GIScience & Remote Sensing · 2015 · 18 citations · 20 references
Natural SciencesEarth SciencesOceanographyCryosphere StudiesRemote SensingSea Ice OceanographyInfrared Remote SensingRemote Sensing ImageryRemote Sensing Of IceSatellite SensorsSea Ice Remote SensingSea Ice Thickness DistributionActive Microwave SensorsReflectanceSea Ice Mapping From Satellite DataSea Ice Thickness EstimationSea Ice Thickness RetrievalSynthetic Aperture RadarSynthetic Aperture Radar ImagingSynthetic Aperture Radar Sea Ice Observation
The thicknesses of level and rough sea ice in the Bohai Sea were estimated, using Huan Jing-1 (HJ-1) charge-coupled device (CCD) images and environmental satellite (ENVISAT) advanced synthetic aperture radar (ASAR) images, respectively. Two empirical models were developed, one to describe the relationship between the reflectance of visible/near-infrared (VIS/NIR) imagery and level ice thickness and one to describe the relationship between the backscattering coefficient of synthetic aperture radar (SAR) imagery and rough ice thickness. The results showed that the VIS/NIR images were more suitable for distinguishing sea ice from sea water, and the active microwave remote sensing images were suitable for determining the difference between level and rough sea ice. The thickness of the level sea ice was logarithmically related to the VIS/NIR reflectance, and the R2 value of the fitted curve was 0.99 with a root mean square error (RMSE) of 1.0 cm. In contrast, the thickness of the rough sea ice was exponentially related to the SAR backscattering coefficient, and the R2 value of the fitted curve was 0.90 with an RMSE of 2.3 cm. The thicknesses of level and rough sea ice were then calculated using the empirical models, and the results reflected the thickness distribution of sea ice in the Bohai Sea. We concluded that high-resolution images can accurately extract the sea ice area and estimate the thickness of sea ice.
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