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我国现存的森林资源调查方法存在着空间关联性强、适应性差的缺陷。随着新的森林调查技术规程的出台与林区社会经济条件的变化,急剧上升的调查成本与有限的调查经费的矛盾日益突出。与此同时,森林资源调查过程中抽样框变化、无反应样本单元的现象日益突出。空间平衡抽样(SBS)强调样本点抽取的随机等概和空间上的均衡分布,通过包含概率栅格层的过滤运算,极大地减少了无反应样本单元现象发生。紫金山国家森林公园风景林美学调查空间平衡抽样案例研究表明,空间平衡抽样在降低调查成本、减少空间关联性强方面,明显优于简单随机抽样;但在提高抽样精度方面没有表现出明显的优势,只有当样本容量大于或等于理论计算容量时,空间平衡抽样才表现出一定的抽样精度优势。作为一种具有严格统计学基础的、高效低成本的、适应性强的抽样方法,空间平衡抽样在森林资源调查中具有较大的应用潜力。
The existing method of forest resources survey in our country has the defects of strong spatial relevance and poor adaptability. With the promulgation of new forest investigation technical regulations and the changes of social and economic conditions in forest areas, the contradiction between the sharply rising investigation cost and limited investigation funding has become increasingly prominent. In the meantime, the sampling frame changes during the forest resources survey and the phenomena of non-reaction sample units have become increasingly prominent. Spatial Balance Sampling (SBS) emphasizes stochastic equality and spatially balanced distribution of sample points, and greatly reduces the occurrence of unresponsive sample cells through filtering operations involving the probability grid layer. The case study of spatial equilibrium sampling in scenic forest aesthetics of Purple Mountain National Forest Park shows that spatial balanced sampling is obviously superior to simple random sampling in reducing survey cost and reducing the spatial correlation, but it has no obvious advantage in improving sampling precision , Only when the sample size is greater than or equal to the theoretical calculation capacity, the space balance sampling shows a certain sampling precision advantage. As a sampling method with rigorous statistics, high efficiency, low cost and adaptability, spatial equilibrium sampling has great potential in forest resources survey.