From Event: SPIE Commercial + Scientific Sensing and Imaging, 2018
Field-based high-throughput phenotyping is a bottleneck to future breeding advances. The use of remote sensing with
unmanned aerial vehicles (UAVs) can change the way agricultural research operates by increasing the spatiotemporal
resolution of data collection to monitor status of plant growth. A fixed-wing UAV (Tuffwing) was operated to collect
images of a sorghum breeding research field with 70% overlap at an altitude of 120 m. The study site was located at Texas
A and M AgriLife Research’s Brazos Bottom research farm near College Station, Texas, USA. Relatively high-resolution
(>2.7cm/pixel) images were collected from May to July 2017 over 880 sorghum plots (including six treatments with four
replications). The collected images were mosaicked and structure from motion (SfM) calculated, which involves
construction of a digital surface model (DSM) by interpolation of 3D point clouds. Maximum plant height for each
genotype (plot) was estimated from the DSM and height calibration implemented with aerial measured values of groundcontrol
points with known height. Correlations and RMSE values between actual height and estimated height were
observed over sorghum across all genotypes and flight dates. Results indicate that the proposed height calibration method
has a potential for future application to improve accuracy in plant height estimations from UAVs.
Xiongzhe Han, J. Alex Thomasson, Cody Bagnall, N. Ace Pugh, David W. Horne, William L. Rooney, L. Malambo, Anjin Chang, Jinha Jung, and Dale A. Cope, "Calibrated plant height estimates with structure from motion from fixed-wing UAV images," Proc. SPIE 10664, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping III, 106640D (Presented at SPIE Commercial + Scientific Sensing and Imaging: April 16, 2018; Published: 21 May 2018); https://doi.org/10.1117/12.2305746.
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