UAV-Based Multispectral Time-Series Imagery of Biomass Sorghum — 2019
CABBI Theme: Feedstock Production
Keyword: Biomass Analytics
Varela Quintela, S., Leakey, A.D.B. May 10, 2021. “UAV-Based Multispectral Time-Series Imagery of Biomass Sorghum — 2019.” University of Illinois Urbana-Champaign. DOI: 10.13012/B2IDB-0353090_V1.
UAV-based high-resolution multispectral time-series orthophotos utilized to understand the relation between growth dynamics, imagery temporal resolution, and end-of-season biomass productivity of biomass sorghum as bioenergy crop. Sensor utilized is a RedEdge Micasense flown at 40 meters above ground level at the Energy Farm at University of Illinois Urbana-Champaign in 2019.
Varela, S., Pederson, T., Bernacchi, C.J., Leakey, A.D.B. May 1, 2021. “Understanding growth Dynamics and Yield Prediction of Sorghum Using High Temporal Resolution UAV Imagery Time Series and Machine Learning.” Remote Sensing 13 (9), 1763. DOI: 10.3390/rs13091763.
Varela, S., Pederson, T., Bernacchi, C.J., Leakey, A.D.B. Feb. 4, 2022. “Implementing Spatio-Temporal 3D-Convolution Neural Networks and UAV Time Series Imagery to Better Predict Lodging Damage in Sorghum.” Remote Sensing 14(3): 733. DOI: 10.3390/rs14030733.