Haoteng Zhao, Ph.D. Postdoctoral Research Associate USDA-ARS Hydrology and Remote Sensing Laboratory Bldg. 007, Rm. 104, BARC-West Beltsville, MD 20705-2350 USA Voice: (301) 504-7490 Fax: (301) 504-8931 Haoteng.Zhao@usda.gov

Research Interests:

• Crop condition monitoring using remote sensing imagery.
• Intelligent irrigation scheduling using land data modeling.
• Crop type mapping using machine learning models.
• Web system development for multi-senor data analysis in smart agriculture.
• Land cover and land use change detection using time-series remote sensing data.

Education:

• 2015 B.S. (Remote Sensing) Wuhan University, Wuhan, China.
• 2018 M.E. (Signal and Information Processing) University of Chinese Academy of Sciences, Beijing, China.
• 2023 Ph.D. (Earth System and Geoinformation Sciences) George Mason University, Fairfax, VA.

Professional Experience:

• 2016 - 2018: Graduate Research Assistant, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences (CAS), China.
• 2018 - 2023: Doctoral Research Assistant, Center for Spatial Information Science and Systems, George Mason University, Fairfax, VA.
• 2023 – present: Postdoctoral Fellow, USDA-ARS-Hydrology and Remote Sensing Laboratory, Beltsville, MD.

Publication Databases: 

• Google Scholar

Selected Publications: 

Zhao, H., Di, L., Sun, Z., Yu, E., Zhang, C. and Lin, L., 2022, July. Validation and Calibration of HRLDAS Soil Moisture Products in Nebraska. In 2022 10th International Conference on Agro-geoinformatics (Agro-Geoinformatics) (pp. 1-4). IEEE.

Zhao, H., Di, L., Guo, L., Zhang, C. and Lin, L., 2023. An Automated Data-Driven Irrigation Scheduling Approach Using Model Simulated Soil Moisture and Evapotranspiration. Sustainability, 15(17), p.12908.

Zhao, H., Di, L., Guo, L., Li, L., Zhang, C., Yu, E., & Li, H. (2023, July). Optimizing Irrigation Scheduling Using Deep Reinforcement Learning. In 2023 11th International Conference on Agro-Geoinformatics (Agro-Geoinformatics) (pp. 1-4). IEEE.

Zhao, H., Di, L., Yu, E., Guo, L., Li, L., Zhang, C., & Li, H. (2023, July). A Review of Scientific Irrigation Scheduling Methods. In 2023 11th International Conference on Agro-Geoinformatics (Agro-Geoinformatics) (pp. 1-4). IEEE.

Zhao, H., Di, L. and Sun, Z., 2022. WaterSmart-GIS: A Web Application of a Data Assimilation Model to Support Irrigation Research and Decision Making. ISPRS International Journal of Geo-Information, 11(5), p.271.

Zhao, H., Di, L., Sun, Z., Hao, P., Yu, E., Zhang, C. and Lin, L., 2021, July. Impacts of Soil Moisture on Crop Health: A Remote Sensing Perspective. In 2021 9th International Conference on Agro-Geoinformatics (Agro-Geoinformatics) (pp. 1-4). IEEE.

Zhao, H., Ma, Y., Chen, F., Liu, J., Jiang, L., Yao, W. and Yang, J., 2018. Monitoring quarry area with landsat long time-series for socioeconomic study. Remote Sensing, 10(4), p.517.

Zhang, C., Di, L., Lin, L., Zhao, H., Li, H., Yang, A., ... & Yang, Z. (2023). Cyberinformatics tool for in-season crop-specific land cover monitoring: Design, implementation, and applications of iCrop. Computers and Electronics in Agriculture, 213, 108199.

Zhang, C., Yang, Z., Zhao, H., Sun, Z., Di, L., Bindlish, R., Liu, P.W., Colliander, A., Mueller, R., Crow, W. and Reichle, R.H., 2022. Crop-CASMA: A web geoprocessing and map service based architecture and implementation for serving soil moisture and crop vegetation condition data over US Cropland. International Journal of Applied Earth Observation and Geoinformation, 112, p.102902.

Zhang, C., Di, L., Hao, P., Yang, Z., Lin, L., Zhao, H. and Guo, L., 2021. Rapid in-season mapping of corn and soybeans using machine-learned trusted pixels from Cropland Data Layer. International Journal of Applied Earth Observation and Geoinformation, 102, p.102374.

Yang, Z., Zhang, C., Zhao, H., Sun, Z., Bindlish, R., Liu, P.W., Colliander, A., Mueller, R., Di, L., Crow, W. and Reichle, R.H., 2021, July. Crop-CASMA-a web GIS tool for cropland soil moisture monitoring and assessment based on SMAP data. In 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS (pp. 6315-6318). IEEE.