TopCap: A Tool to Quantify Soil Surface Topology and Subsurface Structure

The surface of a material such as soil, as characterized by its topology and roughness, typically has a profound effect on its functional behavior. While nondestructive imaging techniques such as X-ray computed tomography (CT) have been used extensively in recent years to characterize the internal a...

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Main Authors: Amin Garbout, Craig J. Sturrock, Elena Armenise, Sujung Ahn, Robert W. Simmons, Stefan Doerr, Karl Ritz, Sacha J. Mooney
Format: Article
Language:English
Published: Wiley 2018-04-01
Series:Vadose Zone Journal
Online Access:https://dl.sciencesocieties.org/publications/vzj/articles/17/1/170091
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spelling doaj-fe2cf1b1c07f4e298e402784a6b6cba42020-11-25T03:31:57ZengWileyVadose Zone Journal1539-16632018-04-0117110.2136/vzj2017.05.0091TopCap: A Tool to Quantify Soil Surface Topology and Subsurface StructureAmin GarboutCraig J. SturrockElena ArmeniseSujung AhnRobert W. SimmonsStefan DoerrKarl RitzSacha J. MooneyThe surface of a material such as soil, as characterized by its topology and roughness, typically has a profound effect on its functional behavior. While nondestructive imaging techniques such as X-ray computed tomography (CT) have been used extensively in recent years to characterize the internal architecture of soil, less attention has been paid to the morphology of the soil surface, possibly because other techniques such as scanning electron microscopy and atomic force microscopy are viewed as more appropriate. However, X-ray CT exploration of the surface of a soil also permits analyses immediately below its surface and beyond into the sample, contingent on its thickness. This provides important information such as how a connected structure might permit solute infiltration or gaseous diffusion through the surface and beyond into the subsurface matrix. A previous limitation to this approach had been the inability to segment and quantify the actual three-dimensional structural complexity at the surface, rather than a predefined geometrically simplistic volume immediately below it. To overcome this, we formulated TopCap, a novel algorithm that operates with ImageJ as a plugin and automatically captures the actual three-dimensional surface morphology, segments the pore structure within the acquired volume, and provides a series of incisive morphological measurements of the associated porous architecture. TopCap provides rapid, automated analysis of the immediate surface of materials and beyond, and while developed in the context of soil, is applicable to any three-dimensional image volume.https://dl.sciencesocieties.org/publications/vzj/articles/17/1/170091
collection DOAJ
language English
format Article
sources DOAJ
author Amin Garbout
Craig J. Sturrock
Elena Armenise
Sujung Ahn
Robert W. Simmons
Stefan Doerr
Karl Ritz
Sacha J. Mooney
spellingShingle Amin Garbout
Craig J. Sturrock
Elena Armenise
Sujung Ahn
Robert W. Simmons
Stefan Doerr
Karl Ritz
Sacha J. Mooney
TopCap: A Tool to Quantify Soil Surface Topology and Subsurface Structure
Vadose Zone Journal
author_facet Amin Garbout
Craig J. Sturrock
Elena Armenise
Sujung Ahn
Robert W. Simmons
Stefan Doerr
Karl Ritz
Sacha J. Mooney
author_sort Amin Garbout
title TopCap: A Tool to Quantify Soil Surface Topology and Subsurface Structure
title_short TopCap: A Tool to Quantify Soil Surface Topology and Subsurface Structure
title_full TopCap: A Tool to Quantify Soil Surface Topology and Subsurface Structure
title_fullStr TopCap: A Tool to Quantify Soil Surface Topology and Subsurface Structure
title_full_unstemmed TopCap: A Tool to Quantify Soil Surface Topology and Subsurface Structure
title_sort topcap: a tool to quantify soil surface topology and subsurface structure
publisher Wiley
series Vadose Zone Journal
issn 1539-1663
publishDate 2018-04-01
description The surface of a material such as soil, as characterized by its topology and roughness, typically has a profound effect on its functional behavior. While nondestructive imaging techniques such as X-ray computed tomography (CT) have been used extensively in recent years to characterize the internal architecture of soil, less attention has been paid to the morphology of the soil surface, possibly because other techniques such as scanning electron microscopy and atomic force microscopy are viewed as more appropriate. However, X-ray CT exploration of the surface of a soil also permits analyses immediately below its surface and beyond into the sample, contingent on its thickness. This provides important information such as how a connected structure might permit solute infiltration or gaseous diffusion through the surface and beyond into the subsurface matrix. A previous limitation to this approach had been the inability to segment and quantify the actual three-dimensional structural complexity at the surface, rather than a predefined geometrically simplistic volume immediately below it. To overcome this, we formulated TopCap, a novel algorithm that operates with ImageJ as a plugin and automatically captures the actual three-dimensional surface morphology, segments the pore structure within the acquired volume, and provides a series of incisive morphological measurements of the associated porous architecture. TopCap provides rapid, automated analysis of the immediate surface of materials and beyond, and while developed in the context of soil, is applicable to any three-dimensional image volume.
url https://dl.sciencesocieties.org/publications/vzj/articles/17/1/170091
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