Arctic Sea Ice Type Classification by Combining CFOSCAT and AMSR-2 Data

被引:7
作者
Xu, Rui [1 ]
Zhao, Chaofang [1 ,2 ]
Zhai, Xiaochun [3 ,4 ]
Chen, Ge [1 ,2 ]
机构
[1] Ocean Univ China, Dept Marine Technol, Qingdao, Peoples R China
[2] Pilot Natl Lab Marine Sci & Technol Qingdao, Qingdao, Peoples R China
[3] Natl Satellite Meteorol Ctr, Beijing, Peoples R China
[4] FengYun Meteorol Satellite Innovat Ctr FY MSIC, Beijing, Peoples R China
关键词
sea ice type classification; CFOSCAT; AMSR-2; Arctic; SCATTEROMETER;
D O I
10.1029/2021EA002052
中图分类号
P1 [天文学];
学科分类号
0704 ;
摘要
First-year ice (FYI) and multi-year ice (MYI) are the two most common ice types in the Arctic. In this article, the classification of FYI and MYI over the Arctic region in the winter of 2019/2020 and 2020/2021 is investigated by combining the data of the scatterometer on Chinese-French Oceanography Satellite (CFOSCAT) and the Advanced Microwave Scanning Radiometer-2 (AMSR-2) based on the Tree Augmented Naive Bayes (TAN) classifier. The CFOSCAT/AMSR ice type classification results are validated by using Ocean and Sea Ice Satellite Application Facility (OSI SAF) sea ice type products, Canadian Ice Service ice charts, and synthetic-aperture radar data. The results showed that the overall MYI extent change trend retrieved from CFOSCAT/AMSR was consistent with the OSI SAF product with a correlation coefficient of 0.89 for winter of 2019/2020 and 0.88 for 2020/2021. In addition, CFOSCAT/AMSR identified a slightly larger MYI extent than OSI SAF and the average deviation between them is 10.1% for 2019/2020 while 8.3% for 2020/2021. Besides, CFOSCAT/AMSR can identify more MYI pixels when the MYI concentration is relatively low in the Western Arctic region. We also used CFOSCAT data only to retrieve ice type and found that the active and passive microwave data fusion could capture more MYI pixels located near the boundary of MYI and FYI main body, and the introduction of AMSR-2 data in ice type classification could reduce the error caused by the abnormal values of CFOSCAT parameters.
引用
收藏
页数:24
相关论文
共 48 条
  • [1] Aaboe S., 2021, VALIDATION REPORT GL
  • [2] Aaboe S., 2021, PRODUCT USER MANUAL
  • [3] Aaboe S., 2021, ALGORITHM THEORETICA
  • [4] Arctic multiyear sea ice variability observed from satellites: a review
    Bi Haibo
    Liang Yu
    Wang Yunhe
    Liang Xi
    Zhang Zehua
    Du Tingqin
    Yu Qinglong
    Huang Jue
    Kong Mei
    Huang Haijun
    [J]. JOURNAL OF OCEANOLOGY AND LIMNOLOGY, 2020, 38 (04) : 962 - 984
  • [5] Classification of Sea Ice Types in Sentinel-1 SAR Data Using Convolutional Neural Networks
    Boulze, Hugo
    Korosov, Anton
    Brajard, Julien
    [J]. REMOTE SENSING, 2020, 12 (13)
  • [6] Canadian Ice Service, 2009, **DATA OBJECT**, DOI 10.7265/N51V5BW9
  • [7] Cho K., 2020, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., VV-3-2020, P369, DOI [10.5194/isprs-annals-V-3-2020-369-2020, DOI 10.5194/ISPRS-ANNALS-V-3-2020-369-2020]
  • [8] Large Decadal Decline of the Arctic Multiyear Ice Cover
    Comiso, Josefino C.
    [J]. JOURNAL OF CLIMATE, 2012, 25 (04) : 1176 - 1193
  • [9] Comiso JC, 2008, J GEOPHYS RES-OCEANS, V113, DOI 10.1029/2007JC004255
  • [10] EUMETSAT OSI SAF Global Sea-Ice Type Near-Real-Time product-Multimission, 2020, OSI 403 DAT EXTR OSI