Automated characterisation of glaciomarine sediments using X-ray computed laminography


McDonald N, Bradwell T, Callard SL, Toney JL, Shreeve B & Shreeve J (2022) Automated characterisation of glaciomarine sediments using X-ray computed laminography. Quaternary Science Advances, 5, Art. No.: 100046.

This study investigates the potential of a new high-resolution, non-destructive, X-ray imaging technique for the Quaternary Sciences – computed laminography (CL). Greyscale properties are systematically extracted from digital X-radiographic CL images of cored glaciomarine sediments to analyse and characterise sediments at pixel-scale resolution (< 0.1 mm). We show how this can be achieved manually, and also with an easy-to-use, automated statistical tool which we have devised specifically for use in glaciomarine sediments. This Sediment Characteristics tool, in the form of a plugin for the freely available FIJI/ImageJ programme, extracts mean or median X-ray grey values (GV) – a proxy for sediment density; and associated standard deviation (SD) – a proxy for sediment heterogeneity – at sub-mm resolution, across the width of sediment core CL images. We demonstrate how these properties (GV and SD) can be directly used to characterise sediment properties and in particular to quantify the abundance of gravel clasts, or ice-rafted debris, in cored glaciomarine sediments. The tool’s effectiveness is compared with other, more traditional, X-radiographic methods for counting ice-rafted gravel clasts in glaciomarine sediment. We propose that the CL output and Sediment Characteristics tool also have the potential to quantitatively analyse other 3-dimensional structures, such as cyclic lamination (varve) geometry; deformation structures; bioturbation and void space (porosity). Finally, we present the raw code, allowing open-access, transparency and reproducibility in other formats.

X-radiography; Laminography; Glaciomarine; Sediments; Ice-rafted debris

Quaternary Science Advances: Volume 5

FundersNERC Natural Environment Research Council
Publication date31/01/2022
Publication date online31/12/2021
Date accepted by journal29/11/2021
PublisherElsevier BV