Assessing Within-Field Variation in Alfalfa Leaf Area Index Using UAV Visible Vegetation Indices
2023
Keegan Hammond | Ruth Kerry | Ryan R. Jensen | Ross Spackman | April Hulet | Bryan G. Hopkins | Matt A. Yost | Austin P. Hopkins | Neil C. Hansen
This study examines the use of leaf area index (LAI) to inform variable-rate irrigation (VRI) for irrigated alfalfa (Medicago sativa). LAI is useful for predicting zone-specific evapotranspiration (ETc). One approach toward estimating LAI is to utilize the relationship between LAI and visible vegetation indices (VVIs) using unmanned aerial vehicle (UAV) imagery. This research has three objectives: (1) to measure and describe the within-field variation in LAI and canopy height for an irrigated alfalfa field, (2) to evaluate the relationships between the alfalfa LAI and various VVIs with and without field average canopy height, and (3) to use UAV images and field average canopy height to describe the within-field variation in LAI and the potential application to VRI. The study was conducted in 2021&ndash:2022 in Rexburg, Idaho. Over the course of the study, the measured LAI varied from 0.23 m2 m&minus:2 to 11.28 m2 m&minus:2 and canopy height varied from 6 cm to 65 cm. There was strong spatial clustering in the measured LAI but the spatial patterns were dynamic between dates. Among eleven VVIs evaluated, the four that combined green and red wavelengths but excluded blue wavelengths showed the most promise. For all VVIs, adding average canopy height to multiple linear regression improved LAI prediction. The regression model using the modified green&ndash:red vegetation index (MGRVI) and canopy height (R2 = 0.93) was applied to describe the spatial variation in the LAI among VRI zones. There were significant (p <: 0.05) but not practical differences (<:15%) between pre-defined zones. UAV imagery coupled with field average canopy height can be a useful tool for predicting LAI in alfalfa.
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