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林业资源管理 ›› 2022›› Issue (6): 76-81.doi: 10.13466/j.cnki.lyzygl.2022.06.012

• 科学研究 • 上一篇    下一篇

森林资源监测地面固定样地优化研究

阳帆(), 白星雯   

  1. 国家林业和草原局林草调查规划院,北京 100714
  • 收稿日期:2022-10-09 修回日期:2022-11-11 出版日期:2022-12-28 发布日期:2023-01-16
  • 作者简介:阳帆(1992-),男,湖南人,工程师,博士,主要从事森林资源监测及经营管理研究与实践工作。Email:yang2170057@163.com

Optimization of Fixed Ground Plots for Forest Resource Monitoring

YANG Fan(), BAI Xingwen   

  1. Academy of Forestry Inventory and Planning,National Forestry and Grassland Administration,Beijing 100714,China
  • Received:2022-10-09 Revised:2022-11-11 Online:2022-12-28 Published:2023-01-16

摘要:

地面固定样地是大区域尺度范围内开展森林资源监测的基本抽样调查单元。地面固定样地对林分的预估精度将直接影响到整体区域监测结果的准确性。从样地类型、空间排列方式、样地尺度大小出发,在1 hm2大样地中采用随机抽样法,通过抽样精度验证在不同类型林分中开展森林资源监测的最优样地类型。结果表明:1)在不同类型林分中开展蓄积量监测的最优样地面积尺度大小不一,在布设地面固定样地时,应当根据林分起源、龄组的不同,确定样地面积、间距;2)在样地面积相同情况下,单一圆形样地抽样监测精度略高于单一方形样地,群团样地的蓄积抽样监测精度明显高于单一样地,四点圆形群团样地抽样监测精度略高于方阵式群团样地。

关键词: 森林资源监测, 地面固定样地, 抽样精度, 群团样地

Abstract:

The ground fixed sample plot is a basic sampling unit for forest resource monitoring in a large regional scale.The prediction accuracy of ground fixed sample will directly affect the accuracy of the overall regional monitoring results.Based on the sample type,spatial arrangement and size of the sample plot,random sampling method was adopted in a 1 hm2 area plot to verify the optimal sample type of forest resources monitoring in different types of stands by sampling accuracy.The results showed that: 1) The optimal plot area scales for stock monitoring in different stand types were different.When laying ground fixed plots,the plot area and spacing should be determined according to the origin and age group of the stand.2) Under the condition that the sample area was the same,the sampling monitoring accuracy of the single round sample was slightly higher than that of the single square sample,the accumulation sampling monitoring accuracy of the cluster sample was obviously higher than that of the single cluster sample,and the sampling monitoring accuracy of the four-point round cluster sample was slightly higher than that of the square cluster sample.

Key words: forest resource monitoring, fixed ground plots, sampling accuracy, cluster plots

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