## Abstract

Analysis of channel cross sections is hindered by lack of parameters to describe the shape of the cross section. In the situation of a sample of cross sections taken across tidal inlets, if the cross section is expressed as an observation vector, principal-component analysis can be used to derive eigenvectors for the data set. By neglecting eigenvectors that explain little variance, mathematical representation of the original data set is simplified by transformation to the eigenvector space. For 408 cross sections each represented by a 60-component vector, three eigenvectors explain 97.5 percent of the total variance in the data set. The three-dimensional representation simplifies the task of analyzing cross-sectional shape. The physical form of the first three eigenvectors have considerable resemblance to classical types of variation noted in inlet-channel studies. The method is applicable directly to analysis of other fluvial and estuarine channels.

Original language | English (US) |
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Pages (from-to) | 635-647 |

Number of pages | 13 |

Journal | Journal of the International Association for Mathematical Geology |

Volume | 8 |

Issue number | 6 |

DOIs | |

State | Published - Dec 1976 |

Externally published | Yes |

## Keywords

- geomorphology
- oceanography
- principal-components analysis
- sedimentology

## ASJC Scopus subject areas

- Mathematics (miscellaneous)
- Earth and Planetary Sciences (miscellaneous)