Analysing Soil Structure Through 3D Grayscale Imaging: Geometrical and Network-Based Insights Without Binarization

Soil structure is fundamental in determining soil functionality, including water retention, nutrient availability, microbial growth processes, and gas exchange. Analysing soil structure through 3D grayscale imaging provides an innovative approach to understand its properties without resorting to binarization, a process that can oversimplify complex soil features. By systematically altering the global threshold applied to grayscale images, detailed geometrical and network-based parameters can be extracted, preserving the nuanced heterogeneity of natural (real) soils.

This study compared natural soil images with randomly generated models to calculate critical parameters. Geometrical metrics such as porosity, pore size distribution, tortuosity, formation factor, and fractal dimension were determined to characterise the structural complexity of the soil matrix. Additionally, connectivity and other network-based parameters, reflecting the porous network's topology, were analysed to reveal insights into the soil's functionality and capacity to support biological and physical processes.

Our approach highlights the importance of maintaining grayscale image fidelity to capture subtle but essential soil features, offering a more nuanced analysis than traditional binarization techniques. The findings emphasise the interplay between geometrical and network properties in defining soil structure and its ecological roles. This method holds promise for advancing soil science and sustainable land management practices.

Keywords: soil structure, 3D grayscale imaging, porosity, tortuosity, fractal dimension, porous network, connectivity.

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