Characterization of soil microstructure using 3d X-ray tomographic images
X-Ray CT Scan Soil Samples; Detrended Fluctuation Analysis; Fisher-Shannon plane; complexity; Land use change.
Dozens of definitions of soil can be found in literature, ranging from the most straightforward concepts, where it is asserted, for example, that soil is a heterogeneous mixture of air, water, inorganic and organic solids, and microorganisms, to more complex concepts, where the soil is considered a living, four-dimensional natural Entity. However, regardless of the adopted definition, the importance of soil is unquestionable, as it provides nutrients for plant growth essential for human and animal nutrition. Moreover, history has frequently shown that its misuse can lead to poverty, hunger, drought, and ecological and economic disasters. This great importance given to soil generates a need for ongoing studies searching for methods and tools that contribute to new knowledge. A powerful tool that can observe the elements of soil in a non-destructive way is computerized tomography (CT). Despite advances in the resolution of CT equipment and computer power, there is no consensus on data analysis methods that can reveal the complexity of all elements associated with 3D soil images, especially methods that do not require a threshold to segment images. In this context, this work employs two methods originally developed for the analysis of complex signals, Detrended Fluctuation Analysis (DFA) and Fisher-Shannon (FS), to bring a new understanding of the complexity of morphological properties of soil based on the analysis of 3D CT images. Up to date, these two methods have not been used in 3D image analysis. In this work, 3D soil tomographic images were analyzed using DFA in its original form and its generalization for 2D and 3D data. The results of DFA exponents were found to be smaller than 0.5 indicating antipersistence of local density fluctuations, which are consistently stronger (lower exponent value) for the sugar cane plantation sample, than for the Atlantic Forest. Furthermore, a new complexity measure is defined as the distance from the isocomplexity line in the normalized FS plane, which may be seen as a quantifier of soil degradation level. This novel approach resulted in a high grouping success rate (91.7%) between soil covered by native vegetation (Atlantic Forest) and soil that was the subject of the degradation process as the consequence of land use change (from native Atlantic Forest to sugarcane cultivation).