Retrieval of Snow Properties from the Sentinel-3 Ocean and Land Colour Instrument

The Sentinel Application Platform (SNAP) architecture facilitates Earth Observation data processing. In this work, we present results from a new Snow Processor for SNAP. We also describe physical principles behind the developed snow property retrieval technique based on the analysis of Ocean and Lan...

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Published in:Remote Sensing
Main Authors: Kokhanovsky, Alexander, Lamare, Maxim, Danne, Olaf, Brockmann, Carsten, Dumont, Marie, Picard, Ghislain, Arnaud, Laurent, Favier, Vincent, Jourdain, Bruno, Le Meur, Emmanuel, Di Mauro, Biagio, Aoki, Teruo, Niwano, Masashi, Rozanov, Vladimir, Korkin, Sergey, Kipfstuhl, Sepp, Freitag, Johannes, Hoerhold, Maria, Zuhr, Alexandra (Dr.), Vladimirova, Diana, Faber, Anne-Katrine, Steen-Larsen, Hans Christian, Wahl, Sonja, Andersen, Jonas K., Vandecrux, Baptiste, van As, Dirk, Mankoff, Kenneth D., Kern, Michael, Zege, Eleonora, Box, Jason E.
Format: Article in Journal/Newspaper
Language:English
Published: 2019
Subjects:
Online Access:https://publishup.uni-potsdam.de/frontdoor/index/index/docId/48525
https://doi.org/10.3390/rs11192280
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spelling ftubpotsdam:oai:kobv.de-opus4-uni-potsdam:48525 2023-06-11T04:03:11+02:00 Retrieval of Snow Properties from the Sentinel-3 Ocean and Land Colour Instrument Kokhanovsky, Alexander Lamare, Maxim Danne, Olaf Brockmann, Carsten Dumont, Marie Picard, Ghislain Arnaud, Laurent Favier, Vincent Jourdain, Bruno Le Meur, Emmanuel Di Mauro, Biagio Aoki, Teruo Niwano, Masashi Rozanov, Vladimir Korkin, Sergey Kipfstuhl, Sepp Freitag, Johannes Hoerhold, Maria Zuhr, Alexandra (Dr.) Vladimirova, Diana Faber, Anne-Katrine Steen-Larsen, Hans Christian Wahl, Sonja Andersen, Jonas K. Vandecrux, Baptiste van As, Dirk Mankoff, Kenneth D. Kern, Michael Zege, Eleonora Box, Jason E. 2019-09-29 https://publishup.uni-potsdam.de/frontdoor/index/index/docId/48525 https://doi.org/10.3390/rs11192280 eng eng https://publishup.uni-potsdam.de/frontdoor/index/index/docId/48525 https://doi.org/10.3390/rs11192280 info:eu-repo/semantics/closedAccess ddc:550 Institut für Geowissenschaften article doc-type:article 2019 ftubpotsdam https://doi.org/10.3390/rs11192280 2023-04-23T22:33:19Z The Sentinel Application Platform (SNAP) architecture facilitates Earth Observation data processing. In this work, we present results from a new Snow Processor for SNAP. We also describe physical principles behind the developed snow property retrieval technique based on the analysis of Ocean and Land Colour Instrument (OLCI) onboard Sentinel-3A/B measurements over clean and polluted snow fields. Using OLCI spectral reflectance measurements in the range 400-1020 nm, we derived important snow properties such as spectral and broadband albedo, snow specific surface area, snow extent and grain size on a spatial grid of 300 m. The algorithm also incorporated cloud screening and atmospheric correction procedures over snow surfaces. We present validation results using ground measurements from Antarctica, the Greenland ice sheet and the French Alps. We find the spectral albedo retrieved with accuracy of better than 3% on average, making our retrievals sufficient for a variety of applications. Broadband albedo is retrieved with the average accuracy of about 5% over snow. Therefore, the uncertainties of satellite retrievals are close to experimental errors of ground measurements. The retrieved surface grain size shows good agreement with ground observations. Snow specific surface area observations are also consistent with our OLCI retrievals. We present snow albedo and grain size mapping over the inland ice sheet of Greenland for areas including dry snow, melted/melting snow and impurity rich bare ice. The algorithm can be applied to OLCI Sentinel-3 measurements providing an opportunity for creation of long-term snow property records essential for climate monitoring and data assimilation studies-especially in the Arctic region, where we face rapid environmental changes including reduction of snow/ice extent and, therefore, planetary albedo. Article in Journal/Newspaper albedo Antarc* Antarctica Arctic Greenland Ice Sheet University of Potsdam: publish.UP Arctic Greenland The Sentinel ENVELOPE(73.317,73.317,-52.983,-52.983) Remote Sensing 11 19 2280
institution Open Polar
collection University of Potsdam: publish.UP
op_collection_id ftubpotsdam
language English
topic ddc:550
Institut für Geowissenschaften
spellingShingle ddc:550
Institut für Geowissenschaften
Kokhanovsky, Alexander
Lamare, Maxim
Danne, Olaf
Brockmann, Carsten
Dumont, Marie
Picard, Ghislain
Arnaud, Laurent
Favier, Vincent
Jourdain, Bruno
Le Meur, Emmanuel
Di Mauro, Biagio
Aoki, Teruo
Niwano, Masashi
Rozanov, Vladimir
Korkin, Sergey
Kipfstuhl, Sepp
Freitag, Johannes
Hoerhold, Maria
Zuhr, Alexandra (Dr.)
Vladimirova, Diana
Faber, Anne-Katrine
Steen-Larsen, Hans Christian
Wahl, Sonja
Andersen, Jonas K.
Vandecrux, Baptiste
van As, Dirk
Mankoff, Kenneth D.
Kern, Michael
Zege, Eleonora
Box, Jason E.
Retrieval of Snow Properties from the Sentinel-3 Ocean and Land Colour Instrument
topic_facet ddc:550
Institut für Geowissenschaften
description The Sentinel Application Platform (SNAP) architecture facilitates Earth Observation data processing. In this work, we present results from a new Snow Processor for SNAP. We also describe physical principles behind the developed snow property retrieval technique based on the analysis of Ocean and Land Colour Instrument (OLCI) onboard Sentinel-3A/B measurements over clean and polluted snow fields. Using OLCI spectral reflectance measurements in the range 400-1020 nm, we derived important snow properties such as spectral and broadband albedo, snow specific surface area, snow extent and grain size on a spatial grid of 300 m. The algorithm also incorporated cloud screening and atmospheric correction procedures over snow surfaces. We present validation results using ground measurements from Antarctica, the Greenland ice sheet and the French Alps. We find the spectral albedo retrieved with accuracy of better than 3% on average, making our retrievals sufficient for a variety of applications. Broadband albedo is retrieved with the average accuracy of about 5% over snow. Therefore, the uncertainties of satellite retrievals are close to experimental errors of ground measurements. The retrieved surface grain size shows good agreement with ground observations. Snow specific surface area observations are also consistent with our OLCI retrievals. We present snow albedo and grain size mapping over the inland ice sheet of Greenland for areas including dry snow, melted/melting snow and impurity rich bare ice. The algorithm can be applied to OLCI Sentinel-3 measurements providing an opportunity for creation of long-term snow property records essential for climate monitoring and data assimilation studies-especially in the Arctic region, where we face rapid environmental changes including reduction of snow/ice extent and, therefore, planetary albedo.
format Article in Journal/Newspaper
author Kokhanovsky, Alexander
Lamare, Maxim
Danne, Olaf
Brockmann, Carsten
Dumont, Marie
Picard, Ghislain
Arnaud, Laurent
Favier, Vincent
Jourdain, Bruno
Le Meur, Emmanuel
Di Mauro, Biagio
Aoki, Teruo
Niwano, Masashi
Rozanov, Vladimir
Korkin, Sergey
Kipfstuhl, Sepp
Freitag, Johannes
Hoerhold, Maria
Zuhr, Alexandra (Dr.)
Vladimirova, Diana
Faber, Anne-Katrine
Steen-Larsen, Hans Christian
Wahl, Sonja
Andersen, Jonas K.
Vandecrux, Baptiste
van As, Dirk
Mankoff, Kenneth D.
Kern, Michael
Zege, Eleonora
Box, Jason E.
author_facet Kokhanovsky, Alexander
Lamare, Maxim
Danne, Olaf
Brockmann, Carsten
Dumont, Marie
Picard, Ghislain
Arnaud, Laurent
Favier, Vincent
Jourdain, Bruno
Le Meur, Emmanuel
Di Mauro, Biagio
Aoki, Teruo
Niwano, Masashi
Rozanov, Vladimir
Korkin, Sergey
Kipfstuhl, Sepp
Freitag, Johannes
Hoerhold, Maria
Zuhr, Alexandra (Dr.)
Vladimirova, Diana
Faber, Anne-Katrine
Steen-Larsen, Hans Christian
Wahl, Sonja
Andersen, Jonas K.
Vandecrux, Baptiste
van As, Dirk
Mankoff, Kenneth D.
Kern, Michael
Zege, Eleonora
Box, Jason E.
author_sort Kokhanovsky, Alexander
title Retrieval of Snow Properties from the Sentinel-3 Ocean and Land Colour Instrument
title_short Retrieval of Snow Properties from the Sentinel-3 Ocean and Land Colour Instrument
title_full Retrieval of Snow Properties from the Sentinel-3 Ocean and Land Colour Instrument
title_fullStr Retrieval of Snow Properties from the Sentinel-3 Ocean and Land Colour Instrument
title_full_unstemmed Retrieval of Snow Properties from the Sentinel-3 Ocean and Land Colour Instrument
title_sort retrieval of snow properties from the sentinel-3 ocean and land colour instrument
publishDate 2019
url https://publishup.uni-potsdam.de/frontdoor/index/index/docId/48525
https://doi.org/10.3390/rs11192280
long_lat ENVELOPE(73.317,73.317,-52.983,-52.983)
geographic Arctic
Greenland
The Sentinel
geographic_facet Arctic
Greenland
The Sentinel
genre albedo
Antarc*
Antarctica
Arctic
Greenland
Ice Sheet
genre_facet albedo
Antarc*
Antarctica
Arctic
Greenland
Ice Sheet
op_relation https://publishup.uni-potsdam.de/frontdoor/index/index/docId/48525
https://doi.org/10.3390/rs11192280
op_rights info:eu-repo/semantics/closedAccess
op_doi https://doi.org/10.3390/rs11192280
container_title Remote Sensing
container_volume 11
container_issue 19
container_start_page 2280
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