相关实验视频

Updated: Jan 8, 2026

Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring
08:16

Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring

Published on: October 24, 2025

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通过集体学习结合精细的空间竞争,适应中国的最大冠宽高度

Zeyu Cui1,2, Huaiqing Zhang1,2, Yang Liu1,2

  • 1Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing, 100091, China.

Plant phenomics (Washington, D.C.)
|December 19, 2025
PubMed
概括

这项研究引入了一种新方法,可以使用空间关系和机器学习在密集森林中准确测量树木高度和树冠宽度 (HMCW). 开发的包装模型显著提高了HMCW预测的准确性,有助于森林管理.

关键词:
组合学习学习 组合学习精细的空间竞争 精细的空间竞争最大的皇冠宽度高度高度树 3D 结构现象类型参数

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