Discrimination between Sedimentary Rocks from Close-Range Visible and Very-Near-Infrared Images.

Variation in the mineral composition of rocks results in a change of their spectral response capable of being studied by imaging spectroscopy. This paper proposes the use of a low-cost handy sensor, a calibrated visible-very near infrared (VIS-VNIR) multispectral camera for the recognition of differ...

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Main Authors: Susana Del Pozo, Roderik Lindenbergh, Pablo Rodríguez-Gonzálvez, Jan Kees Blom, Diego González-Aguilera
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2015-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC4493113?pdf=render
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spelling doaj-d0794414547a4929a9f0555933e0a85d2020-11-25T01:55:02ZengPublic Library of Science (PLoS)PLoS ONE1932-62032015-01-01107e013247110.1371/journal.pone.0132471Discrimination between Sedimentary Rocks from Close-Range Visible and Very-Near-Infrared Images.Susana Del PozoRoderik LindenberghPablo Rodríguez-GonzálvezJan Kees BlomDiego González-AguileraVariation in the mineral composition of rocks results in a change of their spectral response capable of being studied by imaging spectroscopy. This paper proposes the use of a low-cost handy sensor, a calibrated visible-very near infrared (VIS-VNIR) multispectral camera for the recognition of different geological formations. The spectral data was recorded by a Tetracam Mini-MCA-6 camera mounted on a field-based platform covering six bands in the spectral range of 0.530-0.801 µm. Twelve sedimentary formations were selected in the Rhône-Alpes region (France) to analyse the discrimination potential of this camera for rock types and close-range mapping applications. After proper corrections and data processing, a supervised classification of the multispectral data was performed trying to distinguish four classes: limestones, marlstones, vegetation and shadows. After a maximum-likelihood classification, results confirmed that this camera can be efficiently exploited to map limestone-marlstone alternations in geological formations with this mineral composition.http://europepmc.org/articles/PMC4493113?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Susana Del Pozo
Roderik Lindenbergh
Pablo Rodríguez-Gonzálvez
Jan Kees Blom
Diego González-Aguilera
spellingShingle Susana Del Pozo
Roderik Lindenbergh
Pablo Rodríguez-Gonzálvez
Jan Kees Blom
Diego González-Aguilera
Discrimination between Sedimentary Rocks from Close-Range Visible and Very-Near-Infrared Images.
PLoS ONE
author_facet Susana Del Pozo
Roderik Lindenbergh
Pablo Rodríguez-Gonzálvez
Jan Kees Blom
Diego González-Aguilera
author_sort Susana Del Pozo
title Discrimination between Sedimentary Rocks from Close-Range Visible and Very-Near-Infrared Images.
title_short Discrimination between Sedimentary Rocks from Close-Range Visible and Very-Near-Infrared Images.
title_full Discrimination between Sedimentary Rocks from Close-Range Visible and Very-Near-Infrared Images.
title_fullStr Discrimination between Sedimentary Rocks from Close-Range Visible and Very-Near-Infrared Images.
title_full_unstemmed Discrimination between Sedimentary Rocks from Close-Range Visible and Very-Near-Infrared Images.
title_sort discrimination between sedimentary rocks from close-range visible and very-near-infrared images.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2015-01-01
description Variation in the mineral composition of rocks results in a change of their spectral response capable of being studied by imaging spectroscopy. This paper proposes the use of a low-cost handy sensor, a calibrated visible-very near infrared (VIS-VNIR) multispectral camera for the recognition of different geological formations. The spectral data was recorded by a Tetracam Mini-MCA-6 camera mounted on a field-based platform covering six bands in the spectral range of 0.530-0.801 µm. Twelve sedimentary formations were selected in the Rhône-Alpes region (France) to analyse the discrimination potential of this camera for rock types and close-range mapping applications. After proper corrections and data processing, a supervised classification of the multispectral data was performed trying to distinguish four classes: limestones, marlstones, vegetation and shadows. After a maximum-likelihood classification, results confirmed that this camera can be efficiently exploited to map limestone-marlstone alternations in geological formations with this mineral composition.
url http://europepmc.org/articles/PMC4493113?pdf=render
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