He received his B.S. degree from the School of Remote Sensing and Information Engineering, Wuhan University, China, in 2015. He then obtained his M.S. degree in 2017 and Ph.D. degree in 2021, both from the State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing (LIESMARS), Wuhan University, China.

He is currently an Assistant Researcher at the Key Laboratory of Remote Sensing and Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences. He is also a member of the global agricultural remote sensing monitoring team (CropWatch) of China.

 Intelligent interpretation of remote sensing imagery, transfer learning, and agricultural remote sensing

[1] Qin, X., Wu, B., Zeng, H., Zhang, M., and Tian, F.: Global Gridded Crop Production Dataset at 10 km Resolution from 2010 to 2020, Sci Data, 11, 1377, https://doi.org/10.1038/s41597-024-04248-2, 2024b.

[2] Qin, X., Zhao, L., Yang, J., Li, P., Zeng, H., Zhang, M., and Sun, K.: Mitigating Incidence Angle Effects in Airborne SAR Time-Series Crop Classification: Integrating Transfer Learning and Variational Mode Decomposition, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 17, 14502–14520, https://doi.org/10.1109/JSTARS.2024.3438762, 2024c.

[3] Wu, B., Zhang, M., Zeng, H., Tian, F., Potgieter, A. B., Qin, X., et.al.: Challenges and opportunities in remote sensing-based crop monitoring: a review, National Science Review, 10, nwac290, https://doi.org/10.1093/nsr/nwac290, 2023.

[4] Qin, X., Wu, B., Zeng, H., Zhang, M., Tian, F., Cao, Y., and Liu, Y.: An Object-Level Multi-Source Transfer Learning Method Integrating Optical and SAR Features: A Case Study of Gaofen, Ziyuan, and Sentinel-1 Satellites, in: IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, 6978–6981, https://doi.org/10.1109/IGARSS53475.2024.10642882, 2024a.

[5] Qin, X., Yang, J., Li, P., Sun, W., and Liu, W.: A Novel Relational-Based Transductive Transfer Learning Method for PolSAR Images via Time-Series Clustering, Remote Sensing, 11, 1358, https://doi.org/10.3390/rs11111358, 2019.