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	Global mean estimation using a self-organizing dual-zoning method for preferential sampling
	Pan Y. C.; Ren, X. H.; Gao, B. B.; Liu, Y.; Gao, Y. B.; Hao, X. Y.; Chen, Z. Y.
	2015
关键词	Preferential sampling Global mean estimation Self-organizing dual-zoning method optimization inference
英文摘要	Giving an appropriate weight to each sampling point is essential to global mean estimation. The objective of this paper was to develop a global mean estimation method with preferential samples. The procedure for this estimation method was to first zone the study area based on self-organizing dual-zoning method and then to estimate the mean according to stratified sampling method. In this method, spreading of points in both feature and geographical space is considered. The method is tested in a case study on the metal Mn concentrations in Jilin provinces of China. Six sample patterns are selected to estimate the global mean and compared with the global mean calculated by direct arithmetic mean method, polygon method, and cell method. The results show that the proposed method produces more accurate and stable mean estimates under different feature deviation index (FDI) values and sample sizes. The relative errors of the global mean calculated by the proposed method are from 0.14 to 1.47 % and they are the largest (4.83-8.84 %) by direct arithmetic mean method. At the same time, the mean results calculated by the other three methods are sensitive to the FDI values and sample sizes.
出处	Environmental Monitoring and Assessment
卷	187
期	3
收录类别	SCI
语种	英语
ISSN号	0167-6369
内容类型	SCI/SSCI论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/38793]
专题	地理科学与资源研究所_历年回溯文献
推荐引用方式 GB/T 7714	Pan Y. C.,Ren, X. H.,Gao, B. B.,et al. Global mean estimation using a self-organizing dual-zoning method for preferential sampling. 2015.

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