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Yun Yang

Physical Scientist


 /ARSUserFiles/51049/Yun_photo.jpg Yun Yang, Ph.D.
Research Physical Scientist
USDA-ARS Hydrology and Remote Sensing Laboratory
Bldg. 007, Rm. 104, BARC-West
Beltsville, MD 20705 USA
Voice: (301) 504-8354
Fax: (301) 504-8931
Yun.Yang@ars.usda.gov

 

Research Interests:


Education:


Professional Experience:


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

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

Castelli, M., M. Anderson, Yang, G. Wohlfahrt, G. Bertoldi, G. Niedrist, A. Hammerle, P. Zhao, M. Zebisch and C. Notarnicola (2018), Two-source energy balance modeling of evapotranspiration in Alpine grasslands, Remote Sensing of Environment, accepted.

Y., M. Anderson, F. Gao, B. Wardlow, C. Hain, J. Otkin, J. Alfieri, Y. Yang, L. Sun and W. Dulaney (2018), Field-scale mapping of evaporative stress indicators of crop yield: an application over Mead, NE, USA, Remote Sensing of Environment, accepted.

Wang, Z., C. Schaaf., Q. Sun, J. Kim, A. Erb, F. Gao, M. Román, Yang, S. Petroy, J. Taylor, and J. Masek (2017), Monitoring land surface albedo and vegetation dynamics using high spatial and temporal resolution synthetic time series from Landsat and the MODIS BRDF/NBAR/albedo product, Int. J. Appl. Earth Obs. Geoinf., 59, 104–117, doi:10.1016/j.jag.2017.03.008.

Yang, Y., M. Anderson, F. Gao, C. Hain, W. Kustas, T. Meyers, W. Crow, R. Finocchiaro, J. Otkin, and L. Sun (2017), Impact of Tile Drainage on Evapotranspiration in South Dakota, USA, Based on High Spatiotemporal Resolution Evapotranspiration Time Series From a Multisatellite Data Fusion System, IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., 10(6), 2550–2564, doi:10.1109/JSTARS.2017.2680411.

Yang, Y., C. Anderson, F. Gao, C. R. Hain, K. A. Semmens, W. P. Kustas, A. Noormets, R. H. Wynne, V. A. Thomas, and G. Sun (2017), Daily Landsat-scale evapotranspiration estimation over a forested landscape in North Carolina, USA using multi-satellite data fusion, Hydrol. Earth Syst. Sci., 21, 1017–1037, doi:doi:10.5194/hess-21-1017-2017.

Sun, L., M. C. Anderson, F. Gao, C. Hain, J. G. Alfieri, A. Sharifi, G. W. McCarty, Yang, Y. Yang, and W. P. Kustas (2017), Investigating water use over the Choptank River Watershed using a multisatellite data fusion approach, Water Resour. Res., doi:10.1002/2017WR020700.

Sun, L., Z. Chen, F. Gao, M. Anderson, L. Song, L. Wang, B. Hu, and Yang (2017), Reconstructing daily clear-sky land surface temperature for cloudy regions from MODIS data, Comput. Geosci., 105, 10–20, doi:10.1016/j.cageo.2017.04.007.

Semmens, K. A., M. C. Anderson, W. P. Kustas, F. Gao, J. G. Alfieri, L. McKee, J. H. Prueger, C. R. Hain, C. Cammalleri, Yang and T. Xia (2016), Monitoring daily evapotranspiration over two California vineyards using Landsat 8 in a multi-sensor data fusion approach, Remote Sens. Environ., 185, 155–170.

Wang, Z., A. M. Erb, C. B. Schaaf, Q. Sun, Y. Liu, Yang, Y. Shuai, K. A. Casey, and M. O. Román (2016), Early spring post-fire snow albedo dynamics in high latitude boreal forests using Landsat-8 OLI data, Remote Sens. Environ.,185

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

Tenenbaum, D. E., Yang, and W. Zhou (2011), 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.

Wang, J., W. Ding, B. Fradkin, C. H. Pham, P. Sherman, B. D. Tran, D. Wang, Yang, and T. F. Stepinski (2010), Effective classification for crater detection: A case study on Mars, in Cognitive Informatics (ICCI), 2010 9th IEEE International Conference on, pp. 688–695, IEEE.

 

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