Geospatial Management and Analysis of Microstructural Data from San Andreas Fault Observatory at Depth (SAFOD) Core Samples
Core samples obtained from scientific drilling could provide large volumes of direct microstructural and compositional data, but generating results via the traditional treatment of such data is often time-consuming and inefficient. Unifying microstructural data within a spatially referenced Geograph...
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doaj-17281523f0484021a41ebfa99de2002d2021-05-31T23:59:40ZengMDPI AGISPRS International Journal of Geo-Information2220-99642021-05-011033233210.3390/ijgi10050332Geospatial Management and Analysis of Microstructural Data from San Andreas Fault Observatory at Depth (SAFOD) Core SamplesElliott M. Holmes0Andrea E. Gaughan1Donald J. Biddle2Forrest R. Stevens3Jafar Hadizadeh4Department of Geography and Geosciences, University of Louisville, Louisville, KY 40208, USADepartment of Geography and Geosciences, University of Louisville, Louisville, KY 40208, USADepartment of Geography and Geosciences, University of Louisville, Louisville, KY 40208, USADepartment of Geography and Geosciences, University of Louisville, Louisville, KY 40208, USADepartment of Geography and Geosciences, University of Louisville, Louisville, KY 40208, USACore samples obtained from scientific drilling could provide large volumes of direct microstructural and compositional data, but generating results via the traditional treatment of such data is often time-consuming and inefficient. Unifying microstructural data within a spatially referenced Geographic Information System (GIS) environment provides an opportunity to readily locate, visualize, correlate, and apply remote sensing techniques to the data. Using 26 core billet samples from the San Andreas Fault Observatory at Depth (SAFOD), this study developed GIS-based procedures for: 1. Spatially referenced visualization and storage of various microstructural data from core billets; 2. 3D modeling of billets and thin section positions within each billet, which serve as a digital record after irreversible fragmentation of the physical billets; and 3. Vector feature creation and unsupervised classification of a multi-generation calcite vein network from cathodluminescence (CL) imagery. Building on existing work which is predominantly limited to the 2D space of single thin sections, our results indicate that a GIS can facilitate spatial treatment of data even at centimeter to nanometer scales, but also revealed challenges involving intensive 3D representations and complex matrix transformations required to create geographically translated forms of the within-billet coordinate systems, which are suggested for consideration in future studies.https://www.mdpi.com/2220-9964/10/5/332Geographic Information Systems (GIS)remote sensingstructural geology3D visualizationspatial analyses |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Elliott M. Holmes Andrea E. Gaughan Donald J. Biddle Forrest R. Stevens Jafar Hadizadeh |
spellingShingle |
Elliott M. Holmes Andrea E. Gaughan Donald J. Biddle Forrest R. Stevens Jafar Hadizadeh Geospatial Management and Analysis of Microstructural Data from San Andreas Fault Observatory at Depth (SAFOD) Core Samples ISPRS International Journal of Geo-Information Geographic Information Systems (GIS) remote sensing structural geology 3D visualization spatial analyses |
author_facet |
Elliott M. Holmes Andrea E. Gaughan Donald J. Biddle Forrest R. Stevens Jafar Hadizadeh |
author_sort |
Elliott M. Holmes |
title |
Geospatial Management and Analysis of Microstructural Data from San Andreas Fault Observatory at Depth (SAFOD) Core Samples |
title_short |
Geospatial Management and Analysis of Microstructural Data from San Andreas Fault Observatory at Depth (SAFOD) Core Samples |
title_full |
Geospatial Management and Analysis of Microstructural Data from San Andreas Fault Observatory at Depth (SAFOD) Core Samples |
title_fullStr |
Geospatial Management and Analysis of Microstructural Data from San Andreas Fault Observatory at Depth (SAFOD) Core Samples |
title_full_unstemmed |
Geospatial Management and Analysis of Microstructural Data from San Andreas Fault Observatory at Depth (SAFOD) Core Samples |
title_sort |
geospatial management and analysis of microstructural data from san andreas fault observatory at depth (safod) core samples |
publisher |
MDPI AG |
series |
ISPRS International Journal of Geo-Information |
issn |
2220-9964 |
publishDate |
2021-05-01 |
description |
Core samples obtained from scientific drilling could provide large volumes of direct microstructural and compositional data, but generating results via the traditional treatment of such data is often time-consuming and inefficient. Unifying microstructural data within a spatially referenced Geographic Information System (GIS) environment provides an opportunity to readily locate, visualize, correlate, and apply remote sensing techniques to the data. Using 26 core billet samples from the San Andreas Fault Observatory at Depth (SAFOD), this study developed GIS-based procedures for: 1. Spatially referenced visualization and storage of various microstructural data from core billets; 2. 3D modeling of billets and thin section positions within each billet, which serve as a digital record after irreversible fragmentation of the physical billets; and 3. Vector feature creation and unsupervised classification of a multi-generation calcite vein network from cathodluminescence (CL) imagery. Building on existing work which is predominantly limited to the 2D space of single thin sections, our results indicate that a GIS can facilitate spatial treatment of data even at centimeter to nanometer scales, but also revealed challenges involving intensive 3D representations and complex matrix transformations required to create geographically translated forms of the within-billet coordinate systems, which are suggested for consideration in future studies. |
topic |
Geographic Information Systems (GIS) remote sensing structural geology 3D visualization spatial analyses |
url |
https://www.mdpi.com/2220-9964/10/5/332 |
work_keys_str_mv |
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