Abstract
A sea ice detection algorithm based on Fisher’s linear discriminant analysis is developed to segment sea ice and open water for the Ku-band scatterometer onboard the China’s Hai Yang 2A Satellite (HY-2A/SCAT). Residual classification errors are reduced through image erosion/dilation techniques and sea ice growth/retreat constraint methods. The arctic sea-ice-type classification is estimated via a time-dependent threshold derived from the annual backscatter trends based on previous HY-2A/SCAT derived sea ice extent. The extent and edge of the sea ice obtained in this study is compared with the Special Sensor Microwave Imager/Sounder (SSMIS) sea ice concentration data and the Sentinel-1 SAR imagery for verification, respectively. Meanwhile, the classified sea ice type is compared with a multi-sensor sea ice type product based on data from the Advanced Scatterometer (ASCAT) and SSMIS. Results show that HY-2A/SCAT is powerful in providing sea ice extent and type information, while differences in the sensitivities of active/passive products are found. In addition, HY-2A/SCAT derived sea ice products are also proved to be valuable complements for existing polar sea ice data products.
Highlights
Sea ice, acting as one of the critical components of the global climate system, modulates atmospheric and oceanic circulations through affecting ocean surface radiation, temperature, energy balance, and the circulation of salt flow [1]
Results have shown that HY-2A/SCAT data are capable of effectively discriminating between sea ice and open water using Fisher’s linear discriminant analysis method and image processing technology Using an algorithm similar to the one used in [5], arctic sea ice type products are produced using HY-2A derived sea ice extent based on dynamic threshold of the
The combination of these parameters is proven effective in identifying sea ice versus ocean regions and Arctic sea ice type classification
Summary
Sea ice, acting as one of the critical components of the global climate system, modulates atmospheric and oceanic circulations through affecting ocean surface radiation, temperature, energy balance, and the circulation of salt flow [1]. In 1997, Remund and Long developed an automatic sea ice and open water discrimination algorithm using Ku-Band data derived from NASA Scatterometer (NSCAT) [7,8]. Their principles were later adopted by the French Institute of Research for the Exploitation of the Sea (IFREMER). The KNMI algorithm is based on the probabilistic distances to ocean wind and sea ice geophysical model functions Later, this algorithm was improved to detect sea ice using QuikSCAT data [14,15].
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