利用FY-3卫星MWRI数据探测海冰分布

详细信息    查看全文 | 推荐本文 |

英文篇名：Sea Ice Distribution Detection Based on FY-3 Satellite MWRI Data 作者：吴展开 ; 王星东 ; 王成 英文作者：WU Zhankai;WANG Xingdong;WANG Cheng;College of Information Science and Engineering,Henan University of Technology;Institute of Remote Sensing and Digital Earth,Chinese Academy of Sciences; 关键词：FY-3 ; Otsu算法 ; 海冰分布 ; 极化差 ; MWRI 英文关键词：FY-3;;Otsu algorithm;;sea ice distribution;;polarization;;MWRI 中文刊名：CHTB 英文刊名：Bulletin of Surveying and Mapping 机构：河南工业大学信息科学与工程学院;中国科学院遥感与数字地球研究所; 出版日期：2018-10-25 出版单位：测绘通报 年：2018 期：No.499 基金：国家自然科学基金(41606209);; 中国科学院海洋环流与波动重点实验室开放基金(KLOCW1805);; 国家海洋局海洋大气化学与全球变化重点实验室开放基金(GCMAC1605);; 医学光电科学与技术教育部重点实验室开放基金(JYG1707) 语种：中文; 页：CHTB201810013 页数：6 CN：10 ISSN：11-2246/P 分类号：60-64+69

摘要

基于风云3卫星(FY-3)微波成像仪(MWRI) 19 GHz数据提出了一种探测北极海冰分布的新方法,即利用海水和海冰在19 GHz频段极化差异最大的特性,通过大津法(Otsu算法)对19 GHz的极化差进行处理得到海水和海冰分类阈值,进而获取海冰分布。以2016年1月数据为例进行结果反演,并与美国冰雪数据中心(NSIDC)提供的结果进行了对比验证。结果表明:基于MWRI数据得到的1月平均海冰范围为12.905×106km~2,NSIDC结果为13.493×106km~2,二者仅差4.35%;且二者海冰范围日增长率比较接近,分别为0.038 4×10~6和0.041 9×106km~2。因此基于19 GHz极化差结合Otsu算法的北极海冰分布探测方法是可行的。
        Based on the MWRI 19 GHz data from the FY-3 microwave imager( MWRI),a new method for detecting the distribution of Arctic sea ice is proposed,using the most polarized characteristics of seawater and sea ice at 19 GHz.Then the polarization difference of 19 GHz is processed by Otsu algorithm to get the classification threshold of seawater and sea ice,and the Arctic sea ice distribution is obtained.The results of sea ice distribution are obtained by taking the data of January 2016 as an example to verify the distribution results of Arctic ice distribution with the North American Ice Data Center( NSIDC).The results show that the average sea ice extent in January based on FY-3 MWRI is 12.905×10~6 km~2,and the sea ice extent provided by NSIDC is 13.493×106 km~2,only a difference of 4.35%.And the daily growth rate of the sea ice extent are 0.038 4× 10~6 and 0.041 9× 106 km~2,respectively.Therefore,it is feasible to detect Arctic sea ice distribution based on the difference of 19 GHz vertical polarization and horizontal polarization combined with Otsu algorithm.

引文

[1]谭继强,詹庆明,殷福忠,等.面向极地海冰变化监测的卫星遥感技术研究进展[J].测绘与空间地理信息,2014,37(4):23-31.
    [2]KANG D,IM J,LEE M I,et al.The MODIS Ice Surface Temperature Product as an Indicator of Sea Ice Minimum over the Arctic Ocean[J].Remote Sensing of Environment,2014,152:99-108.
    [3]LETTERLY A,KEY J,LIU Y H.The Influence of Winter Cloud on Summer Sea Ice in the Arctic,1983-2013[J].Journal of Geophysical Research:Atmospheres,2016,121:2178-2187.
    [4]李振福,尤雪,王文雅,等.北极东北航线集装箱运输的经济性分析[J].集美大学学报(哲社版),2015,18(1):34-40.
    [5]苏洁,郝光华,叶鑫欣,等.极区海冰密集度AMSR-E数据反演算法的试验与验证[J].遥感学报,2013,17(3):504-513.
    [6]ANDERSEN S,TONBOE R,KALESCHKE L,et al.Intercomparison of Passive Microwave Sea Ice Concentration Retrievals over the High-concentration Arctic Sea Ice[J].Journal of Geophysical Research:Oceans,2007,112(C8):207-220.
    [7]CAVALIERI D J,GLOERSEN P,CAMPBELL W.Determination of Sea Ice Parameters with the Nimbus 7SMMR[J].Journal of Geophysical Research:Atmospheres,1984,89(D4):5355-5369.
    [8]COMISO J C.Characteristics of Arctic Winter Sea Ice from Satellite Multispectral Microwave Observations[J].Journal of Geophyspheric Research:Oceans,1986,91(C1):975-994.
    [9]MARKUS T,CAVALIERI D J.An Enhancement of the NASA Team Sea Ice Algorithm[J].IEEE Transactions on Geoscience and Remote Sensing,2000,38(3):1387-1398.
    [10]张翔,王振占,谌华.一种利用HY-2卫星扫描微波辐射计数据反演极地海冰密集度的算法[J].遥感技术与应用,2012,27(6):912-918.
    [11]KERN S,HEYGSTER G.Sea-ice Concentration Retrieval in the Antarctic Based on the SSM/I 85.5 GHz polarization[J].Annals of Glaciology,2001,33(1):109-114.
    [12]SVENDSEN E,MATZLER C,GRENFELL T C.A Model for Retrieving Total Sea Ice Concentration from a Spaceborne Dual-polarized Passive Microwave Instrument Operating near 90 GHz[J].International Journal on Remote Sensing,2001,8(10):1479-1487.
    [13]KERN S,KALESCHKE L,CLAUSI D A.A Comparison of two 85 GHz SSM/I Ice Concentration Algorithms with AVHRR and ERS-2 SAR Imagery[J].IEEE Transactions on Geoscience and Remote Sensing,2003,41(10):2294-2306.
    [14]张苗苗,庞小平,赵羲,等.南极海冰总覆盖范围与面积的不确定性研究[J].华中师范大学学报(自然科学版),2014,48(6):930-936.
    [15]SPREEN G,KALESCHKE L,HEYGSTER G.Sea Ice Remote Sensing Using AMSR-E 89 GHz Channels[J].Journal of Geophysical Research:Oceans,2008,113(C2):1-8.
    [16]WIEBE H,HEYGSTER G,MARKUS T.Comparison of the ASI Ice Concentration Algorithm with Landsat-7 ETM+and SAR Imagery[J].IEEE Transactions on Geoscience and Remote Sensing,2009,47(9):3008-3015.
    [17]COMISO J C,STEFFEN K.Introduction to Special Section on Large-scale Characteristics of the Sea Ice Cover from AMSR-E and Other Satellite Sensors[J]Journal of Geophysical Research:Oceans,2008,113:C02S01.DOI:10.1029/2007JC004442.
    [18]PARKINSON C L,CAVALIERI D J.Arctic Sea Ice Variability and Trends,1979-2006[J].Journal o Geophysical Research,2008,113(C7):1-28.
    [19]SERREZE M C,HOLLAND M M,STROEVE J.Perspectives on the Arctic’s Shrinking Sea-ice Cover[J].Science,2007,315(5818):1533-1536.
    [20]COMISO J C.A Rapidly Declining Perennial Sea Ice Cover in the Arctic[J].Geophysical Research Letters,2002,29(20):171-174.
    [21]RODRIGUES J.The Increase in the Length of the Icefree Season in the Arctic[J].Cold Regions Science and Technology,2009,59(1):78-101.
    [22]NORSEX G.Norwegian Remote Sensing Experiment in a Marginal Ice Zone[J].Science,1983,220(4599):781-787.
    [23]ONSTOTT R G,GRENFELL T C,MATZLER C,et al.Evolution of Microwave Sea Ice Signatures During Early Summer and Midsummer in the Marginal Ice Zone[J].Journal Geophysical Research,1987,92(C7):6825-6835.