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林业资源管理 ›› 2021, Vol. 0 ›› Issue (2): 29-35.doi: 10.13466/j.cnki.lyzygl.2021.02.005

• 实践探讨 • 上一篇    下一篇

全国森林资源调查年度出数统计方法探讨

曾伟生1(), 夏锐2   

  1. 1.国家林业和草原局调查规划设计院,北京 100714
    2.中国地质调查局自然资源综合调查指挥中心,北京 100055
  • 收稿日期:2021-01-08 修回日期:2021-01-30 出版日期:2021-04-28 发布日期:2021-06-03
  • 作者简介:曾伟生(1966-),男,湖南涟源人,教授级高工,博士,主要从事森林资源清查与林业数学建模。Email: zengweisheng0928@126.com
  • 基金资助:
    国家财政专项“森林资源监测与评价”(2130207)

Discussion on Methodology for Generating Annual Estimates in National Forest Inventory

ZENG Weisheng1(), XIA Rui2   

  1. 1. Academy of Inventory and Planning,National Forestry and Grassland Administration,Beijing 100714,China
    2. Command Center of Comprehensive Survey for Natural Resources,China Geological Survey,Beijing 100055,China
  • Received:2021-01-08 Revised:2021-01-30 Online:2021-04-28 Published:2021-06-03

摘要:

开展全国森林资源调查,实现森林覆盖率和森林蓄积量两项约束性指标年度出数,是绿色发展指标和生态文明建设目标年度评价考核的需要。基于北京市第八次和第九次森林资源连续清查1 669个样地的调查数据,按照“5年1个周期、每年完成1/5”的调查方案,采用系统抽样和随机抽样方式各抽取5套样本,分别利用联合估计方法和双重回归方法,统计产出了第1个年度的森林蓄积量估计值及其精度。结果显示,两种统计方法对北京市森林蓄积量的估计精度都能达到90%以上,以北京市第九次清查的森林蓄积量作为对比基础,联合估计结果的相对误差在-1.93%~3.73%之间,双重回归估计结果的相对误差在-2.61%~4.98%之间。研究表明:按系统抽样抽取的样本,其代表性要好于按随机抽样抽取的样本;联合估计方法和双重回归方法,均可用于产出第1个年度及后续年度的森林蓄积量数据;联合估计方法效果略好于双重回归方法,且其适用性更强;双重回归方法可作为一种近似的简易算法。

关键词: 森林蓄积量, 抽样调查, 回归模型, 联合估计, 双重回归

Abstract:

It is necessary to conduct national forest inventory and generating annual estimates of two binding targets,which are forest coverage and forest volume,for the annual examination and evaluation of green development targets and ecological civilization progress targets.Based on the data of 1 669 permanent plots of the 8th and 9th national forest inventories in Beijing,and according to the inventory plan “1/5 of plots being completed every year with a 5-year cycle”,five sets of sample plots were selected by systematic sampling and simple random sampling,respectively.The combined estimation method and double regression method were used to generate annual estimates of forest volume and the precision in the first year.The results show that the precisions of forest volume estimates from two methods are more than 90%. The study chose the 9th inventory result of forest volume in Beijing as the base for comparison and found that the relative differences are between -1.93%~3.73% for the estimates based on combined estimation method,and the those are between -2.61%~4.98% for the estimates based on double regression method.The following conclusions can be achieved:The sample plots selected by systematic sampling are more representative than those selected by simple random sampling;Both combined estimation method and double regression method could be used to generate forest volume estimates for the first year and the subsequent years;Combined estimation method is more applicable and little better than double regression method,which can be used as an approximate simple method.

Key words: forest volume, sampling survey, regression model, combined estimation, double regression

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