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1 GeomaticsandInformationScienceofWuhanUniversity Vol.40No.11 Nov.2015 DOI: /j.whugis : (2015) , ,, ,, : 通过研究交叉检验船测样点上的 7 种不同尺度的海冰密集度数据, 发现相同时间和相同空间尺度的海冰密集度值吻合度最高, 不同时间不同尺度的海冰密集度值的相关性较弱由数据获取时间不同引起的密集度差异在高分辨率数据上体现明显真实船测点与伪船测点之间的吻合度不高, 受观测者主观因素天气条件影像处理质量和伪船测点提取方法的影响虽然伪船测点方法在海冰边界研究中具有快速大面积提取边界点的优势, 但需要控制提取算法中的误差传播 : 海冰密集度 ;AMSR-E;MODIS; 海冰边界 :P228.41;TP751 :A WorbyComiso [6] [1] ASPeCt(Antarcticseaice, processesandclimate),,,, [2],, SMM/I 15%, [3], Ozsoy-Cicek [12] 2007,,, (NICiceedge)AMSR-E(ad- vnced microwave scanning radiometerfor the [4] earthobservingsystem),, 15% (seaiceconcentra- tion,sic), [5-10],, 15% 15% 0.1% [6], 26, 20% [11] Landsat-7ETM+ AMSR-E [13], : : ( ); ( ); (GCMAC1305); (CHINARE ) :,,, xi.zhao@whu.edu.cn :,, pxp@whu.edu.cn

40 11 : 1461, 1km,,Zhao, [14], 10% MODIS(moderate-resolutionimaging spectroradiometer), ASPeCt SR-E, 2002,2005 (htp://aspect.antarctica. gov.au/data/aspectalvoys obsmindist6.

2 40 11 : 1461, 1km,,Zhao, [14], 10% MODIS(moderate-resolutionimaging spectroradiometer), ASPeCt SR-E, 2002,2005 (htp://aspect.antarctica. gov.au/data/aspectalvoys obsmindist6. txt) (SIMBASeptember-October2007 [12] ) 2007 ASPeCt, MODIS 1781, 81 10%, 7 (1 10%, ), 8 27 MODIS 1 SR-E ~ ,, ASPeCt AMSR-E/Aqua Daily L312.5km BrightnessTemperature,SeaIceConcentration, AM- EOSAqua, 2002~ MODIS 6 MODIS & Snow DepthPolarGrids (AE SI12), 27, 4 (NationalSnow & 7, AMSR-E(as- IceDataCenter,htps://nsidc.org) AE SI12 cendingnt2 ascendingbba dailynt2 daily, (dailyaver- BBA) MODIS aged) (ascendingaveraged) (de- (RSO) (PSO) scendingaveraged), AMSR-E 12.5km, 1.1 ASPeCt ASPeCt rithm (BBA) [17] 412.5km , ascendingnt2 as- AS- cendingbba dailynt2 dailybba PeCt, [6] AM-, 1.2 AMSR-E/Aqua AMSR-E NASA, 5~50km :NA- SATeam2 (NT2) [16] Bootstrap Basic Algo- 1 ASPeCt (2002~2005,2007) Fig.1 TrackofASPeCtRSOin8CruisesBetween and2007

1462 201511 1.3 MODIS/Aqua Aqua AMSR-E MODIS Terra Aqua, 0.4~14.5μm 36, 250m 500m 1000m, 2330km AMSR- E Aqua, MODIS/,AS- PeCt MODIS/Aqua2002 ~20052007, 6, 27,6 MODIS 2 2 6MODIS/Aqua Fig.

3 MODIS/Aqua Aqua AMSR-E MODIS Terra Aqua, 0.4~14.5μm 36, 250m 500m 1000m, 2330km AMSR- E Aqua, MODIS/,AS- PeCt MODIS/Aqua2002 ~ , 6, 27,6 MODIS 2 2 6MODIS/Aqua Fig.2 LocationsoftheSix MODIS/AquaScenesintheAntarctic MODIS, 3 4 L1B MYD 02 Level-1B CalibratedGeolocationDataSet, Atmos- pherearchiveanddistributionsystem (htp:// ladsweb.nascom.nasa.gov) MODIS/ 3) α=0.331b B [18] Aqua 6, B 4,3 B 1 B 3 B 4, [14,15] α; ( ) 4, ),, (newice,nilas), 1) MODIS, 1 (0.620~0.670μm) 3(0.459~0.479μm) 250m, 3 ; 2) MODIS 7, ; (younggreyice,younggrey-whiteice), (first-yearice <0.7m, first-yearice>0.7 m, ) 4(0.459~0.479μm), [19],4

40 11 : 1463 & ( 4) 0.07, 4(a)4(b) 0.17, (0.07+0.17)/2=0.12, : (R 2 a =0.82R 2 b =0.96) MODIS (α<0.12), (0.12 α< 0.24), (0.24 α<0.46), (0.46 α) 5) ( 1),BBA NT2 ( 0), 250m AMSR-E/AquaDailyL3, 6) 12.

4 40 11 : 1463 & ( 4) 0.07, 4(a)4(b) 0.17, ( )/2=0.12, : (R 2 a =0.82R 2 b =0.96) MODIS (α<0.12), (0.12 α< 0.24), (0.24 α<0.46), (0.46 α) 5) ( 1),BBA NT2 ( 0), 250m AMSR-E/AquaDailyL3, 6) 12.5km AMSR-E NT2-BBA 0, 7%, 12.5km 4(c)4(d) MODIS 1.4 MODIS/Aqua PSO PSO MODIS Zhao [14] MODIS,,, Ascending NT2 AMSR-E,, PSO MODIS,, MODIS Aqua,, MODIS, 1km (R 2 c>r d) 2 [14], MODIS 4(e)4(f) - 2km, ascendingnt2 daily 1km, NT2, 0.99, PSO 2km 4%,, (12.5km) (3, ; 1, 0),, (250m ) 1km, PSO 3 Fig.3 1km ;2 RSO PSO, MovingAverageFilterandthe1km RadiusCircle 2 AMSR-E NT2, 9%, [14] AMSR-E, MODIS, RSO PSO, :1 RSO,PSO 13:30 MODIS, 13h 13h 2km, RSO PSO, MODIS, 2.1, 27 7, ascending NT2 ascending BBA 4(g)4(h) daily NT2 dailybba RSO PSO MODIS,, NT2,BBA 4 : &, &, &, R 2 h =0.63, [10]

5 ; Y=X;R 2 ;Bias(%) ;RSME(%) 4 Fig.4 CorrelationsofVariousSICDerivedfrom DiferentDataSourcesatthe Locationof27RSOSamplingPoints % 1781 ASPeCt, 8 1 Tab.1 StatisticsofIceEdgesDeterminedbythe 8 AM- NorthernmostOccurenceof10% RSOSICinthe8Cruises SR-E NT2 15% AM- SR-E NT , 6 AMSR-E NT E,63.76 S 0.15 E, S E, S 0 2 0, 10% E,71.96 S 0 4 [12,14], E, S W,57.95 S 9 1,,, NT2 / W,62.2 S W, S 0 4

6 40 11 : SIMBA ticseaiceandclimate[j].advancesin Earth Sci-, ence,2005,20: (,,. [J]. 10% RSO,2005,20: W, S, frazil; 3 [3] MaLijuan,LuLonghua,BianLingen.Spatio-tem- RSO 0, W, poralcharacterofantarcticseaice Variation[J]. S 30%, Shuga ChineseJournalof Polar Research,2004,16(1): 10%,frazil20%, 29-37(,,., W, [J].,2004,16(1):29-37) S 15% AMSR-E NT2 [4] XieSimei,ZouBin,WangYi.Long-rangeVariation 50km, 28km Trendofthe AntarcticSeaIce[J].Marine Fore- [14] casts,1996(3):21-29(,,. [J].,1996(3):21-29) 15% AMSR-E ASI 10km [5] LeeH,Han H.EvaluationofSSM/IandAMSR-E, AMSR-E NT2 SeaIceConcentrationsinthe AntarcticSpring U- AMSR-E ASI6.25km ;, singkompsat-1eocimages[j].ieee Trans- RSO PSO AMSR-E actionson Geoscience & RemoteSensing,2008,46 (7): ASPeCt AM- 2004,92(1): [7] KernS,KaleschkeL,ClausiD A.A Comparison SR-E MODIS, of Two 85-GHz SSM/IIce Concentration Algo- 27, rithmswithavhrranders-2sarimagery[j]. IEEE Transactionson Geoscienceand RemoteSens-, ing,2003,41(10): [8] ShokrM,MarkusT.ComparisonofNASA Team2, and AES-York Ice Concentration Algorithms A- gainstoperationalicechartsfromthecanadianice,12.5km Service[J].IEEE Transactionson Geoscience &, 2km RemoteSensing,2006,44(8): [9] ParkinsonCL,ComisoJC.AntarcticSeaIcePa-, rametersfrom AMSR-E Data Using Two Tech-, niquesand Comparisons withseaicefrom SSM/I, [J].Journalof GeophysicalResearch,2008,113 MODIS (C2): [10]Beitsch A,KernS,KaleschkeL.Comparisonof, SSM/Iand AMSR-E SeaIce Concentrations with (1781 ASPeCtShip Observations Around Antarctica[J]. 8), IEEE Transactionson Geoscience & RemoteSens- ing,2015,53(4): [11]CaoYajing,LiuQinyu,GaoGuoping.TheInternnual, VariationoftheSeaIce ConcentrationattheIce EdgeandtheEkmanTransportDrivenbythe West- [1] TurnerJ,BindschadlerR A,ConveyP,etal.Ant- arcticclimate Changeandthe Environment[M]. Cambridge:SCAR,2009 [2] KangJiancheng,TangShulin,LiuLeibao.Antarc- [6] WorbyA P,ComisoJC.StudiesoftheAntarctic SeaIceEdgeandIceExtentfromSateliteandShip Observations[J].RemoteSensingof Environment, erliesinantarctica[j].periodicalof Ocean Univer- sityof China,2005,35(5): (,,. Ekman [J].,2005,35(5): ) [12]Ozsoy-CicekB,AckleySF,WorbyA,etal.Ant-

7 arcticsea-iceextentsandconcentrations:compari- sonofsateliteandship MeasurementsfromInter- nationalpolaryearcruises[j].annalsof Glaciol- ogy,2011,52(57): [13]XiYing,SunBo,LiXin.AssessmentofAMSR-E ASISeaIceConcentrationand Landsat-7 ETM + Imagery[J].Journalof RemoteSensing,2013,17 (3): (,,. [17]ComisoJC.SSM/ISeaIceConcentrations Using Landsat-7ETM+ AMSR-E uct,modisand Pseudo-Ship Observationsofthe AntarcticSea-IceEdge[J].Annalsof Glaciology, 2014,56(69):45-52 [J].,2013,17(3): ) [14]ZhaoXi,Su Haoyue,Stein A,etal.Comparison BetweenAMSR-E ASISea-IceConcentrationProd- [15]ZhangXin,ZhouChunxia,EDongchen,etal.Moni- toringofantarcticseaicebasedonthemultichan- nelmodis Data[J].Geomaticsand Information Scienceof Wuhan University,2014,39(10): (,,,.MODIS [J]. actionson Geoscienceand RemoteSensing,2000,38 (3): thebootstrapalgorithm[c].nasa GoddardSpace Flight Center Reference Publication, Greenbelt, MD,1995 [18]LiangS,ShueyCJ,RussA L,etal.Narrowband tobroadbandconversionsoflandsurfacealbedo: I.Validation[J].RemoteSensingof Environment, 2002,84:25-41 arcticseaicezone[j].journalof Climate,2005, 18: IntercomparisonofMulti-SourcesSeaIce ConcentrationDatainAntarctic ZHAO Xi 1 SU Haoyue 1,2 SHI Zhongyu 1 PANG Xiaoping 1 1 ChineseAntarcticCenterofSurveyingand Mapping,WuhanUniversity,Wuhan430079,China 2 PatentExaminationCooperation HubeiCenterofthePatentOfice,StateIntelectualPropertyOfice,Wuhan430070,China,2014,39(10): ) [16] Markus T,CavalieriD.An Enhancementofthe NASA Team SeaIceAlgorithm[J].IEEE Trans- [19]BrandtR,WarrenSG.SurfaceAlbedooftheAnt- Abstract:Thisstudymadecomprehensivecomparisonofseaiceconcentrationderivedfromshipobser- vations,opticalandpassivemicrowaveimages.seventypesofsicderivedfrom AMSR-Eimagesand MODISimageswerecomparedwithRSOat27samplepointsbetween2002and2007.Thecorrelation betweensicderivedfromsynchronousdataobservedatthesamespatialscalehadhighercorrelation coeficientsthantheothers,whereassicsobservedatdiferenttimesandscalesdisplayedlargeincon- sistencies.thecorrelationbetweensicderivedfromdataobservedatthesamespatialscalebutatdif- ferenttimeswereafectedbythespatialresolution.thersohadconsiderablylargediferenceswith thepso,thesubjectivityinevisualestimation,weatherconditions,qualityoftheimageclassifica- tion,andextraction methodalatributetotheirdiferences.althoughthepseudoshipobservation extractionmethodishelpfultogeneratelargenumberofsamplesattheseaiceedges,errorpropaga- tionmustbecontroledintheextractionprocess. Keywords:seaiceconcentration;AMSR-E;MODIS;seaiceedge Firstauthor:ZHAO Xi,PhD,specializesinpolarseaiceremotesensinganduncertaintyofspatialdata. xi.zhao@whu.edu.cn Correspondingauthor:PANG Xiaoping,PhD,professor, pxp@whu.edu.cn Foundationsupport:TheNationalNaturalScienceFoundationofChina,No ;theSpecializeResearchFundfortheDoctoralPro- gramofhighereducationofchina,no ;thefundofkeylaboratoryofglobalchangeand Marine-AtmosphericChem- istry,soa,no.gcmac1305;thechinesepolarenvironmentcomprehensiveinvestigation & AssessmentProgrammes,No.CHIN- ARE

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NP [11] 7) 4)~ 6) ( ) : Kirk- patrick [26] 1 Fig.1 TextureMergingSketch Map ) 2) 3) 1 4) 5) 40 3 2015 3 GeomaticsandInformationScienceofWuhanUniversity Vol.40No.3 March2015 DOI:10.13203/j.whugis20140231 :1671-8860(2015)03-0347-06 1 1 1 1 430079 : : :P208TP751 :A ISOMAP [1] [2] [25] [3] [4-10]