THE DESIS L2A PROCESSOR AND VALIDATION OF L2A PRODUCTS USING AERONET AND RADCALNET DATA
The hyperspectral instrument ”DLR Earth Sensing Imaging Spectrometer” (DESIS) is a VNIR sensor on-board of the International Space Station (ISS) and operational since October 2019. DESIS acquires images of Earth on user request with a swath of about 30 km width and 235 bands with a Full Width at Hal...
Published in: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
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ftdoajarticles:oai:doaj.org/article:67f6ec00a54a4a0d8737eeb4ebc0ad01 2023-05-15T13:06:03+02:00 THE DESIS L2A PROCESSOR AND VALIDATION OF L2A PRODUCTS USING AERONET AND RADCALNET DATA R. de los Reyes K. Alonso M. Bachmann E. Carmona M. Langheinrich R. Müller B. Pflug R. Richter 2022-02-01T00:00:00Z https://doi.org/10.5194/isprs-archives-XLVI-1-W1-2021-9-2022 https://doaj.org/article/67f6ec00a54a4a0d8737eeb4ebc0ad01 EN eng Copernicus Publications https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLVI-1-W1-2021/9/2022/isprs-archives-XLVI-1-W1-2021-9-2022.pdf https://doaj.org/toc/1682-1750 https://doaj.org/toc/2194-9034 doi:10.5194/isprs-archives-XLVI-1-W1-2021-9-2022 1682-1750 2194-9034 https://doaj.org/article/67f6ec00a54a4a0d8737eeb4ebc0ad01 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLVI-1-W1-2021, Pp 9-12 (2022) Technology T Engineering (General). Civil engineering (General) TA1-2040 Applied optics. Photonics TA1501-1820 article 2022 ftdoajarticles https://doi.org/10.5194/isprs-archives-XLVI-1-W1-2021-9-2022 2022-12-31T04:10:02Z The hyperspectral instrument ”DLR Earth Sensing Imaging Spectrometer” (DESIS) is a VNIR sensor on-board of the International Space Station (ISS) and operational since October 2019. DESIS acquires images of Earth on user request with a swath of about 30 km width and 235 bands with a Full Width at Half Maximum (FWHM) of 3.5 nm in the spectral range between 400 to 1000 nm. In this article we will present the basis of the atmospheric correction by PACO software, implemented inside the DESIS Ground Segment as L2A processor. The resulting L2A products will be validated against independent in-situ measurements. The aerosol optical thickness and water vapor will be compared with the Aerosol Robotic Network (AERONET) measurements and the surface reflectance will be validated with the Radiometric Calibration Network (RadCalNet) data. Article in Journal/Newspaper Aerosol Robotic Network Directory of Open Access Journals: DOAJ Articles The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVI-1/W1-2021 9 12 |
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Open Polar |
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Directory of Open Access Journals: DOAJ Articles |
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ftdoajarticles |
language |
English |
topic |
Technology T Engineering (General). Civil engineering (General) TA1-2040 Applied optics. Photonics TA1501-1820 |
spellingShingle |
Technology T Engineering (General). Civil engineering (General) TA1-2040 Applied optics. Photonics TA1501-1820 R. de los Reyes K. Alonso M. Bachmann E. Carmona M. Langheinrich R. Müller B. Pflug R. Richter THE DESIS L2A PROCESSOR AND VALIDATION OF L2A PRODUCTS USING AERONET AND RADCALNET DATA |
topic_facet |
Technology T Engineering (General). Civil engineering (General) TA1-2040 Applied optics. Photonics TA1501-1820 |
description |
The hyperspectral instrument ”DLR Earth Sensing Imaging Spectrometer” (DESIS) is a VNIR sensor on-board of the International Space Station (ISS) and operational since October 2019. DESIS acquires images of Earth on user request with a swath of about 30 km width and 235 bands with a Full Width at Half Maximum (FWHM) of 3.5 nm in the spectral range between 400 to 1000 nm. In this article we will present the basis of the atmospheric correction by PACO software, implemented inside the DESIS Ground Segment as L2A processor. The resulting L2A products will be validated against independent in-situ measurements. The aerosol optical thickness and water vapor will be compared with the Aerosol Robotic Network (AERONET) measurements and the surface reflectance will be validated with the Radiometric Calibration Network (RadCalNet) data. |
format |
Article in Journal/Newspaper |
author |
R. de los Reyes K. Alonso M. Bachmann E. Carmona M. Langheinrich R. Müller B. Pflug R. Richter |
author_facet |
R. de los Reyes K. Alonso M. Bachmann E. Carmona M. Langheinrich R. Müller B. Pflug R. Richter |
author_sort |
R. de los Reyes |
title |
THE DESIS L2A PROCESSOR AND VALIDATION OF L2A PRODUCTS USING AERONET AND RADCALNET DATA |
title_short |
THE DESIS L2A PROCESSOR AND VALIDATION OF L2A PRODUCTS USING AERONET AND RADCALNET DATA |
title_full |
THE DESIS L2A PROCESSOR AND VALIDATION OF L2A PRODUCTS USING AERONET AND RADCALNET DATA |
title_fullStr |
THE DESIS L2A PROCESSOR AND VALIDATION OF L2A PRODUCTS USING AERONET AND RADCALNET DATA |
title_full_unstemmed |
THE DESIS L2A PROCESSOR AND VALIDATION OF L2A PRODUCTS USING AERONET AND RADCALNET DATA |
title_sort |
desis l2a processor and validation of l2a products using aeronet and radcalnet data |
publisher |
Copernicus Publications |
publishDate |
2022 |
url |
https://doi.org/10.5194/isprs-archives-XLVI-1-W1-2021-9-2022 https://doaj.org/article/67f6ec00a54a4a0d8737eeb4ebc0ad01 |
genre |
Aerosol Robotic Network |
genre_facet |
Aerosol Robotic Network |
op_source |
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLVI-1-W1-2021, Pp 9-12 (2022) |
op_relation |
https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLVI-1-W1-2021/9/2022/isprs-archives-XLVI-1-W1-2021-9-2022.pdf https://doaj.org/toc/1682-1750 https://doaj.org/toc/2194-9034 doi:10.5194/isprs-archives-XLVI-1-W1-2021-9-2022 1682-1750 2194-9034 https://doaj.org/article/67f6ec00a54a4a0d8737eeb4ebc0ad01 |
op_doi |
https://doi.org/10.5194/isprs-archives-XLVI-1-W1-2021-9-2022 |
container_title |
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
container_volume |
XLVI-1/W1-2021 |
container_start_page |
9 |
op_container_end_page |
12 |
_version_ |
1766401375883755520 |