Zhang Guodong, Ph.D., Master's Supervisor, graduated from Wuhan University with a degree in Photogrammetry and Remote Sensing. His research primarily focuses on quantitative vegetation remote sensing, including radiative transfer, spatiotemporal fusion, deep learning, and data assimilation. He has published over 20 papers in authoritative journals in the field, such as Remote Sensing of Environment and IEEE Transactions on Geoscience and Remote Sensing, and serves as a reviewer for journals including Remote Sensing of Environment. He leads multiple research projects, including the National Natural Science Foundation of China, the National Postdoctoral Research Fellowship Program (Category B), and the Big Earth Data in Support of the Sustainable Development Goals.

The research group maintains a harmonious atmosphere with generous research funding and rewards. The supervisor provides personal guidance with abundant paper outputs. Students interested in quantitative and ecological remote sensing are warmly welcome to apply!

Representative Publications:

1. Guodong Zhang, Gaofei Yin*, Wei Zhao, Meilian Wang, Aleixandre Verger. A deep learning method for generating gap-free FAPAR time series from Landsat data. Remote Sensing of Environment, 2025, 326:114783.

2. Guodong Zhang, Gaofei Yin*, Yi Zhang, Jiangchuan Hu, Zongyan Li, Changjing Wang, Dujuan Ma, Jiangliu Xie. An RTM-driven machine learning approach for estimating high resolution FAPAR from Landsat 5/7/8/9 surface reflectance. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2024.

3. Guodong Zhang, Shunlin Liang*, Han Ma, Tao He, Gaofei Yin, Jianglei Xu, Xiaobang Liu, Yufang Zhang. Simultaneous estimation of five temporally regular land variables at seven spatial resolutions from seven satellite data using a multi-scale and multi-depth convolutional neural network. Remote Sensing of Environment, 2024, 301:113928.

4. Guodong Zhang, Han Ma*, Shunlin Liang*, Aolin Jia, Tao He, Dongdong Wang. A machine learning method trained by radiative transfer model inversion for generating seven global land and atmospheric estimates from VIIRS top-of-atmosphere observations. Remote Sensing of Environment, 2022, 279:113132.

5. Guodong Zhang, Han Ma*, Shunlin Liang. Estimating 250-m Land Surface and Atmospheric Variables From MERSI Top-of-Atmosphere Reflectance. IEEE Transactions on Geoscience and Remote Sensing, 2021, 60:1-16.

6. Guodong Zhang, Hongmin Zhou*, Changjing Wang, Huazhu Xue, Jindi Wang, Huawei Wan. Forecasting time series albedo using NARnet based on EEMD decomposition. IEEE Transactions on Geoscience and Remote Sensing, 2020, 58(5):3544-3557.

7. Guodong Zhang, Hongmin Zhou*, Changjing Wang, Huazhu Xue*, Jindi Wang, Huawei Wan. Time series high-resolution land surface albedo estimation based on the ensemble Kalman filter algorithm. Remote Sensing, 2019, 11(7): 753.