A comparative analysis of georeferencing techniques for crop canopy height estimation using UAS photogrammetry

In the rapidly evolving fields of geospatial engineering and precision agriculture, the accuracy and reliability of georeferencing techniques and Uncrewed Aircraft System (UAS) methodologies are crucial for effective decision-making and crop management. This research aims to enhance UAS Structure-from-Motion (SfM) photogrammetry data quality for crop canopy height estimation in high-throughput phenotyping. The study investigates and compares the accuracy and reliability of three distinct methods used for georeferencing of the UAS imagery, which subsequently enables more accurate SfM 3D reconstruction: Global Navigation Satellite System (GNSS) without any correction aiding (GNSS-only), GNSS+Real-Time Kinematic (RTK), receiving RTK corrections from a local base station, GNSS+Real-Time Network (RTN), receiving RTK corrections from the Texas Department of Transportation (TxDOT) GNSS reference station network. The study further assesses the correlation between manually measured plant heights and those estimated from UAS-SfM point cloud data, exploring three different Digital Terrain Model (DTM) generation techniques. The research was conducted at the Texas A&M AgriLife Research and Extension Center in Corpus Christi, Texas, USA, on corn crops grown during the 2022 agricultural season. The three DTM generation methods under consideration included 1) using a DTM acquired from a flight conducted before plant emergence, 2) creating a DTM by interpolating ground height points, and 3) implementing automatic classification algorithms. Findings initially revealed that the GNSS+RTK method consistently outperformed the other georeferencing techniques, delivering more accurate results across various dates. Despite these overall trends, there were some instances where the GNSS+RTK method did not consistently outperform the other techniques. The use of one ground control point (GCP) improved georeferencing accuracy compared to scenarios with no GCPs used, while GNSS-only without correction aiding reported the least accurate results as expected. Regarding plant height estimation, the highest accuracy was generally achieved with greater canopy cover percentages, with the optimal percentage varying depending on the data collection date and DTM creation method. The highest coefficient of determination (R2) of 0.92 between manual measurements and UAS-SfM derived plant heights was found when the DTM was either interpolated from ground height points or obtained from a pre-emergence flight.