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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » People » Liang Sun

Liang Sun

Visiting Scientist


photo of Liang Sun Liang Sun
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
Liang.Sun@ars.usda.gov
Research Interests:
  • Remotely sensed data fusion and gap filling algorithms.
  • Soil moisture, ET mapping, and crop monitoring.

Education:

  • 2005 B.S. (Land Resources Management) China University of Geosciences, Beijing, China.
  • 2010 Ph.D. (Remote Sensing) Beijing Normal University, Beijing, China.

Professional Experience:

  • 2010-2012: Post-doctoral researcher, Global change and earth system science school, Beijing Normal University, Beijing, China.
  • 2012-2015: Research assistant, Remote sensing center, Chinese Academy of Agricultural Sciences, Beijing, China.
  • 2015-present: Post-doctoral researcher, USDA-ARS Hydrology and Remote Sensing Laboratory, Beltsville, MD.

Funded Research:

  • 2014: The National Natural Science Foundation of China "Monitoring soil moisture based on improved Land surface temperature and NDVI feature space" (3 year RMB 250K).
  • 2013: The foundation of the Key Laboratory of Agri-informatics, Ministry of Agriculture "Study on crop water cycle balance" (2 year RMB 20K).

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

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

Sun, L., Anderson, M. C., Gao, F., Hain, C., Alfieri, J. G., Sharifi, A., McCarty, G. W., Yang, Y., Yang, Y., Kustas, W. P. and McKee, L., 2017. Investigating water use over the Choptank River Watershed using a multisatellite data fusion approach, Water Resources Research., in press, doi:10.1002/2017WR020700. AGU Research Spotlight.

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

Sun, L., Gao, F., Anderson, M., Kustas, W., Alsina, M., Sanchez, L., Sams, B., McKee, L., Dulaney, W., White, W., Alfieri, J., Prueger, J., Melton, F., Post, K., 2017. Daily Mapping of 30 m LAI and NDVI for Grape Yield Prediction in California Vineyards. Remote Sensing. 9, 317. doi:10.3390/rs9040317

Sun L., Gao F., Anderson M., Dulaney W, McKee L, White W, Kustas W, Alfteri J, Prueger J., 2016. Daily mapping of Landsat-like LAI and correlation to grape yield. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 7157-7160. doi: 10.1109/IGARSS.2016.7730867

Sun, L., Liang, S., Yuan, W. and Chen, Z., 2013. Improving a Penman–Monteith evapotranspiration model by incorporating soil moisture control on soil evaporation in semiarid areas, International Journal of Digital Earth, 6(sup1), 134–156, doi:10.1080/17538947.2013.783635.

Sun L, Chen Z., 2013. Comparison of Evapotranspiration Models over different land covers. IOP Conference Series: Earth and Environmental Science 17 (1), 012128. doi: 10.1088/1755-1315/17/1/012128.

Sun L, Sun R, Li X, Liang S, Zhang R. Monitoring surface soil moisture status based on remotely sensed surface temperature and vegetation index information, Agriculture and Forest Meteorology, 2012, 166-167:175-187, doi:10.1016/j.agrformet.2012.07.015

Sun L, Sun R, Yang S, Wang W., Chen H., Li X.. 2009, Estimation of land surface evapotranspiration using MODIS data, Transactions of the Chinese Society of Agricultural Engineering, 2009, 25(Supp.2): 23-28.

Sun L, Chen Z. Estimation of regional evapotranspiration based on Penman-Monteith theory and soil moisture estimates. Transactions of the Chinese Society of Agricultural Engineering, 2013, 29 (10): 101-108.

Sun L., Sun R., Li X., et al. 2011, Estimating Evapotranspiration Using Improved Fractional Vegetation Cover and Land Surface Temperature Space, Journal of Resources and Ecology, 2(3) 289-299

Sun L, Sun R, Jia C, et al. 2008, A comparison of split window algorithm to retrieve land surface temperature from MODIS data, Journal of Beijing Normal University (Natural Science), 44 (4): 434-438. (in Chinese with English abstract)

Zhu, W., Lv, A., Jia, S., Sun, L., 2017. Development and evaluation of the MTVDI for soil moisture monitoring. Journal of Geophysical Research: Atmospheres, 122, 5533–5555. doi:10.1002/2017JD026607

Yang, Y., Anderson, M., Gao, F., Hain, C., Kustas, W., Meyers, T., Crow, W., Finocchiaro, R., Otkin, J., Sun, L., Yang, Y., 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 Journal of Selected Topics in Applied Earth Observations and Remote Sensing, in press. doi:10.1109/JSTARS.2017.2680411.

Yao, Y., Liang, S., Yu, J., Chen, J., Liu, S., Lin, Y., Fisher, J. B., McVicar, T. R., Cheng, J., Jia, K., Zhang, X., Xie, X., Jiang, B. and Sun, L., 2017. A simple temperature domain two-source model for estimating agricultural field surface energy fluxes from Landsat images, Journal of Geophysical Research: Atmospheres, 122(10), 5211–5236, doi:10.1002/2016JD026370.

Yao, Y., Liang, S., Yu, J., Zhao, S., Lin, Y., Jia, K., Zhang, X., Cheng, J., Xie, X., Sun, L., Wang, X. and Zhang, L., 2017. Differences in estimating terrestrial water flux from three satellite-based Priestley-Taylor algorithms, International Journal of Applied Earth Observation and Geoinformation, 56, 1–12, doi:10.1016/j.jag.2016.10.009.

Li, H., Chen, Z., Jiang, Z., Sun, L., Liu, K. and Liu, B., 2015. Temporal-spatial variation of evapotranspiration in the Yellow River Delta based on an integrated remote sensing model, Journal of Applied Remote Sensing, 9(1), 96047. doi:10.1117/1.JRS.9.096047.

Chen, Y., Xia, J., Liang, S., Feng, J., Fisher, J.B., Li, X., Li, X., Liu, S., Ma, Z., Miyata, A., Mu, Q., Sun, L., Tang, J., Wang, K., Wen, J., Xue, Y., Yu, G., Zha, T., Zhang, L., Zhang, Q., Zhao, T., Zhao, L., & Yuan, W. (2014). Comparison of satellite-based evapotranspiration models over terrestrial ecosystems in China. Remote Sensing of Environment, 140, 279-293, doi:10.1016/j.rse.2013.08.045.

Jiang, Z., Chen, Z., Chen, J., Liu, J., Ren, J., Li, Z., Sun, L. and Li, H., 2014. Application of Crop Model Data Assimilation With a Particle Filter for Estimating Regional Winter Wheat Yields, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7(11), 4422–4431. doi:10.1109/JSTARS.2014.2316012.

Jiang, Z., Chen, Z., Chen, J., Ren, J., Li, Z. and Sun, L., 2014. The estimation of regional crop yield using ensemble-based four-dimensional variational data assimilation, Remote Sensing, 6(4), 2664–2681, doi:10.3390/rs6042664.

Yao, Y. J., Liang, S. L., Li, X. L., Hong, Y., Fisher, J. B., Zhang, N. N., Chen, J. Q., Cheng, J., Zhao, S. H., Zhang, X. T., Jiang, B., Sun, L., Jia, K., Wang, K. C., Chen, Y., Mu, Q. Z. and Feng, F., 2014. Bayesian multimodel estimation of global terrestrial latent heat flux from eddy covariance, meteorological, and satellite observations, Journal of Geophysical Research: Atmospheres, 119(8), 4521–4545. doi: 10.1002/2013jd020864.



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