The pore size distribution is widely used to assess the physical quality of soil as an attribute affecting many chemical and biological processes within the soil. These data are commonly inferred indirectly through physical measurements such as water retention curves and Hg porosimetry. Digital image processing and analysis can provide a more direct route to acquire these data. Individual imaging approaches are typically limited, however, in terms of the range of pore sizes that can be identified. As soil processes occur across various scales, a multiscale approach is required to characterize the complexity of their function, which suggests that image data collected by various means must be integrated to allow a holistic understanding. We have developed a simple method for combining pore size distributions of soils acquired by various imaging techniques at different scales to produce a more useful data set for characterizing, assessing, and modeling soil processes. This method is illustrated with a set of local pore size distributions derived from three different image acquisition techniques.

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