Dynamic UAV data fusion and deep learning for improved maize phenological-stage tracking

Dynamic UAV data fusion and deep learning for improved maize phenological-stage tracking

Near real–time maize phenology monitoring is crucial for field management, cropping system adjustments, and yield estimation. Most phenological monitoring methods are post–seasonal and heavily rely on high–frequency time–series data. These methods are not applicable on the unmanned aerial vehicle (U...

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Bibliographic Details
Main Authors: Ziheng Feng, Jiliang Zhao, Liunan Suo, Heguang Sun, Huiling Long, Hao Yang, Xiaoyu Song, Haikuan Feng, Bo Xu, Guijun Yang, Chunjiang Zhao
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2025-06-01
Series:Crop Journal
Subjects:
Near real-time
Maize phenology
Deep learning
UAV
Multi-source data fusion
Online Access:http://www.sciencedirect.com/science/article/pii/S2214514125000935
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http://www.sciencedirect.com/science/article/pii/S2214514125000935

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