Next Article in Journal
Multi-Temporal Sentinel-2 Data Analysis for Smallholding Forest Cut Control
Next Article in Special Issue
Fine-Scale Sea Ice Segmentation for High-Resolution Satellite Imagery with Weakly-Supervised CNNs
Previous Article in Journal
Exploring the Use of PlanetScope Data for Particulate Matter Air Quality Research
Previous Article in Special Issue
Evaluation of 2-m Air Temperature and Surface Temperature from ERA5 and ERA-I Using Buoy Observations in the Arctic during 2010–2020
 
 
Article

A Blended Sea Ice Concentration Product from AMSR2 and VIIRS

1
Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin-Madison, 1225 West Dayton St., Madison, WI 53706, USA
2
Center for Satellite Applications and Research, NOAA/NESDIS, 1225 West Dayton St., Madison, WI 53706, USA
3
National Snow and Ice Data Center, CIRES, 449 UCB, University of Colorado Boulder, Boulder, CO 80309, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Mohammed Shokr and Yufang Ye
Remote Sens. 2021, 13(15), 2982; https://doi.org/10.3390/rs13152982
Received: 5 May 2021 / Revised: 20 July 2021 / Accepted: 22 July 2021 / Published: 29 July 2021
(This article belongs to the Special Issue Polar Sea Ice: Detection, Monitoring and Modeling)
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. View Full-Text
Keywords: Arctic; sea ice concentration; melting ice; high spatial resolution; blending technique; best-linear unbiased estimator; thermal infrared; visible; NDSI; passive microwave; uncertainties; VIIRS; AMSR2; Sentinel; Synthetic Aperture Radar Arctic; sea ice concentration; melting ice; high spatial resolution; blending technique; best-linear unbiased estimator; thermal infrared; visible; NDSI; passive microwave; uncertainties; VIIRS; AMSR2; Sentinel; Synthetic Aperture Radar
Show Figures

Figure 1

MDPI and ACS Style

Dworak, R.; Liu, Y.; Key, J.; Meier, W.N. A Blended Sea Ice Concentration Product from AMSR2 and VIIRS. Remote Sens. 2021, 13, 2982. https://doi.org/10.3390/rs13152982

AMA Style

Dworak R, Liu Y, Key J, Meier WN. A Blended Sea Ice Concentration Product from AMSR2 and VIIRS. Remote Sensing. 2021; 13(15):2982. https://doi.org/10.3390/rs13152982

Chicago/Turabian Style

Dworak, Richard, Yinghui Liu, Jeffrey Key, and Walter N. Meier. 2021. "A Blended Sea Ice Concentration Product from AMSR2 and VIIRS" Remote Sensing 13, no. 15: 2982. https://doi.org/10.3390/rs13152982

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop