文献类型：期刊文献

英文题名：A new design for sampling with adaptive sample plots

作者：Yang, Haijun[1] Kleinn, Christoph[1] Fehrmann, Lutz[1] Tang, Shouzheng[2] Magnussen, Steen[3]

第一作者：Yang, Haijun

通信作者：Kleinn, C[1]

机构：[1]Univ Gottingen, D-37077 Gottingen, Germany;[2]Chinese Acad Forestry, Inst Forest Resources Informat Tech, Beijing 100091, Peoples R China;[3]Forestry Canada, Pacific Forestry Ctr, Canadian Forest Serv, Nat Resources Canada, Victoria, BC V8Z 1M5, Canada

年份：2011

卷号：18

期号：2

起止页码：223-237

外文期刊名：ENVIRONMENTAL AND ECOLOGICAL STATISTICS

收录：;Scopus(收录号：2-s2.0-79957599481);WOS:【SCI-EXPANDED(收录号:WOS:000291040600002)】；

基金：The results presented here are from the research project KL 894/10-1 funded by the German Science Council (DFG). We gratefully acknowledge this support from DFG. Our sincere thanks go to Dr. Frantisek Vilcko who shared his skills and experiences in computer programming for determining inclusion zones, to Mr. Tim Exner for his kind assistance, to Mr. Paul Magdon for his comments on the graphic presentation of the study results, and Dr. Yuancai Lei and Mr. Guangyu Zhu for their support to field work when mapping our real population. Furthermore, we thank two anonymous reviewers for their helpful comments.

语种：英文

外文关键词：Forest inventory; Adaptive cluster sampling; Plot design; Conditional plot expansion; Inclusion zone approach

摘要：Adaptive cluster sampling (ACS) is a sampling technique for sampling rare and geographically clustered populations. Aiming to enhance the practicability of ACS while maintaining some of its major characteristics, an adaptive sample plot design is introduced in this study which facilitates field work compared to "standard" ACS. The plot design is based on a conditional plot expansion: a larger plot (by a pre-defined plot size factor) is installed at a sample point instead of the smaller initial plot if a pre-defined condition is fulfilled. This study provides insight to the statistical performance of the proposed adaptive plot design. A design-unbiased estimator is presented and used on six artificial and one real tree position maps to estimate density (number of objects per ha). The performance in terms of coefficient of variation is compared to the non-adaptive alternative without a conditional expansion of plot size. The adaptive plot design was superior in all cases but the improvement depends on (1) the structure of the sampled population, (2) the plot size factor and (3) the critical value (the minimum number of objects triggering an expansion). For some spatial arrangements the improvement is relatively small. The adaptive design may be particularly attractive for sampling in rare and compactly clustered populations with an appropriately chosen plot size factor.