Application of Spatial Balanced Sampling on forest resources inventory

机译：空间均衡抽样在森林资源清查中的应用

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There are a lot of uncertainties existing in the traditional sampling methods of forest resources inventory. The presence of these uncertainties will reduce the sampling precision and the representation of the sample point on the whole. Under this background, Spatial Balanced Sampling (SBS) arises, which dramatically reduces the effects caused by the sampling frame change and non-response sampling units. This paper, by the method of Analysis Hierarchy Process (AHP) model for selecting the sampling program, analyzes the scenic beauty value of scenic forest in Nanjing Zijin Mountain and concludes that SBS should be selected to analyze the case. Meanwhile, by comparison between Spatial Balanced Sampling and traditional sampling methods, we draw some relative conclusions.

机译：传统的森林资源清查抽样方法存在很多不确定性。这些不确定性的存在将降低采样精度和总体上采样点的表示。在这种背景下，出现了空间平衡采样（SBS），从而大大减少了由采样帧变化和无响应采样单位引起的影响。本文采用层次分析法（AHP）选择抽样方案，分析了南京紫金山风景名胜区的风景名胜价值，并认为应该选择SBS对案例进行分析。同时，通过空间均衡采样与传统采样方法的比较，我们得出了一些相对的结论。

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《2010 International Conference on Computer Application and System Modeling》|2010年|V6-517-V6-521|共5页
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作者
Zhongquan Lv; Mingyang Li;
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正文语种
中图分类自动化技术、计算机技术;
关键词
AHP; SBS; traditional sampling;

机译：AHP; SBS;传统采样;

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Application of Spatial Balanced Sampling on forest resources inventory

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