The evaluation of macroscopic and microscopic textures of sand grains using elliptic Fourier and principal component analysis: Implications for the discrimination of sedimentary environments
The evaluation of macroscopic and microscopic textures of sand grains using elliptic Fourier and principal component analysis: Implications for the discrimination of sedimentary environments
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DOI：
10.1111/sed.12183
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发表时间：
2015-06
期刊：
影响因子：
3.5
通讯作者：
Keita Suzuki;H. Fujiwara;T. Ohta
中科院分区：
文献类型：
--
作者：
Keita Suzuki;H. Fujiwara;T. Ohta
椭圆傅里叶与主成分分析相结合的方法是砂粒形状分析的新发展。然而，传统的椭圆傅里叶和基于椭圆傅里叶结果的方差-协方差矩阵的主成分分析只能确定沙粒的形态，而无法量化颗粒的细尺度边界光滑度。在本研究中，使用椭圆傅里叶和主成分分析以及基于相关矩阵的椭圆傅里叶和主成分分析的扩展来分析来自冰川、河流、前滨和风沙环境的沙粒，以分别提取颗粒形状（宏观）和颗粒边界光滑度（微观）的信息。基于方差-协方差矩阵的传统椭圆傅里叶和主成分分析可产生宏观颗粒形状描述符，例如伸长指数和凹凸指数。这些指数表明，暴露于水下运输（河流和前滩）的沙粒的形状比暴露于水下运输（风成沙丘）的沙粒更长。然而，基于相关矩阵的椭圆傅里叶和主成分分析还能够提取微观颗粒特征，这可以用边界平滑度指数来解释。边界光滑度指数表明冰川颗粒的表面最粗糙，而风成颗粒的表面最光滑。在边界平滑度和伸长指数的双变量图中，来自河流、前滨、风沙和冰川环境的样本聚集在离散区域。此外，分析表明，冰川颗粒暴露于与河流、前滨和风成环境中的颗粒不同的形态成熟路径。
A method that integrates elliptic Fourier and principal component analysis is a new development in the analysis of the shapes of sand grains. However, conventional elliptic Fourier and principal component analysis based on the variance–covariance matrix of the elliptic Fourier results can determine only the form of sand grains, and fails to quantify fine‐scale boundary smoothness of grains. In this study, sand grains from glacial, fluvial, foreshore and aeolian environments were analysed using both elliptic Fourier and principal component analysis and an extension of elliptic Fourier and principal component analysis based on the correlation matrix to extract information on grain form (macroscopic) and grain boundary smoothness (microscopic) separately. Conventional elliptic Fourier and principal component analysis based on the variance–covariance matrix produces macroscopic particle shape descriptors, such as the elongation index and bump indices. These indices indicate that sand grains exposed to subaqueous transportation (fluvial and foreshore) have forms that are more elongated than those exposed to subaerial transportation (aeolian dunes). However, elliptic Fourier and principal component analysis based on the correlation matrix is, in addition, able to extract microscopic particle features, which can be interpreted in terms of a boundary smoothness index. The boundary smoothness index indicates that the surfaces of glacial grains are the most rugged, whereas the surfaces of aeolian grains are the smoothest. On bivariate plots of the boundary smoothness and elongation indices, samples from fluvial, foreshore, aeolian and glacial environments cluster in discrete regions. In addition, the analysis reveals that glacial grains are exposed to different morphological maturation pathways than those from fluvial, foreshore and aeolian environments.