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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...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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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. |
format | Online Article Text |
id | pubmed-7085641 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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