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dc.contributor.authorPadró, Joan-Cristianes_ES
dc.contributor.authorPons, Xavieres_ES
dc.contributor.authorAragonés, Davides_ES
dc.contributor.authorDíaz-Delgado, Ricardoes_ES
dc.contributor.authorGarcía, Diegoes_ES
dc.contributor.authorBustamante, Javieres_ES
dc.contributor.authorPesquer, Lluíses_ES
dc.contributor.authorDomingo-Marimon, Cristinaes_ES
dc.contributor.authorGonzález-Guerrero, Óscares_ES
dc.contributor.authorCristóbal, Jordies_ES
dc.contributor.authorDoktor, Danieles_ES
dc.contributor.authorLange, Maximilianes_ES
dc.date.accessioned2018-01-02T09:29:31Z-
dc.date.available2018-01-02T09:29:31Z-
dc.date.issued2017-
dc.identifier.citationRemote Sensing, 9:1319 (2017)es_ES
dc.identifier.urihttp://hdl.handle.net/10261/158709-
dc.description.abstractThe use of Pseudoinvariant Areas (PIA) makes it possible to carry out a reasonably robust and automatic radiometric correction for long time series of remote sensing imagery, as shown in previous studies for large data sets of Landsat MSS, TM, and ETM+ imagery. In addition, they can be employed to obtain more coherence among remote sensing data from different sensors. The present work validates the use of PIA for the radiometric correction of pairs of images acquired almost simultaneously (Landsat-7 (ETM+) or Landsat-8 (OLI) and Sentinel-2A (MSI)). Four pairs of images from a region in SW Spain, corresponding to four different dates, together with field spectroradiometry measurements collected at the time of satellite overpass were used to evaluate a PIA-based radiometric correction. The results show a high coherence between sensors (r2 = 0.964) and excellent correlations to in-situ data for the MiraMon implementation (r2 > 0.9). Other methodological alternatives, ATCOR3 (ETM+, OLI, MSI), SAC-QGIS (ETM+, OLI, MSI), 6S-LEDAPS (ETM+), 6S-LaSRC (OLI), and Sen2Cor-SNAP (MSI), were also evaluated. Almost all of them, except for SAC-QGIS, provided similar results to the proposed PIA-based approach. Moreover, as the PIA-based approach can be applied to almost any image (even to images lacking of extra atmospheric information), it can also be used to solve the robust integration of data from new platforms, such as Landsat-8 or Sentinel-2, to enrich global data acquired since 1972 in the Landsat program. It thus contributes to the program’s continuity, a goal of great interest for the environmental, scientific, and technical communityes_ES
dc.language.isoenges_ES
dc.publisherMultidisciplinary Digital Publishing Institutees_ES
dc.relation.isversionofPublisher's versiones_ES
dc.rightsopenAccesses_ES
dc.subjectRadiometric correctiones_ES
dc.subjectLandsat-7es_ES
dc.subjectLandsat-8es_ES
dc.subjectSentinel- 2Aes_ES
dc.subjectLandsat legacyes_ES
dc.subjectField spectroradiometryes_ES
dc.subjectPseudoinvariant areas (PIA)es_ES
dc.titleRadiometric Correction of Simultaneously Acquired Landsat-7/Landsat-8 and Sentinel-2A Imagery Using Pseudoinvariant Areas (PIA): Contributing to the Landsat Time Series Legacyes_ES
dc.typeartículoes_ES
dc.identifier.doi10.3390/rs9121319-
dc.description.peerreviewedPeer reviewedes_ES
dc.relation.publisherversionhttp://dx.doi.org/10.3390/rs9121319es_ES
dc.relation.csices_ES
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