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

Del Pozo S, Lindenbergh R, Rodríguez-Gonzálvez P, Kees Blom J, González-Aguilera D - PLoS ONE (2015)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Department of Cartographic and Land Engineering, University of Salamanca, Polytechnic School of Avila, Avila, Spain.

ABSTRACT
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.

No MeSH data available.


Related in: MedlinePlus

Hemispherical spectral reflectance factor of each Spectralon panel.
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pone.0132471.g004: Hemispherical spectral reflectance factor of each Spectralon panel.

Mentions: In order to obtain images with physical values (reflectance) from raw digital images two essential parameters must be known, the radiometric calibration parameters of each of the six bands (offset and gain, c0 and c1), and the solar irradiance (E) of the capture moment. Since the multispectral camera was radiometrically calibrated in a previous field campaign, c0 and c1 per band were known [22]. This calibration was a radiometric vicarious calibration based on the radiance method and closely related to the empirical line correction approach [23, 24]. On the other hand, the solar irradiance for each capture moment was obtained by using a standard calibrated reflection target (Spectralon, Labsphere) as will be explained below. The calibrated Spectralon used in this study (Fig 4) consisted of four different panels of 99%, 50%, 25% and 12% reflectance. The spectral behaviour of each Spectralon panel was certified in laboratory.


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

Del Pozo S, Lindenbergh R, Rodríguez-Gonzálvez P, Kees Blom J, González-Aguilera D - PLoS ONE (2015)

Hemispherical spectral reflectance factor of each Spectralon panel.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4493113&req=5

pone.0132471.g004: Hemispherical spectral reflectance factor of each Spectralon panel.
Mentions: In order to obtain images with physical values (reflectance) from raw digital images two essential parameters must be known, the radiometric calibration parameters of each of the six bands (offset and gain, c0 and c1), and the solar irradiance (E) of the capture moment. Since the multispectral camera was radiometrically calibrated in a previous field campaign, c0 and c1 per band were known [22]. This calibration was a radiometric vicarious calibration based on the radiance method and closely related to the empirical line correction approach [23, 24]. On the other hand, the solar irradiance for each capture moment was obtained by using a standard calibrated reflection target (Spectralon, Labsphere) as will be explained below. The calibrated Spectralon used in this study (Fig 4) consisted of four different panels of 99%, 50%, 25% and 12% reflectance. The spectral behaviour of each Spectralon panel was certified in laboratory.

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Department of Cartographic and Land Engineering, University of Salamanca, Polytechnic School of Avila, Avila, Spain.

ABSTRACT
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.

No MeSH data available.


Related in: MedlinePlus