A comparison of AMSR-E/Aqua snow products with in situ observations and MODIS snow cover products in the Mackenzie River Basin, Canada
Since 2002, global snow water equivalent (SWE) estimates have been generated using Advanced Microwave Scanning Radiometer (AMSR-E)/Aqua data. Accurate estimates of SWE are important to improve monitoring and managing of water resources in specific regions. SWE and snow map product accuracy are funct...
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Language: | English |
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2010
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Online Access: | http://www.escholarship.org/uc/item/1h8277zh |
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ftcdlib:qt1h8277zh 2023-05-15T17:09:40+02:00 A comparison of AMSR-E/Aqua snow products with in situ observations and MODIS snow cover products in the Mackenzie River Basin, Canada Tong, J Velicogna, I 2313 - 2322 2010-10-01 application/pdf http://www.escholarship.org/uc/item/1h8277zh english eng eScholarship, University of California qt1h8277zh http://www.escholarship.org/uc/item/1h8277zh Attribution (CC BY): http://creativecommons.org/licenses/by/3.0/ CC-BY Tong, J; & Velicogna, I. (2010). A comparison of AMSR-E/Aqua snow products with in situ observations and MODIS snow cover products in the Mackenzie River Basin, Canada. Remote Sensing, 2(10), 2313 - 2322. doi:10.3390/rs2102313. UC Irvine: Retrieved from: http://www.escholarship.org/uc/item/1h8277zh article 2010 ftcdlib https://doi.org/10.3390/rs2102313 2017-10-13T22:51:46Z Since 2002, global snow water equivalent (SWE) estimates have been generated using Advanced Microwave Scanning Radiometer (AMSR-E)/Aqua data. Accurate estimates of SWE are important to improve monitoring and managing of water resources in specific regions. SWE and snow map product accuracy are functions of topography and of land cover type because landscape characteristics have a strong influence on redistribution and physical properties of snow cover, and influence the microwave properties of the surface. Here we evaluate the AMSR-E SWE and derived snow map products in the Mackenzie River Basin (MRB), Canada, which is characterized by complex topography and varying land cover types from tundra to boreal forest. We compare in situ snow depth observations and Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover maps from January 2003 to December 2007 with passive microwave remotely sensed SWE from AMSR-E and derived snow cover maps. In the MRB the mean absolute error ranges from 12 mm in the early winter season to 50 mm in the late winter season and overestimations of snow cover maps based on a 1 mm threshold of AMSR-E SWE varies from 4% to 8%. The optimal threshold for AMSR-E SWE to classify the pixels as snow ranges from 6 mm to 9 mm. The overall accuracy of new snow cover maps from AMSR-E varies from 91% to 94% in different sub-basins in the MRB. © 2010 by the authors. Article in Journal/Newspaper Mackenzie river Tundra University of California: eScholarship Canada Mackenzie River Remote Sensing 2 10 2313 2322 |
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Open Polar |
collection |
University of California: eScholarship |
op_collection_id |
ftcdlib |
language |
English |
description |
Since 2002, global snow water equivalent (SWE) estimates have been generated using Advanced Microwave Scanning Radiometer (AMSR-E)/Aqua data. Accurate estimates of SWE are important to improve monitoring and managing of water resources in specific regions. SWE and snow map product accuracy are functions of topography and of land cover type because landscape characteristics have a strong influence on redistribution and physical properties of snow cover, and influence the microwave properties of the surface. Here we evaluate the AMSR-E SWE and derived snow map products in the Mackenzie River Basin (MRB), Canada, which is characterized by complex topography and varying land cover types from tundra to boreal forest. We compare in situ snow depth observations and Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover maps from January 2003 to December 2007 with passive microwave remotely sensed SWE from AMSR-E and derived snow cover maps. In the MRB the mean absolute error ranges from 12 mm in the early winter season to 50 mm in the late winter season and overestimations of snow cover maps based on a 1 mm threshold of AMSR-E SWE varies from 4% to 8%. The optimal threshold for AMSR-E SWE to classify the pixels as snow ranges from 6 mm to 9 mm. The overall accuracy of new snow cover maps from AMSR-E varies from 91% to 94% in different sub-basins in the MRB. © 2010 by the authors. |
format |
Article in Journal/Newspaper |
author |
Tong, J Velicogna, I |
spellingShingle |
Tong, J Velicogna, I A comparison of AMSR-E/Aqua snow products with in situ observations and MODIS snow cover products in the Mackenzie River Basin, Canada |
author_facet |
Tong, J Velicogna, I |
author_sort |
Tong, J |
title |
A comparison of AMSR-E/Aqua snow products with in situ observations and MODIS snow cover products in the Mackenzie River Basin, Canada |
title_short |
A comparison of AMSR-E/Aqua snow products with in situ observations and MODIS snow cover products in the Mackenzie River Basin, Canada |
title_full |
A comparison of AMSR-E/Aqua snow products with in situ observations and MODIS snow cover products in the Mackenzie River Basin, Canada |
title_fullStr |
A comparison of AMSR-E/Aqua snow products with in situ observations and MODIS snow cover products in the Mackenzie River Basin, Canada |
title_full_unstemmed |
A comparison of AMSR-E/Aqua snow products with in situ observations and MODIS snow cover products in the Mackenzie River Basin, Canada |
title_sort |
comparison of amsr-e/aqua snow products with in situ observations and modis snow cover products in the mackenzie river basin, canada |
publisher |
eScholarship, University of California |
publishDate |
2010 |
url |
http://www.escholarship.org/uc/item/1h8277zh |
op_coverage |
2313 - 2322 |
geographic |
Canada Mackenzie River |
geographic_facet |
Canada Mackenzie River |
genre |
Mackenzie river Tundra |
genre_facet |
Mackenzie river Tundra |
op_source |
Tong, J; & Velicogna, I. (2010). A comparison of AMSR-E/Aqua snow products with in situ observations and MODIS snow cover products in the Mackenzie River Basin, Canada. Remote Sensing, 2(10), 2313 - 2322. doi:10.3390/rs2102313. UC Irvine: Retrieved from: http://www.escholarship.org/uc/item/1h8277zh |
op_relation |
qt1h8277zh http://www.escholarship.org/uc/item/1h8277zh |
op_rights |
Attribution (CC BY): http://creativecommons.org/licenses/by/3.0/ |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.3390/rs2102313 |
container_title |
Remote Sensing |
container_volume |
2 |
container_issue |
10 |
container_start_page |
2313 |
op_container_end_page |
2322 |
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1766065818089553920 |