Narendra Das
Associate Professor
Biosystems and Agricultural Engineering (BAE), College of Engineering, College of Agriculture and Natural Resources
Associate Professor - Civil and Environmental Engineering (CEE) in the College of Engineering
Farrall Hall, 524 S Shaw Ln Rm 223
Biography
Dr. Narendra N. Das is an Associate Professor with joint appointments in the Departments of Biosystems and Agricultural Engineering and Civil and Environmental Engineering. His research focuses on hydrology, microwave remote sensing, and crop modeling. Dr. Das leads the Remote Sensing for Agriculture and Hydrology Lab (RSHAL), where he collaborates with NASA satellite missions, a continuation of projects ... initiated during his tenure at NASA's Jet Propulsion Laboratory. Dr. Das is a Science Team Member of both the NASA Soil Moisture Active and Passive (SMAP) mission and the NASA ISRO SAR (NISAR) mission. In the latter role, he is responsible for producing very high-resolution global soil moisture data products. Additionally, he serves as a principal investigator (PI) for the Applied Science NASA SERVIR Program, which implements a Drought and Crop Forecast System for the East Africa region and Lower Mekong Basin countries. He is also a PI for the NASA Terrestrial Hydrology Program.
Read MoreEducation
Ph.D., Biological and Agricultural Engineering, Texas A&M University
M.S., Biological and Agricultural Engineering, Texas A&M University
B.E., Chemical Engineering, National Institute of Technology, Raipur
Awards
MSU 2022, MTRAC AgBio Innovation Challenge award to create a Low-Cost Gas Sensor for Agricultural Applications and Climate Change Studies.
JPL Voyager Award 2020 for high impact work on hydrological extreme forecasting.
NASA Achievement Award for 2019 for exceptional service toward the NASA SMAP mission.
NASA Group Achievement Award 2017 to SMAP Science and Cal/Val Team for contribution towards SMAP Algorithm and Calibration and Validation activities
... Read MorePublications
Nanda, A.1, Das N. N.3, Singh G., Bindlish R., Andreadis K., and Jayasinghe S., (2024). Harnessing SMAP Satellite Soil Moisture Product to Optimize Soil Properties to Improve Water Resource Management for Agriculture. Agriculture Water Management. vol. 300, 108918. (DOI: https://doi.org/10.1016/j.agwat.2024.108918)
Lal, P.1, Singh G., Colliander A., Entekhabi D., and Das N. N.3, (2024). Uncertainty Estimates in the NISAR High-Resolution Soil Moisture Retrievals from Multi-Scale Algorithm. Remote Sensing of Environment (in Press).
Hashemi M G.Z1, Tan P. Tan, Jalilvand E., Wilke B., Alemohammad H., and Das N. N.3, (2023). Synthetic Aperture Radar (SAR); Deep Learning; Crop Yield Prediction; XGBoost; 3D-CNNs. Submitted to Computers and Electronics in Agriculture (under review).
Hashemi M G.Z1, Tan P. Tan, Jalilvand E., Wilke B., Alemohammad H., and Das N. N.3, (2023). A Systematic Review of Synthetic Aperture Radar and Deep Learning in Agricultural Applications. Submitted to International Society for Photogrammetry and Remote Sensing (under review).
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