[基于随机森林模型的自然Larix gmelinii森林中单个树木的年龄估计模型]
Xiao-Nan Wang1, Wen-Hao Su1, Ling-Bo Dong1
1Ministry of Education Key Laboratory of Sustainable Forest Ecosystem Management, School of Forestry, Northeast Forestry University, Harbin 150040, China.
概括
准确估计Larix gmelinii树的年龄对于可持续森林管理至关重要. 一个随机森林模型的性能优于阶段性回归,直径与乳房高度是最重要的预测因素.
科学领域:
- 林业林业 林业 林业 林业
- 生态生态学 生态生态学
- 量化林业 量化林业是什么
背景情况:
- 准确的个体树木年龄估计对于可持续森林管理至关重要.
- 在中国大兴安山脉的自然Larix gmelinii森林需要有效的管理策略.
研究的目的:
- 构建和评估Larix gmelinii的个体树木年龄预测模型.
- 分析影响年龄预测准确性的因素.
主要方法:
- 开发了使用逐步回归和随机森林算法的预测模型.
- 利用了44个固定地块和280个标准树核的数据.
- 使用R2,RMSE和MAE评估模型性能.
主要成果:
- 随机森林模型表现出卓越的准确性 (R2=0.5882,RMSE=9.9259,MAE=8.1155). 这是一个非常好的模型.
- 关键预测因素包括乳房高度的直径 (83.8%),树木高度 (34.4%),高度 (17.9%) 和每公基底面积 (17.5%).
- 最佳随机森林参数:1500个决策树和8个节点争议变量.
结论:
- 随机森林算法在Larix gmelinii中对个别树木年龄的预测非常有效.
- 准确的年龄估计可以改善生长和收获预测,有助于可持续森林管理.
- 结果为类似森林生态系统中树木年龄估计提供了参考.
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