Influence of thresholding in mass and entropy dimension of 3-D soil images

Tarquis, Ana M.; Heck, Richard J.; Grau, Juan B.; Fabregat, J.; Sanchez, M. E.; Muñoz-Antón, Javier

doi:10.5194/npg-15-881-2008

Cited by 28 publications

(17 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…However, it was also shown that for the type of samples in this study, a reasonable agreement with the overall porosity was found (Baveye et al, 2010). Tarquis et al (2008; showed the impact of thresholding on various geometrical descriptors of pore geometry, but the consequences for soil functioning is still largely unknown, which can be explored with the modelling framework presented in this paper.…”

Section: Discussionmentioning

confidence: 94%

Modelling and quantifying the effect of heterogeneity in soil physical conditions on fungal growth

et al. 2010

View full text Add to dashboard Cite

Abstract. Despite the importance of fungi in soil ecosystem services, a theoretical framework that links soil management strategies with fungal ecology is still lacking. One of the key challenges is to understand how the complex geometrical shape of pores in soil affects fungal spread and species interaction. Progress in this area has long been hampered by a lack of experimental techniques for quantification. In this paper we use X-ray computed tomography to quantify and characterize the pore geometry at microscopic scales (30 µm) that are relevant for fungal spread in soil. We analysed the pore geometry for replicated samples with bulk-densities ranging from 1.2-1.6 g/cm 3 . The bulk-density of soils significantly affected the total volume, mean pore diameter and connectivity of the pore volume. A previously described fungal growth model comprising a minimal set of physiological processes required to produce a range of phenotypic responses was used to analyse the effect of these geometric descriptors on fungal invasion, and we showed that the degree and rate of fungal invasion was affected mainly by pore volume and pore connectivity. The presented experimental and theoretical framework is a significant first step towards understanding how environmental change and soil management impact on fungal diversity in soils.

show abstract

Section: Discussionmentioning

confidence: 94%

Modelling and quantifying the effect of heterogeneity in soil physical conditions on fungal growth

et al. 2010

View full text Add to dashboard Cite

show abstract

“…The crossover length derived from semivariogram analysis is an index that is commonly used in most recent soil microrelief studies to describe surface microroughness. It has the advantage of its quantification being scale-independent through the consideration of the spatial correlation between surface elevations (Vidal Vázquez et al, 2007;Paz-Ferreiro et al, 2008;Tarquis et al, 2008). The semivariogram is calculated from the following equation:…”

Section: Soil Surface Roughness Quantificationmentioning

confidence: 99%

“…Assuming a fractional Brownian motion model for describing soil surface roughness (as proposed in the pioneering work of Mandelbrot and Van Ness, 1968), the following expression for γ (h) that incorporates the generalized Hurst exponent, H is obtained (Huang and Bradford, 1992;Vidal Vázquez et al, 2007;PazFerreiro et al, 2008;Tarquis et al, 2008):…”

Section: Soil Surface Roughness Quantificationmentioning

confidence: 99%

Quantifying the changes of soil surface microroughness due to rainfall impact on a smooth surface

Abban

Papanicolaou

Giannopoulos

et al. 2017

Nonlin. Processes Geophys.

View full text Add to dashboard Cite

Abstract. This study examines the rainfall-induced change in soil microroughness of a bare smooth soil surface in an agricultural field. The majority of soil microroughness studies have focused on surface roughness on the order of ∼ 5-50 mm and have reported a decay of soil surface roughness with rainfall. However, there is quantitative evidence from a few studies suggesting that surfaces with microroughness less than 5 mm may undergo an increase in roughness when subject to rainfall action. The focus herein is on initial microroughness length scales on the order of 2 mm, a low roughness condition observed seasonally in some landscapes under bare conditions and chosen to systematically examine the increasing roughness phenomenon. Three rainfall intensities of 30, 60, and 75 mm h −1 are applied to a smoothened bed surface in a field plot via a rainfall simulator. Soil surface microroughness is recorded via a surface-profile laser scanner. Several indices are utilized to quantify the soil surface microroughness, namely the random roughness (RR) index, the crossover length, the variance scale from the MarkovGaussian model, and the limiting difference. Findings show a consistent increase in roughness under the action of rainfall, with an overall agreement between all indices in terms of trend and magnitude. Although this study is limited to a narrow range of rainfall and soil conditions, the results suggest that the outcome of the interaction between rainfall and a soil surface can be different for smooth and rough surfaces and thus warrant the need for a better understanding of this interaction.

show abstract

“…The principal advantages of the CT technique are that it reduces the physical impact of the sampling, provides three-dimensional (3D) information, and allows for rapid scanning, such that the sample can be studied in nearly real-time (Rasiah and Aylmore, 1998). Several authors have recently dedicated their attention to solid-pore CT boundary identification, as this is a critical step in digital image processing on which the quality of the final results is highly dependent (Baveye et al, 2010;Tarquis et al, 2008Tarquis et al, , 2009Tarquis et al, , 2012). An overview of the steps and instrumental settings used to generate the X-ray CT greyscale soil images and the influence on the final quality can be seen in Houston et al (2013a).…”

Section: Introductionmentioning

confidence: 99%

Identification of pore spaces in 3D CT soil images using PFCM partitional clustering

Ojeda-Magaña

Quintanilla-Domínguez

Ruelas

et al. 2014

Geoderma

View full text Add to dashboard Cite

Recent advances in non-destructive imaging techniques, such as X-ray computed tomography (CT), make it possible to analyse pore space features from the direct visualisation from soil structures. A quantitative characterisation of the three-dimensional solid-pore architecture is important to understand soil mechanics, as they relate to the control of biological, chemical, and physical processes across scales. This analysis technique therefore offers an opportunity to better interpret soil strata, as new and relevant information can be obtained. In this work, we propose an approach to automatically identify the pore structure of a set of 200-2D images that represent slices of an original 3D CT image of a soil sample, which can be accomplished through non-linear enhancement of the pixel grey levels and an image segmentation based on a PFCM (Possibilistic Fuzzy C-Means) algorithm. Once the solids and pore spaces have been identified, the set of 200-2D images is then used to reconstruct an approximation of the soil sample by projecting only the pore spaces. This reconstruction shows the structure of the soil and its pores, which become more bounded, less bounded, or unbounded with changes in depth. If the soil sample image quality is sufficiently favourable in terms of contrast, noise and sharpness, the pore identification is less complicated, and the PFCM clustering algorithm can be used without additional processing; otherwise, images require pre-processing before using this algorithm. Promising results were obtained with four soil samples, the first of which was used to show the algorithm validity and the additional three were used to demonstrate the robustness of our proposal. The methodology we present here can better detect the solid soil and pore spaces on CT images, enabling the generation of better 2D-3D representations of pore structures from segmented 2D images.

show abstract

Influence of thresholding in mass and entropy dimension of 3-D soil images

Cited by 28 publications

References 39 publications

Modelling and quantifying the effect of heterogeneity in soil physical conditions on fungal growth

Modelling and quantifying the effect of heterogeneity in soil physical conditions on fungal growth

Quantifying the changes of soil surface microroughness due to rainfall impact on a smooth surface

Identification of pore spaces in 3D CT soil images using PFCM partitional clustering

Contact Info

Product

Resources

About