Almond canopy geometry has been shown to correlate with harvest yield, but the existing specialized and expensive equipment used to measure geometric features provides data limited in resolution and must be operated in a narrow time window, challenging its role in precise orchard management. To increase adoption, this study examines novel aerial data collection methods by small unmanned aerial systems (sUAS) and intuitive data processing methods with the goal of improving accuracy and reducing cost, time, and training required for canopy measurements and potential yield estimation.
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