Multiphasic Quantification of Soil Morphology using High-Resolution X-ray Computed Tomography

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X-ray computed tomography (CT) has become an important tool for understanding the three-dimensional (3D) configuration of soil components. This technology has provided unique insight into the physical nature of soil, especially its hydrodynamic behaviour and the impact of management practices on structural quality. One of the principle limitations of typical CT imagery of soil is its monochromatic nature, limiting our ability to distinguish among the various solid and organic solids. The issue of partial volumes, whereby the value expressed by a given unit of the imagery (voxel) may result from more than one material (referred to as the partial volume effect) further introduces complexity to segmentation and classification. Moreover, our capacity to process 3D imagery lags behind that for 2D imagery (which has been driven primarily by remote sensing applications); in part, this is also due to greater computational requirements for 3D imagery. As such, effective standardization of methodologies for the application of X-ray CT to soil has yet to be achieved. The current research program will focus on contributing our ability to discriminate the major mineral and organic solid phases that commonly occur naturally in soils, or may be present as contaminants. Specific attention will be given to refining the composition of the X-ray beam, through appropriate combinations of scanning energy and metal pre-filtering, to maximize the discrimination among phases during the scanning stage. This will be complemented by the adaptation of advanced object-based image segregation techniques to 3D X-ray CT imagery. Specific attention will be given to optimizing the quantification of hydromorphic pedofeatures, specifically Fe and Mn segregations. Finally, methods for morphometric analysis of classified imagery and advanced spatial analysis, including multi-fractal and entropy techniques, of the original grey-scale imagery will continue to be refined to take advantage of improved scanning and segmentation techniques. This research will be conducted primarily in the Soil Imaging Laboratory of the University of Guelph, but will also engage an international network of expertise on X-ray CT imaging and image processing, and provide both post-graduate and undergraduate level training opportunities.