Shadow analysis: A method for measuring soil surface roughness

Erosion potential and the effects of tillage can be evaluated from quantitative descriptions of soil surface roughness. The present study therefore aimed to fill the need for a reliable, low-cost and convenient method to measure that parameter. Based on the interpretation of micro-topographic shadows, this new procedure is primarily designed for use in the field after tillage. The principle underlying shadow analysis is the direct relationship between soil surface roughness and the shadows cast by soil structures under fixed sunlight conditions. The results obtained with this method were compared to the statistical indexes used to interpret field readings recorded by a pin meter. The tests were conducted on 4-m2 sandy loam and sandy clay loam plots divided into 1-m2 subplots tilled with three different tools: chisel, tiller and roller. The highly significant correlation between the statistical indexes and shadow analysis results obtained in the laboratory as well as in the field for all the soil–tool combinations proved that both variability (CV) and dispersion (SD) are accommodated by the new method. This procedure simplifies the interpretation of soil surface roughness and shortens the time involved in field operations by a factor ranging from 12 to 20

Variation in spectral and mass dimension on three-dimensional soil image processing

A quantitative characterization of the three-dimensional soil pore architecture is important for understanding soil processes as it relates to the control of biological, chemical, and physical processes across scales. Recent advances in nondestructive imaging, such as X-ray computed tomography (CT), provide an opportunity to analyze pore space features from direct visualization of soil structure. At the same time that these techniques provide new opportunities, they also introduce new processing steps on which the final results depend. Fractal formalism has been shown to be a useful tool in cases where highly complex and heterogeneous media are studied. One of these quantifications is mass dimension (Dm) and spectral dimension (d) applied for water and gas diffusion in soil. In this work, intact soil samples were collected from four horizons of a Brazilian soil, and three-dimensional images, of 45.1-Km resolution (256 x 256 x 256 voxels), were obtained. Four different threshold criteria were used to transform CT grayscale imagery in binary imagery (pore/solid), based on the frequency of CT units. We calculated the sensitivity of a geometrical parameter (the mass fractal dimension, Dm), a topological parameter (the spectral dimension, d), and the ratio of the two (Dm), which relates to the scaling property of dynamic processes in soil such as diffusion. Each threshold criterion had a direct influence on the measured porosity and on the value of Dm, showing a clear logarithmic increase in Dm with porosity. Meanwhile, d increased faster, that is, linearly with measured porosity. In all cases, the detailed dependence on porosity was different for each horizon. In contrast, the ratio for each horizon was less sensitive to the thresholding criteria applied to the image. Thus, the results based on our soil samples suggest that thresholding has a strong influence on parameters that relate to geometrical and topological properties of structure but may have a less important