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...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	International journal of applied earth observation and geoinformation Jg. 144; S. 104925
Hauptverfasser:	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
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.11.2025 Elsevier
Schlagworte:	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-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!