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dc.creatorSola Torralba, Iones_ES
dc.creatorGonzález Audicana, Maríaes_ES
dc.creatorÁlvarez Mozos, Jesúses_ES
dc.date.accessioned2017-11-15T08:00:44Z
dc.date.available2017-11-15T08:00:44Z
dc.date.issued2016
dc.identifier.issn2072-4292 (Electronic)
dc.identifier.urihttps://hdl.handle.net/2454/26145
dc.description.abstractSatellite images in mountainous areas are strongly affected by topography. Different studies demonstrated that the results of semi-empirical topographic correction algorithms improved when a stratification of land covers was carried out first. However, differences in the stratification strategies proposed and also in the evaluation of the results obtained make it unclear how to implement them. The objective of this study was to compare different stratification strategies with a non-stratified approach using several evaluation criteria. For that purpose, Statistic-Empirical and Sun-Canopy-Sensor + C algorithms were applied and six different stratification approaches, based on vegetation indices and land cover maps, were implemented and compared with the non-stratified traditional option. Overall, this study demonstrates that for this particular case study the six stratification approaches can give results similar to applying a traditional topographic correction with no previous stratification. Therefore, the non-stratified correction approach could potentially aid in removing the topographic effect, because it does not require any ancillary information and it is easier to implement in automatic image processing chains. The findings also suggest that the Statistic-Empirical method performs slightly better than the Sun-Canopy-Sensor + C correction, regardless of the stratification approach. In any case, further research is necessary to evaluate other stratification strategies and confirm these results.en
dc.description.sponsorshipThe authors gratefully acknowledge the financial support provided by the Public University of Navarre (UPNA). Part of the research presented in this paper is funded by the Spanish Ministry of Economy and Competitiveness in the frame of the ESP2013-48458-C4-2-P project.en
dc.format.extent22 p.
dc.format.mimetypeapplication/pdfen
dc.language.isoenen
dc.publisherMDPIen
dc.relation.ispartofRemote Sensing, 2016, 8(2), 131en
dc.rights© 2016 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.subjectTopographic correctionen
dc.subjectStratificationen
dc.subjectNDVIen
dc.subjectLand coveren
dc.subjectEvaluationen
dc.subjectQuality assessmenten
dc.titleThe added value of stratified topographic correction of multispectral imagesen
dc.typeArtículo / Artikuluaes
dc.typeinfo:eu-repo/semantics/articleen
dc.contributor.departmentUniversidad Pública de Navarra. Departamento de Proyectos e Ingeniería Rurales_ES
dc.contributor.departmentNafarroako Unibertsitate Publikoa. Landa Ingeniaritza eta Proiektuak Sailaeu
dc.rights.accessRightsAcceso abierto / Sarbide irekiaes
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessen
dc.identifier.doi10.3390/rs8020131
dc.relation.projectIDinfo:eu-repo/grantAgreement/ES/1PE/ESP2013-48458
dc.relation.publisherversionhttps://dx.doi.org/10.3390/rs8020131
dc.type.versionVersión publicada / Argitaratu den bertsioaes
dc.type.versioninfo:eu-repo/semantics/publishedVersionen
dc.contributor.funderUniversidad Pública de Navarra / Nafarroako Unibertsitate Publikoaes


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© 2016 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.
Except where otherwise noted, this item's license is described as © 2016 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.