TY - JOUR
T1 - Quantitative characterization of grain shape
T2 - Implications for textural maturity analysis and discrimination between depositional environments
AU - Tunwal, Mohit
AU - Mulchrone, Kieran F.
AU - Meere, Patrick A.
N1 - Publisher Copyright:
© 2017 The Authors. Sedimentology © 2017 International Association of Sedimentologists
PY - 2018/8
Y1 - 2018/8
N2 - Grain shape plays an important role in textural analysis of sedimentary grains. Textural analysis helps to determine the formation, transportation and deposition processes of sedimentary rocks. However, there is a lack of standardized methodology for quantitative characterization of grain shapes. The utility of fully automated image analysis for grain shape measurement is assessed in this paper. This research aimed to identify the most useful shape parameters for textural characterization of populations of grains and determine the relative importance of the parameters. A key aspect of this study is to determine whether, in a particular sedimentary environment, textural maturity of the samples can be ranked based on their grain shape data. Furthermore, discrimination of sedimentary depositional environments is explored on the basis of grain shape. In this study, 20 loose sediment samples from four known depositional environments (beach, aeolian, glacial and fluvial) were analysed using newly implemented automatic image analysis methods. For each sample, a set of 11 shape parameters were calculated for 200 grains. The data demonstrate a progression in textural maturity in terms of roundness, angularity, irregularity, fractal dimension, convexity, solidity and rectangularity. Furthermore, statistical analysis provides strong support for significant differences between samples grouped by environment and generates a ranking consistent with trends in maturity. Based on novel application of machine learning algorithms, angularity and fractal dimension are found to be the two most important parameters in texturally classifying a grain. The results of this study indicate that textural maturity is readily categorized using automated grain shape parameter analysis. However, it is not possible to absolutely discriminate between different depositional environments on the basis of shape parameters alone. This work opens up the possibility of detailed studies of the relationship between textural maturity and sedimentary environment, which may be more complicated than previously considered.
AB - Grain shape plays an important role in textural analysis of sedimentary grains. Textural analysis helps to determine the formation, transportation and deposition processes of sedimentary rocks. However, there is a lack of standardized methodology for quantitative characterization of grain shapes. The utility of fully automated image analysis for grain shape measurement is assessed in this paper. This research aimed to identify the most useful shape parameters for textural characterization of populations of grains and determine the relative importance of the parameters. A key aspect of this study is to determine whether, in a particular sedimentary environment, textural maturity of the samples can be ranked based on their grain shape data. Furthermore, discrimination of sedimentary depositional environments is explored on the basis of grain shape. In this study, 20 loose sediment samples from four known depositional environments (beach, aeolian, glacial and fluvial) were analysed using newly implemented automatic image analysis methods. For each sample, a set of 11 shape parameters were calculated for 200 grains. The data demonstrate a progression in textural maturity in terms of roundness, angularity, irregularity, fractal dimension, convexity, solidity and rectangularity. Furthermore, statistical analysis provides strong support for significant differences between samples grouped by environment and generates a ranking consistent with trends in maturity. Based on novel application of machine learning algorithms, angularity and fractal dimension are found to be the two most important parameters in texturally classifying a grain. The results of this study indicate that textural maturity is readily categorized using automated grain shape parameter analysis. However, it is not possible to absolutely discriminate between different depositional environments on the basis of shape parameters alone. This work opens up the possibility of detailed studies of the relationship between textural maturity and sedimentary environment, which may be more complicated than previously considered.
KW - Grain shape
KW - image analysis
KW - sedimentary environment discrimination
KW - shape measurement
KW - textural maturity
KW - texture
UR - https://www.scopus.com/pages/publications/85042377159
U2 - 10.1111/sed.12445
DO - 10.1111/sed.12445
M3 - Article
AN - SCOPUS:85042377159
SN - 0037-0746
VL - 65
SP - 1761
EP - 1776
JO - Sedimentology
JF - Sedimentology
IS - 5
ER -