Sea and Freshwater Ice Concentration from VIIRS on Suomi NPP and the Future JPSS Satellites
Information on ice is important for shipping, weather forecasting, and climate monitoring. Historically, ice cover has been detected and ice concentration has been measured using relatively low-resolution space-based passive microwave data. This study presents an algorithm to detect ice and estimate...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2016-06-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | http://www.mdpi.com/2072-4292/8/6/523 |
| _version_ | 1818960070953664512 |
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| author | Yinghui Liu Jeffrey Key Robert Mahoney |
| author_facet | Yinghui Liu Jeffrey Key Robert Mahoney |
| author_sort | Yinghui Liu |
| collection | DOAJ |
| description | Information on ice is important for shipping, weather forecasting, and climate monitoring. Historically, ice cover has been detected and ice concentration has been measured using relatively low-resolution space-based passive microwave data. This study presents an algorithm to detect ice and estimate ice concentration in clear-sky areas over the ocean and inland lakes and rivers using high-resolution data from the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar Orbiting Partnership (S-NPP) and on future Joint Polar Satellite System (JPSS) satellites, providing spatial detail that cannot be obtained with passive microwave data. A threshold method is employed with visible and infrared observations to identify ice, then a tie-point algorithm is used to determine the representative reflectance/temperature of pure ice, estimate the ice concentration, and refine the ice cover mask. The VIIRS ice concentration is validated using observations from Landsat 8. Results show that VIIRS has an overall bias of −0.3% compared to Landsat 8 ice concentration, with a precision (uncertainty) of 9.5%. Biases and precision values for different ice concentration subranges from 0% to 100% can be larger. |
| first_indexed | 2024-12-20T11:51:42Z |
| format | Article |
| id | doaj.art-7ab458833b774f2aaf27486d9582a41d |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-12-20T11:51:42Z |
| publishDate | 2016-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-7ab458833b774f2aaf27486d9582a41d2022-12-21T19:41:46ZengMDPI AGRemote Sensing2072-42922016-06-018652310.3390/rs8060523rs8060523Sea and Freshwater Ice Concentration from VIIRS on Suomi NPP and the Future JPSS SatellitesYinghui Liu0Jeffrey Key1Robert Mahoney2Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin-Madison, 1225 West Dayton St., Madison, WI 53706, USANOAA/NESDIS, 1225 West Dayton St., Madison, WI 53706, USANorthrop Grumman Aerospace Systems, Redondo Beach, CA 90278, USAInformation on ice is important for shipping, weather forecasting, and climate monitoring. Historically, ice cover has been detected and ice concentration has been measured using relatively low-resolution space-based passive microwave data. This study presents an algorithm to detect ice and estimate ice concentration in clear-sky areas over the ocean and inland lakes and rivers using high-resolution data from the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar Orbiting Partnership (S-NPP) and on future Joint Polar Satellite System (JPSS) satellites, providing spatial detail that cannot be obtained with passive microwave data. A threshold method is employed with visible and infrared observations to identify ice, then a tie-point algorithm is used to determine the representative reflectance/temperature of pure ice, estimate the ice concentration, and refine the ice cover mask. The VIIRS ice concentration is validated using observations from Landsat 8. Results show that VIIRS has an overall bias of −0.3% compared to Landsat 8 ice concentration, with a precision (uncertainty) of 9.5%. Biases and precision values for different ice concentration subranges from 0% to 100% can be larger.http://www.mdpi.com/2072-4292/8/6/523iceice concentrationSuomi NPPJPSSremote sensing |
| spellingShingle | Yinghui Liu Jeffrey Key Robert Mahoney Sea and Freshwater Ice Concentration from VIIRS on Suomi NPP and the Future JPSS Satellites Remote Sensing ice ice concentration Suomi NPP JPSS remote sensing |
| title | Sea and Freshwater Ice Concentration from VIIRS on Suomi NPP and the Future JPSS Satellites |
| title_full | Sea and Freshwater Ice Concentration from VIIRS on Suomi NPP and the Future JPSS Satellites |
| title_fullStr | Sea and Freshwater Ice Concentration from VIIRS on Suomi NPP and the Future JPSS Satellites |
| title_full_unstemmed | Sea and Freshwater Ice Concentration from VIIRS on Suomi NPP and the Future JPSS Satellites |
| title_short | Sea and Freshwater Ice Concentration from VIIRS on Suomi NPP and the Future JPSS Satellites |
| title_sort | sea and freshwater ice concentration from viirs on suomi npp and the future jpss satellites |
| topic | ice ice concentration Suomi NPP JPSS remote sensing |
| url | http://www.mdpi.com/2072-4292/8/6/523 |
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