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基于無人機可見光與激光雷達的甜菜株高定量評估
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內蒙古科技重大專項(2019ZD024)和內蒙古科技成果轉化項目(2019CG093)


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

    甜菜株高可用于估算根系生物量,、指示水分脅迫,,還可作為甜菜氮含量和產(chǎn)量的有效指示因子,是育種者和農田管理者評估大田甜菜生長狀態(tài)的重要參數(shù),。本研究以186個不同基因型的大田甜菜為研究對象,,探究無人機分別搭載可見光(RGB)相機與激光雷達(LiDAR)系統(tǒng)對大田作物株高估算的精度差異,并與田間測定值進行比較,。結果表明,,基于無人機LiDAR系統(tǒng)估算的株高與實測值的相關性高于無人機搭載RGB相機估測的相關性。進一步對點云進行分層分析,,比較點云在冠層內分布的差異,,結果表明,對于作物生長后期群體冠層封閉時,,無人機LiDAR系統(tǒng)相較于無人機搭載RGB相機系統(tǒng)能重建更為完整的冠層三維結構,。

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    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. 

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王慶,車熒璞,柴宏紅,邵科,李保國,馬韞韜.基于無人機可見光與激光雷達的甜菜株高定量評估[J].農業(yè)機械學報,2021,52(3):178-184. WANG Qing, CHE Yingpu, CHAI Honghong, SHAO Ke, LI Baoguo, MA Yuntao. Quantitative Evaluation of Sugar Beet Plant Height Based on UAV-RGB and UAV-LiDAR[J]. Transactions of the Chinese Society for Agricultural Machinery,2021,52(3):178-184.

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  • 收稿日期:2020-05-29
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  • 在線發(fā)布日期: 2021-03-10
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