Para depositar en Docta Complutense, identifícate con tu correo @ucm.es en el SSO institucional. Haz clic en el desplegable de INICIO DE SESIÓN situado en la parte superior derecha de la pantalla. Introduce tu correo electrónico y tu contraseña de la UCM y haz clic en el botón MI CUENTA UCM, no autenticación con contraseña.

Identification and classification of mineralogical associations by VNIR-SWIR spectroscopy in the Tajo basin (Spain)

dc.contributor.authorGarcía Rivas, Javier
dc.contributor.authorSuárez Barrios, María Mercedes
dc.contributor.authorGarcía Romero, Emilia
dc.contributor.authorGarcía Meléndez, Eduardo
dc.date.accessioned2024-01-16T08:09:13Z
dc.date.available2024-01-16T08:09:13Z
dc.date.issued2018
dc.description.abstract41 soil samples were collected at the Tajo Basin (Spain), in an area where Mg-rich clays are benefitted, whit the aim of studying their spectral response in the Visible, Near Infrared (VNIR) – Short Wave Infrared (SWIR) range (350–2500 nm) in terms of mineralogical composition and exploring the possibility of using these data as the basis of a geological mapping through hyperspectral imaging in this wavenumber interval in future research. The samples, belonging to nine different stratigraphic units, were characterized by X-Ray diffraction and VNIR – SWIR laboratory reflectance spectroscopy. The mineralogical associations are formed by complex mixtures of carbonates, gypsum, quartz, feldspars, illite, and smectites in variable proportions depending on the stratigraphic unit. The samples were classified into different groups and subgroups according to their spectral response. The resulting groups allow to extrapolate certain type-spectra to different mineralogical associations corresponding to the stratigraphic units sampled within the area of study. This work is of upmost importance for future works through remote-sensing techniques using VNIR – SWIR imaging of the area. The classification of the samples in different groups, according to their spectral response, and their attribution to the different stratigraphic units sampled, according to their mineralogical content, could help improve the geological mapping of the area of study as well as detecting deposits of Mg-rich clays of economic interest.en
dc.description.departmentDepto. de Mineralogía y Petrología
dc.description.facultyFac. de Ciencias Geológicas
dc.description.refereedTRUE
dc.description.sponsorshipMinisterio de Economía y Competitividad (España)
dc.description.statuspub
dc.identifier.citationGarcía-Rivas, Javier, et al. «Identification and Classification of Mineralogical Associations by VNIR-SWIR Spectroscopy in the Tajo Basin (Spain)». International Journal of Applied Earth Observation and Geoinformation, vol. 72, octubre de 2018, pp. 57-65. https://doi.org/10.1016/j.jag.2018.05.028.
dc.identifier.doi10.1016/j.jag.2018.05.028
dc.identifier.essn1872-826X
dc.identifier.issn0303-2434
dc.identifier.officialurlhttps://doi.org/10.1016/j.jag.2018.05.028
dc.identifier.urihttps://hdl.handle.net/20.500.14352/93238
dc.journal.titleInternational journal of applied earth observation and geoinformation
dc.language.isoeng
dc.page.final65
dc.page.initial57
dc.publisherElsevier
dc.relation.projectIDinfo:eu-repo/grantAgreement/CGL2016-77005-R
dc.relation.projectIDinfo:eu-repo/grantAgreement/ESP2017-89045-R
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO/BES-2013-065092/ES/BES-2013-065092/
dc.rights.accessRightsrestricted access
dc.subject.cdu549.6
dc.subject.keywordVNIR-SWIR spectroscopy
dc.subject.keywordXRD
dc.subject.keywordMg-rich smectites
dc.subject.keywordRemote sensing
dc.subject.ucmMineralogía (Geología)
dc.subject.unesco2506.11 Mineralogía
dc.titleIdentification and classification of mineralogical associations by VNIR-SWIR spectroscopy in the Tajo basin (Spain)
dc.typejournal article
dc.type.hasVersionVoR
dc.volume.number72
dspace.entity.typePublication
relation.isAuthorOfPublicatione039abf0-032e-428b-a0d2-513967a1c0ff
relation.isAuthorOfPublicationb7658e83-41da-46f0-aca8-94370da806bd
relation.isAuthorOfPublication.latestForDiscoverye039abf0-032e-428b-a0d2-513967a1c0ff

Download

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
VNIR-SWIR_spectroscopy.pdf
Size:
2.22 MB
Format:
Adobe Portable Document Format

Collections