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Article

PACO: Python-Based Atmospheric Correction

1
German Aerospace Center (DLR), Earth Observation Center, Remote Sensing Technology Institute, Photogrammetry and Image Analysis, Oberpfaffenhofen, 82234 Wessling, Germany
2
German Aerospace Center (DLR), Earth Observation Center, Remote Sensing Technology Institute, Photogrammetry and Image Analysis, 12489 Berlin, Germany
3
German Aerospace Center (DLR), Earth Observation Center, Remote Sensing Data Center, Oberpfaffenhofen, 82234 Wessling, Germany
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(5), 1428; https://doi.org/10.3390/s20051428
Received: 5 February 2020 / Revised: 2 March 2020 / Accepted: 2 March 2020 / Published: 5 March 2020
(This article belongs to the Section Remote Sensors)
The atmospheric correction of satellite images based on radiative transfer calculations is a prerequisite for many remote sensing applications. The software package ATCOR, developed at the German Aerospace Center (DLR), is a versatile atmospheric correction software, capable of processing data acquired by many different optical satellite sensors. Based on this well established algorithm, a new Python-based atmospheric correction software has been developed to generate L2A products of Sentinel-2, Landsat-8, and of new space-based hyperspectral sensors such as DESIS (DLR Earth Sensing Imaging Spectrometer) and EnMAP (Environmental Mapping and Analysis Program). This paper outlines the underlying algorithms of PACO, and presents the validation results by comparing L2A products generated from Sentinel-2 L1C images with in situ (AERONET and RadCalNet) data within VNIR-SWIR spectral wavelengths range. View Full-Text
Keywords: atmospheric correction; remote sensing; Sentinel-2; Landsat-8; DESIS; aerosol optical thickness; water vapor; surface reflectance atmospheric correction; remote sensing; Sentinel-2; Landsat-8; DESIS; aerosol optical thickness; water vapor; surface reflectance
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MDPI and ACS Style

de los Reyes, R.; Langheinrich, M.; Schwind, P.; Richter, R.; Pflug, B.; Bachmann, M.; Müller, R.; Carmona, E.; Zekoll, V.; Reinartz, P. PACO: Python-Based Atmospheric Correction. Sensors 2020, 20, 1428. https://doi.org/10.3390/s20051428

AMA Style

de los Reyes R, Langheinrich M, Schwind P, Richter R, Pflug B, Bachmann M, Müller R, Carmona E, Zekoll V, Reinartz P. PACO: Python-Based Atmospheric Correction. Sensors. 2020; 20(5):1428. https://doi.org/10.3390/s20051428

Chicago/Turabian Style

de los Reyes, Raquel, Maximilian Langheinrich, Peter Schwind, Rudolf Richter, Bringfried Pflug, Martin Bachmann, Rupert Müller, Emiliano Carmona, Viktoria Zekoll, and Peter Reinartz. 2020. "PACO: Python-Based Atmospheric Correction" Sensors 20, no. 5: 1428. https://doi.org/10.3390/s20051428

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