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Remote Sens. 2017, 9(12), 1319; https://doi.org/10.3390/rs9121319

Radiometric Correction of Simultaneously Acquired Landsat-7/Landsat-8 and Sentinel-2A Imagery Using Pseudoinvariant Areas (PIA): Contributing to the Landsat Time Series Legacy

1
Grumets Research Group, Departament de Geografia, Edifici B, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain
2
Remote Sensing and GIS Laboratory (LAST-EBD), Estación Biológica de Doñana (CSIC), C/Américo Vespucio 26, Isla de la Cartuja, 41092 Sevilla, Spain
3
Grumets Research Group, CREAF, Edifici C, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain
4
Asiaq-Greenland Survey, P.O. Box 1003-3900 Nuuk, Greenland, Denmark
5
Geophysical Institute and Institute of Northern Engineering, University of Alaska Fairbanks, 903 Koyukuk Dr, Fairbanks, AK 99709, USA
6
Department of Computational Landscape Ecology, Helmholtz Centre for Environmental Research—UFZ Permoserstr, 15, 04318 Leipzig, Germany
*
Author to whom correspondence should be addressed.
Received: 7 November 2017 / Revised: 6 December 2017 / Accepted: 12 December 2017 / Published: 15 December 2017
(This article belongs to the Section Atmosphere Remote Sensing)
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Abstract

The 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 community. View Full-Text
Keywords: radiometric correction; Landsat-7; Landsat-8; Sentinel-2A; Landsat Legacy; field spectroradiometry; pseudoinvariant areas (PIA) radiometric correction; Landsat-7; Landsat-8; Sentinel-2A; Landsat Legacy; field spectroradiometry; pseudoinvariant areas (PIA)
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Padró, J.-C.; Pons, X.; Aragonés, D.; Díaz-Delgado, R.; García, D.; Bustamante, J.; Pesquer, L.; Domingo-Marimon, C.; González-Guerrero, Ò.; Cristóbal, J.; Doktor, D.; Lange, M. Radiometric Correction of Simultaneously Acquired Landsat-7/Landsat-8 and Sentinel-2A Imagery Using Pseudoinvariant Areas (PIA): Contributing to the Landsat Time Series Legacy. Remote Sens. 2017, 9, 1319.

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