Remotely Sensed Prediction of Rice Yield at Different Growth Durations Using UAV Multispectral Imagery
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Cited by:
- Jibo Yue & Chengquan Zhou & Haikuan Feng & Yanjun Yang & Ning Zhang, 2023. "Novel Applications of Optical Sensors and Machine Learning in Agricultural Monitoring," Agriculture, MDPI, vol. 13(10), pages 1-4, October.
- Bin Ma & Guangqiao Cao & Chaozhong Hu & Cong Chen, 2023. "Monitoring the Rice Panicle Blast Control Period Based on UAV Multispectral Remote Sensing and Machine Learning," Land, MDPI, vol. 12(2), pages 1-15, February.
- Li, Zhenxiao & Cheng, Qian & Chen, Zhen & Xiang, Youzhen & Hu, Xiaotao & Lazarovitch, Naftali & Zhen, Jingbo, 2025. "Estimating soil water content of cotton fields using UAV-based multi-source remote sensing data fusion," Agricultural Water Management, Elsevier, vol. 322(C).
- Shuai Bao & Yiang Wang & Shinai Ma & Huanjun Liu & Xiyu Xue & Yuxin Ma & Mingcong Zhang & Dianyao Wang, 2025. "Field-Scale Maize Yield Estimation Using Remote Sensing with the Integration of Agronomic Traits," Agriculture, MDPI, vol. 15(17), pages 1-23, August.
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