Mapping sugarcane sucrose quality dynamics: A systematic review of multi-temporal sensing, data fusion, and Geo-AI frameworks

Computers and Electronics in Agriculture2月1日 · 周一阅读 0

核心看点

系统综述梳理多时相遥感、数据融合与Geo-AI在甘蔗蔗糖品质监测中的框架，方法学参考价值明确，但属综述类、无新数据，且出版日期在未来，时效性为零。

关注点

该综述整合多时相遥感与Geo-AI框架用于甘蔗蔗糖品质动态监测，可为作物品质遥感建模选型提供方法参考，但结论依赖既有文献，缺乏原始验证数据。

论文信息

Chirag R. Desai / Sonali A. Patil / Nandakumar Kunchge

Computers and Electronics in Agriculture

DOI: 10.1016/j.compag.2026.112604

论文摘要

Mapping sugarcane sucrose quality dynamics: A systematic review of multi-temporal sensing, data fusion, and Geo-AI frameworks。Computers and Electronics in Agriculture

论文原文与出版信息

Computers and Electronics in Agriculture

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智慧农业甘蔗数据融合 Geo-AI

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