Mostrar el registro sencillo del ítem

dc.creatorMilitino, Ana F.es_ES
dc.creatorMontesino San Martín, Manueles_ES
dc.creatorPérez Goya, Unaies_ES
dc.creatorUgarte Martínez, María Doloreses_ES
dc.date.accessioned2021-01-20T09:41:14Z
dc.date.available2021-01-20T09:41:14Z
dc.date.issued2020
dc.identifier.issn2072-4292 (Electronic)
dc.identifier.urihttps://hdl.handle.net/2454/39029
dc.description.abstractThe combination of freely accessible satellite imagery from multiple programs improves the spatio-temporal coverage of remote sensing data, but it exhibits barriers regarding the variety of web services, file formats, and data standards. Ris an open-source software environment with state-of-the-art statistical packages for the analysis of optical imagery. However, it lacks the tools for providing unified access to multi-program archives to customize and process the time series of images. This manuscript introduces RGISTools, a new software that solves these issues, and provides a working example on water mapping, which is a socially and environmentally relevant research field. The case study uses a digital elevation model and a rarely assessed combination of Landsat-8 and Sentinel-2 imagery to determine the water level of a reservoir in Northern Spain. The case study demonstrates how to acquire and process time series of surface reflectance data in an efficient manner. Our method achieves reasonably accurate results, with a root mean squared error of 0.90 m. Future improvements of the package involve the expansion of the workflow to cover the processing of radar images. This should counteract the limitation of the cloud coverage with multi-spectral images.en
dc.description.sponsorshipThis research was supported by the project MTM2017-82553-R(AEI/FEDER, UE). It has also received funding from the La Caixa Foundation (ID1000010434), the Caja Navarra Foundation, and UNED Pamplona, under Agreement LCF/PR/PR15/51100007.en
dc.format.extent19 p.
dc.format.mimetypeapplication/pdfen
dc.language.isoengen
dc.publisherMDPIen
dc.relation.ispartofRemote Sensing, 2020, 12(12), 1934en
dc.rights© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.en
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectLandsaten
dc.subjectR softwareen
dc.subjectSatellite imagesen
dc.subjectSentinelen
dc.subjectSpatio-temporal dataen
dc.titleUsing RGISTools to estimate water levels in reservoirs and lakesen
dc.typeinfo:eu-repo/semantics/articleen
dc.typeArtículo / Artikuluaes
dc.contributor.departmentEstatistika, Informatika eta Matematikaeu
dc.contributor.departmentInstitute for Advanced Materials and Mathematics - INAMAT2en
dc.contributor.departmentEstadística, Informática y Matemáticases_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessen
dc.rights.accessRightsAcceso abierto / Sarbide irekiaes
dc.identifier.doi10.3390/rs12121934
dc.relation.publisherversionhttps://doi.org/10.3390/rs12121934
dc.type.versioninfo:eu-repo/semantics/publishedVersionen
dc.type.versionVersión publicada / Argitaratu den bertsioaes


Ficheros en el ítem

Thumbnail

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.
La licencia del ítem se describe como © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.

El Repositorio ha recibido la ayuda de la Fundación Española para la Ciencia y la Tecnología para la realización de actividades en el ámbito del fomento de la investigación científica de excelencia, en la Línea 2. Repositorios institucionales (convocatoria 2020-2021).
Logo MinisterioLogo Fecyt