Dissertation Defense Announcement for Md Mehedi Farhad – 07/25/2023 at 1:00 PM
July 17, 2023
Dissertation Title
Estimating Surface Reflectivity with Smartphone and Semi-Custom GNSS Receivers on UAS-based GNSS-R Technology and Surface Brightness Temperature using UAS-based L Band Microwave Radiometer
When
07/25/2023 1:00 PM
Where
Simrall 228
Candidate
Md Mehedi Farhad
Degree
Doctor of Philosophy in Electrical and Computer Engineering
Committee Members
Dr. Mehmet Kurum, Dr. John E. Ball, Dr. Ryan Green, Dr. Ali C. Gurbuz
Abstract
Accurate measurement of soil moisture (SM) has a significant impact on agricultural production, hydrological modeling, forestry, horticulture, waste management, and other environmental fields. Particularly in precision agriculture (PA), high spatio-temporal resolution information about surface SM is crucial. However, the use of invasive SM probes and other sensors is expensive and requires extensive manpower. Moreover, these intrusive measurement techniques provide point measurements and are unsuitable for large agricultural fields. As an alternative, this dissertation explores the remote sensing of surface SM by utilizing the surface reflectivity estimated from global navigation satellite systems – reflectometry (GNSS-R) data acquired through smartphones and off-the-shelf, cost-effective U-blox GNSS receivers. To estimate surface reflectivity, the GNSS receivers are attached underneath a small, unmanned aircraft system (UAS), which flies over agricultural fields.
Additionally, this dissertation investigates a fully custom UAS-based dual-polarized (H-pol and V-pol) L-band microwave radiometric measurement technique over agricultural areas to estimate surface brightness temperature (). The radiometer measures surface emissivity as , allowing for the estimation of surface SM while considering the detection and removal of radio frequency interference (RFI) from the radiometric measurements. This radiometer processes the data in near real-time onboard the UAS, collecting raw in-phase and quadratic (I&Q) signals across the study field. This feature mitigates the RFI onboard and significantly reduces post-processing time.
In summary, this study highlights the utilization of smartphones and semi-custom GNSS receivers in conjunction with UAS-based GNSS-R techniques and UAS-based L-band microwave radiometry for the estimation of surface reflectivity and . The radiometric measurement of surface emissivity is related to surface reflectivity through the relationship (Emissivity = 1 – Reflectivity).