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As a Graduate Research Assistant (GRA) and Summer Research Intern during my Doctoral degree studies, I have worked on research areas such as: Remote Sensing, Signal and Image Processing, Unmanned Aircraft System (UAS), Signal of Opportunity, Reflectometry, Precision Agriculture, Reflectometry, Machine Learning, and Agricultural Imaging Techniques.
As a Graduate Research Assistant (GRA) and Summer Research Intern during my Doctoral degree studies, I have worked on research areas such as: Remote Sensing, Signal and Image Processing, Unmanned Aircraft System (UAS), Signal of Opportunity, Reflectometry, Precision Agriculture, Reflectometry, Machine Learning, and Agricultural Imaging Techniques.
The Detailed Timeline of My Research Experiences are as follows:
The Detailed Timeline of My Research Experiences are as follows:
GNSS-R based Soil Moisture Retrieval from UAS Platform
GNSS-R based Soil Moisture Retrieval from UAS Platform
Employing unmanned aircraft system (UAS)-based global navigation satellite system reflectometry (GNNSS-R) technology with ancillary sensors (Multispectral Camera, LiDAR) for soil moisture (SM) estimation over selected field area: data collection and result analysis from field campaign.
Crop Yield Estimation Utilizing UAS-based Multi-Sensor Data
Crop Yield Estimation Utilizing UAS-based Multi-Sensor Data
Investigation of machine learning (ML)-based techniques for crop yield estimation of corn and cotton using multi-sensor (Multispectral Camera, LiDAR, SM Probe, Weather Station) data: Analyzing optimum feature selection and complete processing sequence.
Automatic Weed Detection from RGB Video over Crop Fields Using UAS & ML
Automatic Weed Detection from RGB Video over Crop Fields Using UAS & ML
Machine Learning (ML)-based automatic weed detection from video data captured from an RGB camera mounted on a UAS platform: Through crop line detection, vegetation and weed labeling, and weed detection by a learning algorithm.
Satellite-based Agricultural Production Modeling
Satellite-based Agricultural Production Modeling
Developing a customized and comprehensive data and analysis portal automatically integrating all relevant information for satellite-based remote sensing and agricultural research analysis around the Mississippi River basin area.
Specific tasks of agricultural production modeling through climate variables, geospatial analysis, and cropland data layer masking utilizing data extracted from satellites and USDA through advanced computing.
P-band SoOp Receiver System from UAS for RZSM Estimation
P-band SoOp Receiver System from UAS for RZSM Estimation
Implementing a signal of opportunity (SoOp) receiver system from unmanned aircraft systems (UAS) platform through the MUOS military satellite signals in the P-band frequency region for the estimation of root-zone soil moisture (RZSM).
L-band Radiometer for Passive Sensing
L-band Radiometer for Passive Sensing
Passive microwave remote sensing through cost-effective, portable L-band microwave (dual-polarized) radiometer capable of operating from an unmanned aircraft system (UAS) platform to measure high-resolution surface brightness temperature.
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