Landsat 8 oli broadband albedo validation in antarctica and greenland
The albedo is a fundamental component of the processes that govern the energy budget, and particularly important in the context of climate change. However, a satellite-based high-resolution (30 m) albedo product which can be used in the polar regions up to 82.5◦ latitude during the summer seasons is...
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ftunivroma3iris:oai:iris.uniroma3.it:11590/390912 2024-01-14T10:00:51+01:00 Landsat 8 oli broadband albedo validation in antarctica and greenland Traversa G. Fugazza D. Senese A. Frezzotti M. Traversa, G. Fugazza, D. Senese, A. Frezzotti, M. 2021 http://hdl.handle.net/11590/390912 https://doi.org/10.3390/rs13040799 https://www.mdpi.com/2072-4292/13/4/799 eng eng info:eu-repo/semantics/altIdentifier/wos/WOS:000624429300001 volume:13 issue:4 firstpage:1 lastpage:19 numberofpages:19 journal:REMOTE SENSING http://hdl.handle.net/11590/390912 doi:10.3390/rs13040799 info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85102059604 https://www.mdpi.com/2072-4292/13/4/799 info:eu-repo/semantics/openAccess Albedo Antarctica Cryosphere Greenland Landsat Polar region Remote sensing info:eu-repo/semantics/article 2021 ftunivroma3iris https://doi.org/10.3390/rs13040799 2023-12-20T17:54:13Z The albedo is a fundamental component of the processes that govern the energy budget, and particularly important in the context of climate change. However, a satellite-based high-resolution (30 m) albedo product which can be used in the polar regions up to 82.5◦ latitude during the summer seasons is lacking. To cover this gap, in this study we calculate satellite-based broadband albedo from Landsat 8 OLI and validate it against broadband albedo measurements from in situ stations located on the Antarctic and Greenland icesheets. The model to derive the albedo from raw satellite data includes an atmospheric and topographic correction and conversion from narrow-band to broadband albedo, and at each step different options were taken into account, in order to provide the best combination of corrections. Results, after being cleaned from anomalous data, show a good agreement with in situ albedo measurements, with a mean absolute error between in situ and satellite albedo of 0.021, a root mean square error of 0.026, a standard deviation of 0.015, a correlation coefficient of 0.995 (p < 0.01) and a bias estimate of −0.005. Considering the structure of the model, it could be applied to data from previous sensors of the Landsat family and help construct a record to analyze albedo variations in the polar regions. Article in Journal/Newspaper Antarc* Antarctic Antarctica Greenland Anagrafe della Ricerca d'Ateneo (Universitá degli studi Roma Tre) Antarctic Greenland The Antarctic Remote Sensing 13 4 799 |
institution |
Open Polar |
collection |
Anagrafe della Ricerca d'Ateneo (Universitá degli studi Roma Tre) |
op_collection_id |
ftunivroma3iris |
language |
English |
topic |
Albedo Antarctica Cryosphere Greenland Landsat Polar region Remote sensing |
spellingShingle |
Albedo Antarctica Cryosphere Greenland Landsat Polar region Remote sensing Traversa G. Fugazza D. Senese A. Frezzotti M. Landsat 8 oli broadband albedo validation in antarctica and greenland |
topic_facet |
Albedo Antarctica Cryosphere Greenland Landsat Polar region Remote sensing |
description |
The albedo is a fundamental component of the processes that govern the energy budget, and particularly important in the context of climate change. However, a satellite-based high-resolution (30 m) albedo product which can be used in the polar regions up to 82.5◦ latitude during the summer seasons is lacking. To cover this gap, in this study we calculate satellite-based broadband albedo from Landsat 8 OLI and validate it against broadband albedo measurements from in situ stations located on the Antarctic and Greenland icesheets. The model to derive the albedo from raw satellite data includes an atmospheric and topographic correction and conversion from narrow-band to broadband albedo, and at each step different options were taken into account, in order to provide the best combination of corrections. Results, after being cleaned from anomalous data, show a good agreement with in situ albedo measurements, with a mean absolute error between in situ and satellite albedo of 0.021, a root mean square error of 0.026, a standard deviation of 0.015, a correlation coefficient of 0.995 (p < 0.01) and a bias estimate of −0.005. Considering the structure of the model, it could be applied to data from previous sensors of the Landsat family and help construct a record to analyze albedo variations in the polar regions. |
author2 |
Traversa, G. Fugazza, D. Senese, A. Frezzotti, M. |
format |
Article in Journal/Newspaper |
author |
Traversa G. Fugazza D. Senese A. Frezzotti M. |
author_facet |
Traversa G. Fugazza D. Senese A. Frezzotti M. |
author_sort |
Traversa G. |
title |
Landsat 8 oli broadband albedo validation in antarctica and greenland |
title_short |
Landsat 8 oli broadband albedo validation in antarctica and greenland |
title_full |
Landsat 8 oli broadband albedo validation in antarctica and greenland |
title_fullStr |
Landsat 8 oli broadband albedo validation in antarctica and greenland |
title_full_unstemmed |
Landsat 8 oli broadband albedo validation in antarctica and greenland |
title_sort |
landsat 8 oli broadband albedo validation in antarctica and greenland |
publishDate |
2021 |
url |
http://hdl.handle.net/11590/390912 https://doi.org/10.3390/rs13040799 https://www.mdpi.com/2072-4292/13/4/799 |
geographic |
Antarctic Greenland The Antarctic |
geographic_facet |
Antarctic Greenland The Antarctic |
genre |
Antarc* Antarctic Antarctica Greenland |
genre_facet |
Antarc* Antarctic Antarctica Greenland |
op_relation |
info:eu-repo/semantics/altIdentifier/wos/WOS:000624429300001 volume:13 issue:4 firstpage:1 lastpage:19 numberofpages:19 journal:REMOTE SENSING http://hdl.handle.net/11590/390912 doi:10.3390/rs13040799 info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85102059604 https://www.mdpi.com/2072-4292/13/4/799 |
op_rights |
info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.3390/rs13040799 |
container_title |
Remote Sensing |
container_volume |
13 |
container_issue |
4 |
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799 |
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