1 A TIME SERIES ANALYSIS TO ASSESS THE EFFECT OF SNOWPACK DYNAMICS ON SSM/I BRIGHTNESS TEMPERATURES FOR VARIOUS LAND COVERS IN GREAT LAKES AREA
Abstract- Using satellite technology to estimate snow characteristics has been employed for years. Despite considerable progress, challenges still exist with respect to accuracy and reliability. It is the aim of this study to estimate snow depth using Special Sensor Microwave (SSM/I) channels and Eq...
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ftciteseerx:oai:CiteSeerX.psu:10.1.1.628.1387 2023-05-15T17:14:21+02:00 1 A TIME SERIES ANALYSIS TO ASSESS THE EFFECT OF SNOWPACK DYNAMICS ON SSM/I BRIGHTNESS TEMPERATURES FOR VARIOUS LAND COVERS IN GREAT LAKES AREA Amir E Azar Reza Khanbilvardi Peter Romanov Hosni Ghedira David Astanehasl Prudentia G. Zikalala The Pennsylvania State University CiteSeerX Archives application/pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.628.1387 en eng http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.628.1387 Metadata may be used without restrictions as long as the oai identifier remains attached to it. https://ams.confex.com/ams/pdfpapers/100643.pdf text ftciteseerx 2016-01-08T15:19:02Z Abstract- Using satellite technology to estimate snow characteristics has been employed for years. Despite considerable progress, challenges still exist with respect to accuracy and reliability. It is the aim of this study to estimate snow depth using Special Sensor Microwave (SSM/I) channels and Equal-Area Scalable Earth Grid (EASE-GRID). The study focuses on the Great Lakes Region in the United States. Fifteen SSM/I and EASE-GRID formatted pixels were selected, each 25 by 25 kilometers in size. The pixels were selected based on latitude and land cover characteristics that would produce data significant for a comprehensive study of brightness temperature (TB) of the different SSM/I channels. The actual values for snow depth or ‘ground true data ’ were obtained from the National Climate Data Center (NCDC) and the National Operational Hydrological Remote Sensing Center (NOHRSC). The NCDC provided daily snow depth measurements reported from various stations located in the study area. The measurements were recorded and projected to match EASE-GRID formatting. The NOHRSC SNODAS data set was produced using airborne Gamma radiation and gauge measurements combined with a physical model. The data set consisted of different snow characteristics such as SWE and snow depth, both available in gridded format through the National Snow and Ice Data Center (NSIDC). SSM/I channel signatures – GTVN (19V-37V), GTH (19H-37H), and SSI (22V-85V) – were used along with SWE and Snow Depth to establish a relationship Text National Snow and Ice Data Center Unknown |
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Open Polar |
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ftciteseerx |
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English |
description |
Abstract- Using satellite technology to estimate snow characteristics has been employed for years. Despite considerable progress, challenges still exist with respect to accuracy and reliability. It is the aim of this study to estimate snow depth using Special Sensor Microwave (SSM/I) channels and Equal-Area Scalable Earth Grid (EASE-GRID). The study focuses on the Great Lakes Region in the United States. Fifteen SSM/I and EASE-GRID formatted pixels were selected, each 25 by 25 kilometers in size. The pixels were selected based on latitude and land cover characteristics that would produce data significant for a comprehensive study of brightness temperature (TB) of the different SSM/I channels. The actual values for snow depth or ‘ground true data ’ were obtained from the National Climate Data Center (NCDC) and the National Operational Hydrological Remote Sensing Center (NOHRSC). The NCDC provided daily snow depth measurements reported from various stations located in the study area. The measurements were recorded and projected to match EASE-GRID formatting. The NOHRSC SNODAS data set was produced using airborne Gamma radiation and gauge measurements combined with a physical model. The data set consisted of different snow characteristics such as SWE and snow depth, both available in gridded format through the National Snow and Ice Data Center (NSIDC). SSM/I channel signatures – GTVN (19V-37V), GTH (19H-37H), and SSI (22V-85V) – were used along with SWE and Snow Depth to establish a relationship |
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The Pennsylvania State University CiteSeerX Archives |
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Text |
author |
Amir E Azar Reza Khanbilvardi Peter Romanov Hosni Ghedira David Astanehasl Prudentia G. Zikalala |
spellingShingle |
Amir E Azar Reza Khanbilvardi Peter Romanov Hosni Ghedira David Astanehasl Prudentia G. Zikalala 1 A TIME SERIES ANALYSIS TO ASSESS THE EFFECT OF SNOWPACK DYNAMICS ON SSM/I BRIGHTNESS TEMPERATURES FOR VARIOUS LAND COVERS IN GREAT LAKES AREA |
author_facet |
Amir E Azar Reza Khanbilvardi Peter Romanov Hosni Ghedira David Astanehasl Prudentia G. Zikalala |
author_sort |
Amir E Azar |
title |
1 A TIME SERIES ANALYSIS TO ASSESS THE EFFECT OF SNOWPACK DYNAMICS ON SSM/I BRIGHTNESS TEMPERATURES FOR VARIOUS LAND COVERS IN GREAT LAKES AREA |
title_short |
1 A TIME SERIES ANALYSIS TO ASSESS THE EFFECT OF SNOWPACK DYNAMICS ON SSM/I BRIGHTNESS TEMPERATURES FOR VARIOUS LAND COVERS IN GREAT LAKES AREA |
title_full |
1 A TIME SERIES ANALYSIS TO ASSESS THE EFFECT OF SNOWPACK DYNAMICS ON SSM/I BRIGHTNESS TEMPERATURES FOR VARIOUS LAND COVERS IN GREAT LAKES AREA |
title_fullStr |
1 A TIME SERIES ANALYSIS TO ASSESS THE EFFECT OF SNOWPACK DYNAMICS ON SSM/I BRIGHTNESS TEMPERATURES FOR VARIOUS LAND COVERS IN GREAT LAKES AREA |
title_full_unstemmed |
1 A TIME SERIES ANALYSIS TO ASSESS THE EFFECT OF SNOWPACK DYNAMICS ON SSM/I BRIGHTNESS TEMPERATURES FOR VARIOUS LAND COVERS IN GREAT LAKES AREA |
title_sort |
1 a time series analysis to assess the effect of snowpack dynamics on ssm/i brightness temperatures for various land covers in great lakes area |
url |
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.628.1387 |
genre |
National Snow and Ice Data Center |
genre_facet |
National Snow and Ice Data Center |
op_source |
https://ams.confex.com/ams/pdfpapers/100643.pdf |
op_relation |
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.628.1387 |
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Metadata may be used without restrictions as long as the oai identifier remains attached to it. |
_version_ |
1766071706313555968 |