Tobacco yield estimation via multi-source data fusion and recurrent neural networks

In China, tobacco production must strictly follow the yield plan set by the higher authorities. In this context, accurate and stable yield estimation is meaningful for effective production management. In this paper, we adopted a multi-source data fusion strategy to develop the yield estimation model...

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Bibliographic Details

Published in:	International journal of applied earth observation and geoinformation Vol. 144; p. 104925
Main Authors:	Zhang, Mingzheng, Zhang, Baoyuan, Zhao, Chunjiang, Chen, Liping, Kuai, Yan, Wang, Cong, Jiang, Shuwen, Chen, Dong, Zhu, Qingzhen, Wang, Zhiyong, Gu, Xiaohe, Chen, Tian’en
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01.11.2025 Elsevier
Subjects:	AEC1D HF+BCP+BPP Multi-source data fusion RNN Yield estimation RNN Yield estimation HF+BCP+BPP AEC1D Multi-source data fusion
ISSN:	1569-8432
Online Access:	Get full text
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