长期从事地表通量遥感反演模型开发、模型和产品不确定性评价、高时空分辨率蒸散的遥感反演、农业干旱灾害监测和预警方面的基础理论和应用研究，在遥感领域有影响力的国际一流期刊已发表论文10余篇。 

学习经历

University of Wisconsin – Madison    Ph.D   2015

中国科学院地理科学与自然资源研究所 硕士 2009

北京师范大学 学士 2006

工作经历

USDA ARS Hydrology and Remote Sensing Laboratory

获奖情况

Best Speaker of 2019, USDA Agricultural Research Center Toastmaster Club, 2019

Roy F. Weston Graduate Fellowship in Sustainability Studies, UW - Madison, 2014

Vilas Research Travel Award, UW - Madison, 2014

Nelson Institute Student Travel Grant, UW - Madison, 2010

优秀学生干部，中国科学院地理科学与资源研究所, 2007-2008

三好学生，中国科学院地理科学与资源研究所, 2006-2007

优秀团干部，北京师范大学，2003-2004

优秀学生干部，北京师范大学，2002-2003

学术兼职

Academic Part-time Jobs

高精度高时空分辨率的蒸散估算，农作物估产/旱情监测，多元遥感数据融合，热红外遥感。

1.NASA New Investigator Program in Earth Science: Leveraging Information Theory and Flux Tower Footprints Towards Improved Satellite-Based Evapotranspiration Estimates

2.NSF Prediction of and Resilience against Extreme Events Collaborative Research: Flash droughts: process, prediction, and the central role of vegetation in their evolution

3.NASA ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) Earth Ventures Instrument

4.NASA ROSES Characterizing Field-Scale Water Use, Phenology and Productivity in Agricultural Landscapes using Multi-Sensor Data Fusion.

5.NASA's Land Cover and Land Use Change (LCLUC) Investigating the Relationship Between Land Use/Land Cover Change, Hydrologic Cycle, and Climate in Semi-Arid Central Asia.

1.Yang, Y., Anderson, M., Gao, F., Johnson, D., Yang, Y., Sun, L., Dulaney, W., Hain, C., Otkin, J., Prueger, J.,Meyers, T., Bernacchi, C., Moore, C.,2021. Phenological corrections to a field-scale, ET-based crop stress indicator: An application to yield forecasting across the U.S. Corn Belt. Remote Sensing of Environment, 257, p. 112337.

2.Anderson, M.C., Yang, Y., Xue, J., Knipper, K.R., Yang, Y., Gao, F., Hain, C.R., Kustas, W.P., Cawse-Nicholson, K., Hulley, G. and Fisher, J.B., 2021. Interoperability of ECOSTRESS and Landsat for mapping evapotranspiration time series at sub-field scales. Remote Sensing of Environment, 252, p.112189.

3.Zhang, C., Long, D., Zhang, Y., Anderson, M.C., Kustas, W.P. and Yang, Y., 2021. A decadal (2008–2017) daily evapotranspiration data set of 1 km spatial resolution and spatial completeness across the North China Plain using TSEB and data fusion. Remote Sensing of Environment, 262, p.112519.

4.Kang Y., Ozdogan M., Gao F., Anderson M., White W., Yang Y., Yang Y., Erickson T., 2021.A data-driven approach to estimate leaf area index for Landsat images over the contiguous US. Remote Sensing of Environment, 258, p.112383.
Sun, L., Gao, F., Xie, D., Anderson, M., Chen, R., Yang, Y., Yang, Y. and Chen, Z., 2021.

5.Reconstructing daily 30 m NDVI over complex agricultural landscapes using a crop reference curve approach. Remote Sensing of Environment, 253, p.112156.

6.Song, L., Bian, Z., Kustas, W.P., Liu, S., Xiao, Q., Nieto, H., Xu, Z., Yang, Y., Xu, T. and Han, X., 2020. Estimation of surface heat fluxes using multi-angular observations of radiative surface temperature. Remote Sensing of Environment, 239, p.111674.

7.Yang, Y., Anderson, M.C., Gao, F., Wardlow, B., Hain, C.R., Otkin, J.A., Alfieri, J., Yang, Y., Sun, L. and Dulaney, W., 2018. Field-scale mapping of evaporative stress indicators of crop yield: An application over Mead, NE, USA. Remote Sensing of Environment, 210, pp.387-402.

8.Song, L., Liu, S., Kustas, W.P., Nieto, H., Sun, L., Xu, Z., Skaggs, T.H., Yang, Y., Ma, M., Xu, T. and Tang, X., 2018. Monitoring and validating spatially and temporally continuous daily evaporation and transpiration at river basin scale. Remote Sensing of Environment, 219, pp.72-88.

9.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 C hoptank R iver W atershed using a multisatellite data fusion approach. Water Resources Research, 53, pp.5298-5319.

10.Yang, Y., Anderson, M., Gao, F., Yang, Y. and Sun, L., 2016, July. Study of water use in agricultural landscapes at high spatiotemporal resulotion. In 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) (pp. 7172-7175). IEEE.

11.Ozdogan M., Yang Y., Allez G. and Cervantes C. 2010. Remote Sensing of Irrigated Agriculture: Opportunities and Challenges. Remote Sensing 2: 2274-2304.