Contact：

https://www.researchgate.net/profile/Wanjuan_Song

Email: wjsong@mail.bnu.edu.cn

Research Interests:

Fractional Vegetation Cover (FVC)

Canopy modeling over terrain areas

Remote sensing of vegetation

DSCOVR/EPIC

Education:

2013.9 – present    Ph.D student, Cartography and GIS, School of Geography, Beijing Normal University

2009.9 - 2013.7      B.Sc., GIS, School of Geography, Beijing Normal University

Selected Publications

1、 Song, W., Knyazikhin, Y., Wen, G., Marshak, A., Mõttus, M., Yan, K., Yang, B., Xu, B., Park, T., Chen, C., Zeng, Y., Yan, G., Mu, X., & Myneni, R. (2018). Implications of Whole-Disc DSCOVR EPIC Spectral Observations for Estimating Earth’s Spectral Reflectivity Based on Low-Earth-Orbiting and Geostationary Observations.Remote Sensing, 10, 1594

2、 Mu, X., Song, W., Gao, Z., McVicar, T.R., Donohue, R.J., & Yan, G. (2018). Fractional vegetation cover estimation by using multi-angle vegetation index.Remote Sensing of Environment, 216, 44-56

3、 Knyazikhin, Y., Song, W., Yang, B., Park, T., & Myneni, R. (2018). DSCOVR EPIC Vegetation Earth System Data Record: Science Data Product Guide. In. NASA Langley ASDC

4、 Song, W., Mu, X., Ruan, G., Gao, Z., Li, L., & Yan, G. (2017). Estimating fractional vegetation cover and the vegetation index of bare soil and highly dense vegetation with a physically based method. International Journal of Applied Earth Observation and Geoinformation, 58, 168-176

5、 Mu, X., Hu, R., Zeng, Y., McVicar, T.R., Ren, H., Song, W., Wang, Y., Casa, R., Qi, J., Xie, D., & Yan, G. (2017). Estimating structural parameters of agricultural crops from ground-based multi-angular digital images with a fractional model of sun and shade components. Agricultural and Forest Meteorology, 246, 162-177

6、 Yan, G., Hu, R., Wang, Y., Ren, H., Song, W., Qi, J., & Chen, L. (2016). Scale Effect in Indirect Measurement of Leaf Area Index.IEEE Transactions on Geoscience and Remote Sensing, 54, 3475-3484

7、 Song, W., Mu, X., Yan, G., & Huang, S. (2015). Extracting the Green Fractional Vegetation Cover from Digital Images Using a Shadow-Resistant Algorithm (SHAR-LABFVC). Remote Sensing, 7, 10425

8、 Mu, X., Hu, M., Song, W., Ruan, G., Ge, Y., Wang, J., Huang, S., & Yan, G. (2015). Evaluation of Sampling Methods for Validation of Remotely Sensed Fractional Vegetation Cover.Remote Sensing, 7, 15817

9、 Mu, X., Huang, S., Ren, H., Yan, G., Song, W., & Ruan, G. (2015). Validating GEOV1 fractional vegetation cover derived from coarse-resolution remote sensing images over croplands.IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8, 439-446

Patents:

Selected Academic Awards: