The Optimal Phenological Phase of Maize for Yield Prediction with High-Frequency UAV Remote Sensing

doi:10.3390/rs14071559

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	The Optimal Phenological Phase of Maize for Yield Prediction with High-Frequency UAV Remote Sensing
	B. Yang; W. X. Zhu; E. E. Rezaei; J. Li; Z. G. Sun and J. Q. Zhang
刊名	Remote Sensing
	2022
卷号	14 期号:7 页码:18
DOI	10.3390/rs14071559
英文摘要	Unmanned aerial vehicle (UAV)-based multispectral remote sensing effectively monitors agro-ecosystem functioning and predicts crop yield. However, the timing of the remote sensing field campaigns can profoundly impact the accuracy of yield predictions. Little is known on the effects of phenological phases on skills of high-frequency sensing observations used to predict maize yield. It is also unclear how much improvement can be gained using multi-temporal compared to mono-temporal data. We used a systematic scheme to address those gaps employing UAV multispectral observations at nine development stages of maize (from second-leaf to maturity). Next, the spectral and texture indices calculated from the mono-temporal and multi-temporal UAV images were fed into the Random Forest model for yield prediction. Our results indicated that multi-temporal UAV data could remarkably enhance the yield prediction accuracy compared with mono-temporal UAV data (R-2 increased by 8.1% and RMSE decreased by 27.4%). For single temporal UAV observation, the fourteenth-leaf stage was the earliest suitable time and the milking stage was the optimal observing time to estimate grain yield. For multi-temporal UAV data, the combination of tasseling, silking, milking, and dough stages exhibited the highest yield prediction accuracy (R-2 = 0.93, RMSE = 0.77 t center dot ha(-1)). Furthermore, we found that the Normalized Difference Red Edge Index (NDRE), Green Normalized Difference Vegetation Index (GNDVI), and dissimilarity of the near-infrared image at milking stage were the most promising feature variables for maize yield prediction.
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语种	英语
内容类型	期刊论文
源URL	[http://ir.ciomp.ac.cn/handle/181722/66950]
专题	中国科学院长春光学精密机械与物理研究所
推荐引用方式 GB/T 7714	B. Yang,W. X. Zhu,E. E. Rezaei,et al. The Optimal Phenological Phase of Maize for Yield Prediction with High-Frequency UAV Remote Sensing[J]. Remote Sensing,2022,14(7):18.
APA	B. Yang,W. X. Zhu,E. E. Rezaei,J. Li,&Z. G. Sun and J. Q. Zhang.(2022).The Optimal Phenological Phase of Maize for Yield Prediction with High-Frequency UAV Remote Sensing.Remote Sensing,14(7),18.
MLA	B. Yang,et al."The Optimal Phenological Phase of Maize for Yield Prediction with High-Frequency UAV Remote Sensing".Remote Sensing 14.7(2022):18.