Skip navigation

3D multifractal characterization of computed tomography images of soils under different tillage management: linking multifractal parameters to physical properties

3D multifractal characterization of computed tomography images of soils under different tillage management: linking multifractal parameters to physical properties

Soto-Gomez, Diego, Perez-Rodriguez, Paula, Juiz, Laura Vazquez, Paradelo, Marcos ORCID: 0000-0002-2768-0136 and Lopez-Periago, J. Eugenio (2019) 3D multifractal characterization of computed tomography images of soils under different tillage management: linking multifractal parameters to physical properties. Geoderma, 363:114129. ISSN 0016-7061 (Print), 1872-6259 (Online) (doi:https://doi.org/10.1016/j.geoderma.2019.114129)

Full text not available from this repository. (Request a copy)

Abstract

Multifractal analysis of pore images obtained from X-ray computed tomography (CT) was used to characterize the scaling properties of macropores in soils with different managements and their correspondence with macroscopic physical properties related with the soil functions.

We used CT images of twenty undisturbed soil columns to examine the multifractal properties of the pores identified by X-ray computed tomography (CT-Porosity). Multifractal spectra successfully describe the scaling of the pore network in all soil columns. The dimensions and scaling parameters of these spectra correlate with macroscopic magnitudes, namely, CT-Porosity, surface area of the pore walls, tortuosity, and bulk density. We also found strong correlations between the singularity spectra and the topological descriptors of the pore network skeleton: total slab voxels, number of branches per path, number of endpoints and sum of branch length, among others. These correlations show that the complexity of the CT-Porosity can be related quantitatively with physical properties, the organization of the pore skeleton and solute transport.

Item Type: Article
Uncontrolled Keywords: soil management, soil structure, multifractal analisys, pore network
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
S Agriculture > S Agriculture (General)
Faculty / Department / Research Group: Faculty of Engineering & Science
Faculty of Engineering & Science > Natural Resources Institute
Faculty of Engineering & Science > Natural Resources Institute > Agriculture, Health & Environment Department
Last Modified: 12 Mar 2020 13:38
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
Selected for REF2021: None
URI: http://gala.gre.ac.uk/id/eprint/27350

Actions (login required)

View Item View Item