New methods for unmixing sediment grain size data
文献类型：期刊论文
| 作者 | Paterson, Greig A.1; Heslop, David2 |
| 刊名 | GEOCHEMISTRY GEOPHYSICS GEOSYSTEMS
 |
| 出版日期 | 2015-12-01 |
| 卷号 | 16期号:12页码:4494-4506 |
| 关键词 | grain size distributions end-member analysis unmixing GUI software |
| DOI | 10.1002/2015GC006070 |
| 文献子类 | Article |
| 英文摘要 | Grain size distribution (GSD) data are widely used in Earth sciences and although large data sets are regularly generated, detailed numerical analyses are not routine. Unmixing GSDs into components can help understand sediment provenance and depositional regimes/processes. End-member analysis (EMA), which fits one set of end-members to a given data set, is a powerful way to unmix GSDs into geologically meaningful parts. EMA estimates end-members based on covariability within a data set and can be considered as a nonparametric approach. Available EMA algorithms, however, either produce suboptimal solutions or are time consuming. We introduce unmixing algorithms inspired by hyperspectral image analysis that can be applied to GSD data and which provide an improvement over current techniques. Nonparametric EMA is often unable to identify unimodal grain size subpopulations that correspond to single sediment sources. An alternative approach is single-specimen unmixing (SSU), which unmixes individual GSDs into unimodal parametric distributions (e.g., lognormal). We demonstrate that the inherent nonuniqueness of SSU solutions renders this approach unviable for estimating underlying mixing processes. To overcome this, we develop a new algorithm to perform parametric EMA, whereby an entire data set can be unmixed into unimodal parametric end-members (e.g., Weibull distributions). This makes it easier to identify individual grain size subpopulations in highly mixed data sets. To aid investigators in applying these methods, all of the new algorithms are available in AnalySize, which is GUI software for processing and unmixing grain size data. |
| WOS关键词 | NONNEGATIVE MATRIX FACTORIZATION ; MIXING PROBLEM ; DRILL CORE ; DISTRIBUTIONS ; COMPONENTS ; CHINA ; DECOMPOSITION ; ALGORITHMS ; ATLANTIC ; CURVES |
| WOS研究方向 | Geochemistry & Geophysics |
| 语种 | 英语 |
| WOS记录号 | WOS:000368814000025 |
| 资助机构 | NSFC(41374072) ; NSFC(41374072) ; Australian Research Council(DP120103952) ; Australian Research Council(DP120103952) ; NSFC(41374072) ; NSFC(41374072) ; Australian Research Council(DP120103952) ; Australian Research Council(DP120103952) |
| 源URL | [http://ir.iggcas.ac.cn/handle/132A11/62071]  |
| 专题 | 地质与地球物理研究所_中国科学院地球与行星物理重点实验室 |
| 作者单位 | 1.Chinese Acad Sci, Key Lab Earth & Planetary Phys, Inst Geol & Geophys, Beijing, Peoples R China 2.Australian Natl Univ, Res Sch Earth Sci, Canberra, ACT, Australia |
| 推荐引用方式 GB/T 7714 | Paterson, Greig A.,Heslop, David. New methods for unmixing sediment grain size data[J]. GEOCHEMISTRY GEOPHYSICS GEOSYSTEMS,2015,16(12):4494-4506. |
| APA | Paterson, Greig A.,&Heslop, David.(2015).New methods for unmixing sediment grain size data.GEOCHEMISTRY GEOPHYSICS GEOSYSTEMS,16(12),4494-4506. |
| MLA | Paterson, Greig A.,et al."New methods for unmixing sediment grain size data".GEOCHEMISTRY GEOPHYSICS GEOSYSTEMS 16.12(2015):4494-4506. |
入库方式： OAI收割
来源：地质与地球物理研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。