Visiting Scientist
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Jie Xue, Ph.D. Research Physical Scientist USDA-ARS Hydrology and Remote Sensing Laboratory Bldg. 007, Rm. 104, BARC-West Beltsville, MD 20705-2350 USA Voice: (301) 504-7490 Fax: (301) 504-8931 Jie.Xue@usda.gov |
Research Interests:
- Spatio-temporal fusion of remote sensing data for vegetation monitoring.
- Multi-sensor thermal sharpening for evapotranspiration mapping and drought monitoring.
- Water use and productivity mapping at field scales using multi-sensor imagery.
Education:
- 2010 B.S. (Mathematics and Applied Mathematics) Chang’an University, Xi’an, China.
- 2013 M.S. (Applied Mathematics) Chang’an University, Xi’an, China.
- 2017 Ph.D. (Geography and Resource Management) The Chinese University of Hong Kong, Hong Kong, China.
Professional Experience:
- 2013-2014: Research Assistant, Department of Geography and Resource Management, The Chinese University of Hong Kong, Hong Kong, China.
- 2014-2016: Teaching Assistant, Department of Geography and Resource Management, The Chinese University of Hong Kong, Hong Kong, China.
- 2016: Visiting Student Research Collaborator, Princeton Environmental Institute, Princeton University, Princeton, NJ.
- 2016-2017: Research Assistant, Institute of Future Cities, The Chinese University of Hong Kong, Hong Kong, China.
- 2018-present: Postdoctoral Fellow, USDA-ARS Hydrology and Remote Sensing Laboratory, Beltsville, MD.
Awards:
- Graduate National Scholarship of China, 2012.
- Excellent Graduate Award of Chang’an University, 2010, 2013.
- First Class National Scholarship of China, 2008.
Selected Publications: (please contact the author to determine reprint availability)
Xue, J., Anderson, M. C., Gao, F., Hain, C., Sun, L., Yang, Y., Knipper, K. R., Kustas, W. P., Torres-Rua, A. and Schull, M. (2020) Sharpening ECOSTRESS and VIIRS land surface temperature using harmonized Landsat-Sentinel surface reflectances. (in review).
Xie, B., Zhang, H. K. and Xue, J. (2019). Deep Convolutional Neural Network for Mapping Smallholder Agriculture Using High Spatial Resolution Satellite Image. Sensors, 19(10), 2398.
Xue, J., Leung, Y., & Fung, T. (2019). An Unmixing-based Bayesian Model for Spatio-Temporal Satellite Image Fusion in Heterogeneous Landscapes. Remote Sensing, 11(3), 324.
Ying, H., Leung, Y., Cao, F., Fung, T. and Xue, J. (2018). Sparsity-based Spatiotemporal Fusion via Adaptive Multi-band Constraints. Remote Sensing, 10(10), 1646.
Xue, J., Leung, Y. and Fung, T. (2017). A Bayesian Data Fusion Approach to Spatio-temporal Fusion of Remotely Sensed Images. Remote Sensing, 9(12), 1310.
Xue, J., Leung, Y. and Ma, J. H. (2015). High-order Taylor Series Expansion Methods for Error Propagation in Geographic Information Systems. Journal of Geographical Systems, 17(2), 187-206.
Xue, J. and Ma, J. H. (2012, June). A Comparative Study of Several Taylor Expansion Methods on Error Propagation. Proceedings of the 20th International Conference on Geoinformatics, IEEE GRSS.
