Developing Novel Rice Yield Index Using UAV Remote Sensing Imagery Fusion Technology

نویسندگان

چکیده

Efficient and quick yield prediction is of great significance for ensuring world food security crop breeding research. The rapid development unmanned aerial vehicle (UAV) technology makes it more timely accurate to monitor crops by remote sensing. objective this study was explore the method developing a novel index (YI) with wide adaptability fusing vegetation indices (VIs), color (CIs), texture (TIs) from UAV-based imagery. Six field experiments 24 varieties rice 21 fertilization methods were carried out in three experimental stations 2019 2020. multispectral RGB images canopy collected UAV platform used rebuild six new VIs TIs. performance VI-based YI (MAPE = 13.98%) developed quadratic nonlinear regression at maturity stage better than other stages, outperformed that CI-based 22.21%) TI-based 18.60%). Then VIs, CIs, TIs fused build multiple linear random forest models. Compared heading (R2 0.78, MAPE 9.72%) all 0.59, 22.21%), best + CIs 0.84, 7.86%). Our findings suggest proposed has potential monitoring.

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ژورنال

عنوان ژورنال: Drones

سال: 2022

ISSN: ['2504-446X']

DOI: https://doi.org/10.3390/drones6060151