基于无人机可见光与激光雷达的甜菜株高定量评估

Sugar beet is the world's main sugar production crop and one of the recognized alternative materials for biofuel production. Plant height of sugar beet can be used to estimate root biomass, indicate water stress, and can also be an effective indicator of nitrogen content and yield. It is an important parameter for breeders and farm managers to assess the growth status of sugar beet in the field. The rotary-wing UAV platform has the characteristics of vertical lifting, fixed-point hovering, and strong maneuverability. It is suitable for obtaining multi-scale, multi-repeat, fixed-point, and high-resolution farmland crop information. Totally 186 genotypes of sugar beet were chosen to explore accuracy difference of estimated plant height for UAV-RGB and UAV-LiDAR system, and to do comparison with the measured value. The correlation between estimated plant height by LiDAR and measured value (straight slope was 0.99, R² was 0.88, rRMSE was 6.6%) was higher than that measured by RGB (straight slope was 0.94, R² was 0.8, rRMSE was 9%). Further stratification analysis of point clouds was carried out to compare the difference of point clouds distribution in the canopy. For the later growth stage with relative dense canopy, UAV-LiDAR can reconstruct a more complete three-dimensional canopy structure than that of UAV-RGB system.