一种新的估计林分算术平均高抽样方法的验证与应用

本文用计算机模拟取样,探讨Yojiro Ueno提出的一种新的抽样方法应用于长白山落叶松人工林和柞树林的试验样地的有效性。应用不同次数的重复试验结果表明:1)随着样本容量的增加,不同重复的差异逐渐减小,当增加到一定程度,重复一次随机抽样即可有较好的稳定性和较低的抽样误差。2)平均相对误差AKP-]和不同重复间变异系数CV曲线都随取样数目的增加而呈下降趋势,且上升波动程度也随之减小,渐平稳。当样本量大小达到某值之前 ,AKP-]和CV

Study on the Application of A New Sampling Technique for Estimating the Arithmetic Mean Height of Stand

Forest arithmetic mean height measurement plays a quite important role in the study of ecological factors and forest resource inventory, however , which is usually thought to not only cost too much labor and time, but be low accuracy. A new sampling technique introduced by Yojiro Ueno is that without knowing the exact number of trees , it can efficiently and easily estimate the arithmetic mean height . Based on computer simulation, the paper applied this technique into plots from Larix plantations and Mongolian oak forest in Changbaishan mountains. The results from different repeat times showed that 1) the differences of mean relative error as AKP-] and variation coefficient as CV between different repeat times tended fo decrease as the number of sampling points increased. This sampling technique was efficient by doing only one time when the number of sampling points was big enough. 2)AKP-] and CV had similar decreasing trends as the number of sampling points was increasing , which showed that they decreased remarkably before the number of sampling points reached a certain value , after that the speed of decreasing slowed down .Their fluctuation degrees also decreased as the number of sampling points increased. 3) This technique used in Larix plantations was better than in Mongolian oak forest. It was demonstrated that the lower CV, the larger the number of all trees , the better effectivity this sampling technique had.