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PACO: Python-Based Atmospheric Correction

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 acqui...

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Detalles Bibliográficos
Autores principales: de los Reyes, Raquel, Langheinrich, Maximilian, Schwind, Peter, Richter, Rudolf, Pflug, Bringfried, Bachmann, Martin, Müller, Rupert, Carmona, Emiliano, Zekoll, Viktoria, Reinartz, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085641/
https://www.ncbi.nlm.nih.gov/pubmed/32151105
http://dx.doi.org/10.3390/s20051428
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author de los Reyes, Raquel
Langheinrich, Maximilian
Schwind, Peter
Richter, Rudolf
Pflug, Bringfried
Bachmann, Martin
Müller, Rupert
Carmona, Emiliano
Zekoll, Viktoria
Reinartz, Peter
author_facet de los Reyes, Raquel
Langheinrich, Maximilian
Schwind, Peter
Richter, Rudolf
Pflug, Bringfried
Bachmann, Martin
Müller, Rupert
Carmona, Emiliano
Zekoll, Viktoria
Reinartz, Peter
author_sort de los Reyes, Raquel
collection PubMed
description 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.
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spelling pubmed-70856412020-04-21 PACO: Python-Based Atmospheric Correction de los Reyes, Raquel Langheinrich, Maximilian Schwind, Peter Richter, Rudolf Pflug, Bringfried Bachmann, Martin Müller, Rupert Carmona, Emiliano Zekoll, Viktoria Reinartz, Peter Sensors (Basel) Article 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. MDPI 2020-03-05 /pmc/articles/PMC7085641/ /pubmed/32151105 http://dx.doi.org/10.3390/s20051428 Text en © 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
de los Reyes, Raquel
Langheinrich, Maximilian
Schwind, Peter
Richter, Rudolf
Pflug, Bringfried
Bachmann, Martin
Müller, Rupert
Carmona, Emiliano
Zekoll, Viktoria
Reinartz, Peter
PACO: Python-Based Atmospheric Correction
title PACO: Python-Based Atmospheric Correction
title_full PACO: Python-Based Atmospheric Correction
title_fullStr PACO: Python-Based Atmospheric Correction
title_full_unstemmed PACO: Python-Based Atmospheric Correction
title_short PACO: Python-Based Atmospheric Correction
title_sort paco: python-based atmospheric correction
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085641/
https://www.ncbi.nlm.nih.gov/pubmed/32151105
http://dx.doi.org/10.3390/s20051428
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