A Blended Sea Ice Concentration Product from AMSR2 and VIIRS
Autor: | Yinghui Liu, Richard Dworak, Walter N. Meier, Jeffrey R. Key |
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Rok vydání: | 2021 |
Předmět: |
Synthetic aperture radar
Visible Infrared Imaging Radiometer Suite 010504 meteorology & atmospheric sciences Science media_common.quotation_subject 0211 other engineering and technologies 02 engineering and technology 01 natural sciences Standard deviation high spatial resolution Arctic melting ice Image resolution Sea ice concentration best-linear unbiased estimator 021101 geological & geomatics engineering 0105 earth and related environmental sciences media_common Remote sensing Sky blending technique General Earth and Planetary Sciences Environmental science sea ice concentration Satellite thermal infrared visible NDSI passive microwave uncertainties VIIRS AMSR2 Sentinel Synthetic Aperture Radar Microwave |
Zdroj: | Remote Sensing, Vol 13, Iss 2982, p 2982 (2021) Remote Sensing; Volume 13; Issue 15; Pages: 2982 |
ISSN: | 2072-4292 |
Popis: | An effective blended Sea-Ice Concentration (SIC) product has been developed that utilizes ice concentrations from passive microwave and visible/infrared satellite instruments, specifically the Advanced Microwave Scanning Radiometer-2 (AMSR2) and the Visible Infrared Imaging Radiometer Suite (VIIRS). The blending takes advantage of the all-sky capability of the AMSR2 sensor and the high spatial resolution of VIIRS, though it utilizes only the clear sky characteristics of VIIRS. After both VIIRS and AMSR2 images are remapped to a 1 km EASE-Grid version 2, a Best Linear Unbiased Estimator (BLUE) method is used to combine the AMSR2 and VIIRS SIC for a blended product at 1 km resolution under clear-sky conditions. Under cloudy-sky conditions the AMSR2 SIC with bias correction is used. For validation, high spatial resolution Landsat data are collocated with VIIRS and AMSR2 from 1 February 2017 to 31 October 2019. Bias, standard deviation, and root mean squared errors are calculated for the SICs of VIIRS, AMSR2, and the blended field. The blended SIC outperforms the individual VIIRS and AMSR2 SICs. The higher spatial resolution VIIRS data provide beneficial information to improve upon AMSR2 SIC under clear-sky conditions, especially during the summer melt season, as the AMSR2 SIC has a consistent negative bias near and above the melting point. |
Databáze: | OpenAIRE |
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