Canopy Laser Interception Compensation Mechanism—UAV LiDAR Precise Monitoring Method for Cotton Height

Abstract

Plant height is a crucial phenotypic trait that plays a vital role in predicting cotton growth and yield, as well as in estimating biomass in cotton plants. The accurate estimation of canopy height from single-flight LiDAR data remains a formidable challenge in current high-density cotton cultivation patterns, where dense foliage obstructs the collection of bare soil terrain, particularly after flowering. The existing LiDAR-based methods for cotton height estimation suffer from significant errors. In this study, a new method is proposed to compensate for the canopy height estimation by using the canopy laser interception rate. The ground points are extracted by the ground filtering algorithm, and the interception rate of the laser per unit volume of the canopy is calculated to represent the canopy density and compensate for the cotton height estimation. The appropriate segmented height compensation function is determined by grouping and step-by-step analysis of the canopy laser interception rate. Verified by 440 groups of height data measured manually in the field, the results show that the canopy laser interception compensation mechanism is of great help in improving the estimation accuracy of LiDAR. R2 and RMSE reach 0.90 and 6.18 cm, respectively. Compared with the estimation method before compensation, R2 is increased by 13.92%, and RMSE is reduced by 49.31%. And when the canopy interception rate is greater than 99%, the compensation effect is more obvious, and the RMSE is reduced by 62.49%. This research result can significantly improve the height estimation accuracy of UAV-borne for high planting density cotton areas, which is helpful to improve the efficiency of cotton quality breeding and match genomics data.

Keywords

• UAV-based LiDAR
• cotton height
• phenotype extraction
• canopy laser interception compensation