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基于无人机可见光与激光雷达的甜菜株高定量评估

Quantitative Evaluation of Sugar Beet Plant Height Based on UAV-RGB and UAV-LiDAR

  • 摘要: 甜菜株高可用于估算根系生物量、指示水分胁迫,还可作为甜菜氮含量和产量的有效指示因子,是育种者和农田管理者评估大田甜菜生长状态的重要参数。本研究以186个不同基因型的大田甜菜为研究对象,探究无人机分别搭载可见光(RGB)相机与激光雷达(Li DAR)系统对大田作物株高估算的精度差异,并与田间测定值进行比较。结果表明,基于无人机Li DAR系统估算的株高与实测值的相关性高于无人机搭载RGB相机估测的相关性。进一步对点云进行分层分析,比较点云在冠层内分布的差异,结果表明,对于作物生长后期群体冠层封闭时,无人机Li DAR系统相较于无人机搭载RGB相机系统能重建更为完整的冠层三维结构。

     

    Abstract: 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-Li DAR system,and to do comparison with the measured value. The correlation between estimated plant height by Li DAR and measured value( straight slope was 0. 99,R~2 was 0. 88,rRMSE was 6. 6%) was higher than that measured by RGB( straight slope was 0. 94,R~2 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-Li DAR can reconstruct a more complete three-dimensional canopy structure than that of UAV-RGB system.

     

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