...
首页> 外文期刊>Western Journal of Applied Forestry >Evaluation of n-Tree Distance Sampling for Inventory of Headwater Riparian Forests of Western Oregon
【24h】

Evaluation of n-Tree Distance Sampling for Inventory of Headwater Riparian Forests of Western Oregon

机译:俄勒冈州西部源头河岸森林资源清查的n树距离采样评估

获取原文
获取原文并翻译 | 示例
           

摘要

n-Tree distance sampling (NTDS), also known as k-tree sampling and point-to-tree sampling, has been promoted as a practical method for forest inventory. This simulation study evaluated the performance of three NTDS estimators, as compared with fixed plot sampling and horizontal point sampling, for estimating density and basal area in headwater riparian forests of western Oregon. Bias of at least one NTDS estimator was low for both density and basal area when at least six trees were captured at each sample point, but performance of NTDS for density estimation was poor on stem maps exhibiting a clustered pattern. We close with some comments regarding the statistical efficiency of NTDS for riparian area inventory in similar forest conditions.
机译:n树距离采样(NTDS)也称为k树采样和点对树采样,已被推广为一种实用的森林资源清查方法。这项模拟研究评估了三个NTDS估计器的性能(与固定样点采样和水平点采样相比),以估计俄勒冈州西部源头河岸带森林的密度和基础面积。当在每个采样点捕获至少六棵树时,至少一个NTDS估计量的偏差在密度和基础面积上都很低,但是在显示聚类模式的茎图上,NTDS的密度估计性能很差。最后,我们对在相似森林条件下NTDS在河岸地区清查中的统计效率进行了评论。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号