Dipankar Mandal, Ph.D.

Postdoctoral Fellow,

Kansas State University, USA

Dr. Dipankar Mandal received the B.Tech. degree in agricultural engineering from Bidhan Chandra Krishi Viswavidyalaya, India, in 2015, and the M.Tech + Ph.D. dual degree in geoinformatics and natural resources engineering from the Centre of Studies in Resources Engineering, Indian Institute of Technology Bombay, Mumbai, India, in 2020. He was a Visiting Researcher with the Agriculture and Agri-Food Canada (AAFC), Ottawa, ON, Canada, and Carleton University, Ottawa, ON, Canada, from October 2018 to February 2019. As a Visiting Researcher, he contributed to synthetic aperture radar (SAR) intercomparison experiment for crop biophysical parameter estimation within the Joint Experiment for Crop Assessment and Monitoring (JECAM) network of GEO Global Agricultural Monitoring. His research interests include applications of SAR polarimetry for crop classification, vegetation biophysical parameter estimation, deriving radar vegetation indices, and yield forecasting. Dr. Mandal was a recipient of the Shastri Research Student Fellowship Award by the Shastri Indo–Canadian Institute, India, from 2018 to 2019. He was the recipient of the IEEE Geoscience and Remote Sensing Society India Best Ph.D. thesis award, in 2020, and the ‘Excellence in Ph.D. Research’ from Indian Institute of Technology Bombay, in 2021, for his doctoral work entitled “Retrieval of Biophysical Parameters for Agricultural Crops using Polarimetric SAR Data” and outstanding contribution toward improvement of diverse techniques for agricultural applications utilizing synthetic aperture radar remote sensing data. Currently, Dr. Mandal is a Postdoctoral Fellow at Department of Agronomy, Kansas State University. His research interest includes precision agriculture and remote sensing for agricultural applications.

The main goal of my research is to understand how crop canopy interacts with radar signals by using both Synthetic Aperture Radar (SAR) remote sensing and physical scattering models. Combining remote sensing observations and the models is my approach to understand crop dynamics.

For me, the key question is how to relate crop dynamics for better prediction of yield within a crop season, especially during the Indian monsoon? In our lab, we are trying to tackle these challenges with the concepts of SAR polarimetry and crop simulations through different field campaigns and SAR observables. We believe that the SAR has a high potential for agricultural crop monitoring along with the optical sensors. "And this is just the beginning; we have not even scratched the surface".