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Unmanned aerial vehicles (UAVs) open new opportunities in precision agriculture and phenotyping because of their flexibility and low cost.

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Quantifying Lodging Percentage and Lodging Severity Using a UAV-Based Canopy Height Model Combined with an Objective Threshold Approach.

Received: 31 January 2019 Revised: 26 February 2019 Accepted: 27 February 2019 Published: 3 March 2019.

UAV unmanned aerial vehicle; GIS geographic information system; DTM digital terrain model; CHM canopy height model; ROI region of interest.

Black line represents regression line with 95 confidence interval; blue line represents 1:1 line.

Black line represents regression line with 95 confidence interval; blue line represents 1:1 line ( n 36).

LPT: lodging percentage threshold; ALS: average lodging severity; WALS: weighted average lodging severity, RMSE: root mean square error.

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