S. (Environmental Science) University of Massachusetts, Boston, MA.
  • 2013 Ph.D. (Environmental Science) University of Massachusetts, Boston, MA.

Professional Experience:

  • 2011-2013: Doctoral Research Assistant, School for the Environment, University of Massachusetts, Boston, MA.
  • 2013-2014: Postdoctoral Research Assistant, School for the Environment, University of Massachusetts, Boston, MA.
  • 2014-present: Postdoctoral Fellow, USDA-ARS-Hydrology and Remote Sensing Laboratory, Beltsville, MD.

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

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

Wang, Z., Erb, A. M., Schaaf, C. B., Sun, Q., Liu, Y., Yang, Y., Shuai, Y., Casey, K. A. and Román, M. O.: Early spring post-fire snow albedo dynamics in high latitude boreal forests using Landsat-8 OLI data, Remote Sens. Environ., 2016.

Gao, F., Hilker, T., Zhu, X., Anderson, M., Masek, J., Wang, P. and Yang, Y.: Fusing Landsat and MODIS data for vegetation monitoring, IEEE Geosci. Remote Sens. Mag., 3(3), 47–60, 2015.

Semmens, K. A., Anderson, M. C., Kustas, W. P., Gao, F., Alfieri, J. G., McKee, L., Prueger, J. H., Hain, C. R., Cammalleri, C. and Yang, Y.: Monitoring daily evapotranspiration over two California vineyards using Landsat 8 in a multi-sensor data fusion approach, Remote Sens. Environ., 2015.

Tenenbaum, D. E., Yang, Y. and Zhou, W.: A comparison of object-oriented image classification and transect sampling methods for obtaining land cover information from digital orthophotography, GIScience Remote Sens., 48(1), 112–129, 2011.



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Last Modified: 12/5/2016
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