Dr Yan Zhao

Research Fellow

Centre for Crop Science
Queensland Alliance for Agriculture and Food Innovation
yan.zhao@uq.edu.au
+61 7 336 56529

Overview

Dr Yan Zhao is a dedicated researcher in the field of agricultural systems, utilizing remote sensing observations to unveil spatial and temporal patterns and advance earth observation techniques and modelling. He is an integral member of a multi-disciplinary predictive agriculture research group based at QAAFI.

Currently, Dr Zhao's focus lies in the intricate integration of spatial technologies, crop modelling, and climate forecasting systems at various scales. His primary objective is to leverage remote sensing and crop simulation techniques for a comprehensive understanding of Australia's dryland cropping system. In pursuit of this goal, he has successfully developed pipelines for handling volumetric spatial datasets and delivering crucial information on crop types, production, and phenology, spanning from local to national scales.

Engaging actively with agri-business companies, government departments, and local growers, Dr Zhao collaborates closely with stakeholders to validate and implement his research findings in practical applications.

Dr Zhao earned his Doctoral Degree in Natural Science, with a specialized focus on Cartography and Geographic Information Systems. He completed his doctoral research at the Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, in 2013.

Qualifications

  • Doctor of Philosophy of Natural Science, University of the Chinese Academy of Science

Publications

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Supervision

View all Supervision

Publications

Journal Article

Conference Publication

  • Potgieter, A. B., Camino, C., Poblete, T., Zhi, X., Reynolds-Massey-Reed, S., Zhao, Y., Belwalkar, A., Ruizhu, J., George-Jaeggli, B., Chapman, S., Jordan, D., Wu, A., Hammer, G. L. and J, Zarco-Tejada P. (2023). Advances in the study of biochemical, morphological and physiological traits of wheat and sorghum crops in australia using hyperspectral data and machine learning. 2023 IEEE International Geoscience and Remote Sensing Symposium, Pasadena, CA USA, 16-21 July 2023. Piscataway, NJ USA: Institute of Electrical and Electronics Engineers. doi: 10.1109/igarss52108.2023.10282230

  • Das, Sumanta, Massey-Reed, Sean Reynolds, Mahuika, Jenny, Watson, James, Cordova, Celso, Otto, Loren, Zhao, Yan, Chapman, Scott, George-Jaeggli, Barbara, Jordan, David, Hammer, Graeme L. and Potgieter, Andries B. (2022). A high-throughput phenotyping pipeline for rapid evaluation of morphological and physiological crop traits across large fields. IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, Kuala Lumpur, Malaysia, 17-22 July 2022. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers . doi: 10.1109/IGARSS46834.2022.9884530

  • Nguyen, Dung, Zhao, Yan, Zhang, Yifan, Huynh, Anh Ngoc-Lan, Roosta, Fred, Hammer, Graeme, Chapman, Scott and Potgieter, Andries (2022). Crop type prediction utilising a long short-term memory with a self-attention for winter crops in Australia. IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, Kuala Lumpur, Malaysia, 17-22 July 2022. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/IGARSS46834.2022.9883737

Grants (Administered at UQ)

PhD and MPhil Supervision

Note for students: Dr Yan Zhao is not currently available to take on new students.

Current Supervision

  • Doctor Philosophy — Associate Advisor

  • Doctor Philosophy — Associate Advisor

    Other advisors:

  • Doctor Philosophy — Associate Advisor

    Other advisors: