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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Online Access: | https://hdl.handle.net/11250/2740684 https://doi.org/10.3390/rs11192280 |
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ftunivbergen:oai:bora.uib.no:11250/2740684 2023-05-15T13:11:03+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 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 application/pdf https://hdl.handle.net/11250/2740684 https://doi.org/10.3390/rs11192280 eng eng MDPI urn:issn:2072-4292 https://hdl.handle.net/11250/2740684 https://doi.org/10.3390/rs11192280 cristin:1799244 Navngivelse 4.0 Internasjonal http://creativecommons.org/licenses/by/4.0/deed.no Copyright 2019 by the Authors. Remote Sensing 11:2280 19 1-43 Journal article 2019 ftunivbergen https://doi.org/10.3390/rs11192280 2023-03-14T17:41:29Z 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. publishedVersion Article in Journal/Newspaper albedo Antarc* Antarctica Arctic Greenland Ice Sheet University of Bergen: Bergen Open Research Archive (BORA-UiB) Arctic Greenland The Sentinel ENVELOPE(73.317,73.317,-52.983,-52.983) Remote Sensing 11 19 2280 |
institution |
Open Polar |
collection |
University of Bergen: Bergen Open Research Archive (BORA-UiB) |
op_collection_id |
ftunivbergen |
language |
English |
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. publishedVersion |
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 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. |
spellingShingle |
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 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 |
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 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 |
publisher |
MDPI |
publishDate |
2019 |
url |
https://hdl.handle.net/11250/2740684 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_source |
Remote Sensing 11:2280 19 1-43 |
op_relation |
urn:issn:2072-4292 https://hdl.handle.net/11250/2740684 https://doi.org/10.3390/rs11192280 cristin:1799244 |
op_rights |
Navngivelse 4.0 Internasjonal http://creativecommons.org/licenses/by/4.0/deed.no Copyright 2019 by the Authors. |
op_doi |
https://doi.org/10.3390/rs11192280 |
container_title |
Remote Sensing |
container_volume |
11 |
container_issue |
19 |
container_start_page |
2280 |
_version_ |
1766245728757219328 |