Publication: Using RGISTools to estimate water levels in reservoirs and lakes
| dc.contributor.author | Militino, Ana F. | |
| dc.contributor.author | Montesino San Martín, Manuel | |
| dc.contributor.author | Pérez Goya, Unai | |
| dc.contributor.author | Ugarte Martínez, María Dolores | |
| dc.contributor.department | Estatistika, Informatika eta Matematika | eu |
| dc.contributor.department | Institute for Advanced Materials and Mathematics - INAMAT2 | en |
| dc.contributor.department | Estadística, Informática y Matemáticas | es_ES |
| dc.date.accessioned | 2021-01-20T09:41:14Z | |
| dc.date.available | 2021-01-20T09:41:14Z | |
| dc.date.issued | 2020 | |
| dc.description.abstract | The 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.sponsorship | This 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.extent | 19 p. | |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.doi | 10.3390/rs12121934 | |
| dc.identifier.issn | 2072-4292 (Electronic) | |
| dc.identifier.uri | https://academica-e.unavarra.es/handle/2454/39029 | |
| dc.language.iso | eng | en |
| dc.publisher | MDPI | en |
| dc.relation.ispartof | Remote Sensing, 2020, 12(12), 1934 | en |
| dc.relation.publisherversion | https://doi.org/10.3390/rs12121934 | |
| 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.accessRights | info:eu-repo/semantics/openAccess | en |
| dc.rights.accessRights | Acceso abierto / Sarbide irekia | es |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | Landsat | en |
| dc.subject | R software | en |
| dc.subject | Satellite images | en |
| dc.subject | Sentinel | en |
| dc.subject | Spatio-temporal data | en |
| dc.title | Using RGISTools to estimate water levels in reservoirs and lakes | en |
| dc.type | info:eu-repo/semantics/article | en |
| dc.type | Artículo / Artikulua | es |
| dc.type.version | info:eu-repo/semantics/publishedVersion | en |
| dc.type.version | Versión publicada / Argitaratu den bertsioa | es |
| dspace.entity.type | Publication | |
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