Yuanzhi Zhang

Positions: Professor
Academic Title: Professor
Mailing Address: Yuanzhi Zhang
Education and Career History

1982-1986, Jilin University, Geology, Changchun, China, Bachelor degree
1986-1988, Shanxi Geological Survey Bureau, Shanxi, China, Assistant Engineer
1988-1991, Graduate School of Chinese Academy of Sciences, Beijing, China, MSc
1991-1996, Chinese Academy of Sciences, Beijing, China, Assistant Researcher
1996-1997, International Institute of Aerospace and Geoinformatics, Enschede, Netherlands, MSc
1998-2005, Helsinki University of Technology, Espoo, Finland, PhD
2005-2006, University of Sherbrook, Canada, Post-doc Fellow
2006-2013, Chinese University of Hong Kong, Assistant Professor/Research Fellow
2014-date, Chinese Academy of Sciences, Beijing, China, Research Professor

Research Fields

Lunar and Planetary Remote Sensing, Environmental Remote Sensing, Mineral and rocks detection


Lunar mineral detection
Impervious surface estimation
Environmental remote sensing

Selected Publication

1.       Sun, Y., Li, L., Zhang, Y. (2017). Detection of Mg-spinel bearing central peaks using M3 images: Implications for the petrogenesis of Mg-spinel, Earth and Planetary Science Letters, 465, 48-58.
2.       Zhang, Y., Tsou, J., Huang, Z., Hu, J., Yim, W.S. (2016). Monitoring of the 2008 Chaiten eruption cloud using MODIS data and its impacts, In: Geospatial Technology – Environmental and Social Applications, (ISBN 978-953-51-2627-0), Pasquale Imperatore and Antonio Pepe (ed.): Chapter 3, pp.57-73,
3.       Zhang, Y., Huang, Z., Zhou, C., Chen, S. (2014). Bidirectional reflectance of lunar Olivine with the consideration of grain size, Earth Science Frontiers, 21 (6), 150-154.
4.      Zhang, Y., An, L., Huang, Z. (2014). The study of bidirectional reflectance feature of the Spinel based on the space weathering, Journal of Deep Space Exploration, 1(3), 210-213.
5.   Zhang, Y., Zhang, H., Lin, H. (2014). Improving the impervious surfaces estimation with combined use of optical and SAR remote sensing images, Remote Sensing of Environment, 141, 155-167.