Dr. Guang Zheng is an Associate Professor of Remote Sensing at the International Institute for Earth System Science (ESSI) of Nanjing University (NJU). His researches focus on: (1) characterizing the three dimensional (3-D) forest canopy structure using the point cloud data generated by both Aerial Laser Scanning (ALS) and Terrestrial Laser Scanning (TLS) on investigating; (2) investigating the interactions and relationship between the forest canopy structure and its light environment, and physiological processes; and (3) monitoring and updating the forest aboveground biomass (AGB) by combining multi-source remotely sensed data and process-based ecological model. He got the Ph.D degree from Remote Sensing and Geospatial Analysis Laboratory (RSGAL) at University of Washington (UW), and worked closely with Precision Forestry Cooperative (PFC) directed by Dr. L. Monika Moskal to understand the canopy structure and its implications and interactions with the radiation regime and physiological processes of forest ecosystem.


Team members

Wei He (PhD student), Lixia Ma (PhD student), Xiaofei Wang (PhD student),

Xiaoman Lu (MS student), Lu Lu (MS student), Zengxin Yun (MS student),

Fanghe Zhao (Undergraduate student), Yizhen Jia (Undergraduate student)


2011  Ph.D     University of Washington (UW)

2007  M.Sc.   Nanjing University (NJU)

2004  B.E.S.   Nanjing Forestry University (NJFU)


June, 2016 - now, Visiting associate professor at the School of Environmental and Forest Sciences of University of Washington (UW)




 Tel/Fax: 86-25-8968-1031  
 Email: zhengguang@nju.edu.cn
 Room B-414, 4th floor, Kunshan Building,
 Xianlin Campus, Nanjing University

Office hour

Monday (9:00 am ~ 11:00 am) or by appoitment

Mailing address



11.Zheng, G. Ma, L.X., Eitel, J.U.H., He, W., Magney, T.S., Moskal, L.M., Li, M.S. Retrieving directional gap fraction, extinction coefficient, and effective leaf area index by incorporating scan angle information from discrete aerial laser scanning (ALS) data.doi: 10.1109/TGRS.2016.2611651. IEEE Transactions on Geoscience and Remote Sensing [in press]

10.Ma, L. X. Zheng, G., Magney, T.S., Eitel, J. U. H.,Moskal, L. M. Determining woody-to-total area ratio using terrestrial laser scanning data. Agricultural and Forest Meteorology. 228-229 (2016), 217-228.

9.Zheng, G. Ma, L.X., He, W., Eitel, J.U.H., Moskal, L.M., Zhang, Z.Y. Assessing the contribution of woody materials to forest angular gap fraction and effective leaf area index using terrestrial laser scanning (TLS) data.2016,IEEE Transactions on Geoscience and Remote Sensing. 54(3) 1475-1487

8. Ma, L.X., Zheng, G., Eitel, J.U.H., Moskal, L.M., He, W., Huang, H. B. Improved salient feature-based approach for automatically separating photosynthetic and nonphotosynthetic components within terrestrial lidar point cloud data of forest canopies.2016, IEEE Transactions on Geoscience and Remote Sensing. 54(2) 679-696.

7. Zheng, G., Moskal, L.M., Kim, S.H. Retrieval of effective leaf area index in heterogeneous forests with a terrestrial laser scanner. 2013. IEEE Transactions on Geoscience and Remote Sensing. 51(2) 777-786.

6. Zheng, G. and Moskal, L. M. Computational geometry based retrieval of effective leaf area index using terrestrial laser scanning. 2012. IEEE Transactions on Geoscience and Remote Sensing, 50(10), 3958-3969

5. Zheng, G. and Moskal, L. M. Leaf orientation retrieval from terrestrial laser scanning. 2012, IEEE Transactions on Geoscience and Remote Sensing, 50(10), 3970-3979.

4. Zheng, G. and Moskal, L.M., Spatial variability of terrestrial laser scanner based leaf area index. International Journal of Applied Observation and Geoinformation. 2012(19), 26-237

3. Moskal, L.M and Zheng, G. Retrieving forest inventory variables with terrestrial laser scanning in urban heterogeneous forest. 2012,Remote Sensing, 4, 1-20.

2. Zheng, G. and Moskal, L. M. Retrieving Leaf Area Index (LAI) Using Remote Sensing: Theories, Methods and Sensors. 2009,Sensors,9 (4):2719-2745.

1. Zheng, G., Chen, J.M., Tian, Q.J., Ju, W.M., Xia, X.Q. Combining remote sensing imagery and forest age inventory for biomass mapping. 2007, Journal of Environmental Management, 85(3) pp: 616-623.