简介:TheSecondPitofQinshihnang'sTerra-cottaArmyUndergoesExcavationBystaffreporterCHENJIANInwhatseemstohavebeenarathermegalomaniaca...
简介:Vegetationindices(VI)areoneofthestandardscienceproductsavailablefromtheModerateResolutionImagingSpectroradiometer(MODIS),ValidationofMODIS-VIproductswasanimportantprerequisitetousingthesevariablesforglobalmodeling.Inthisstudy,validationoftheMODIS-VIproductsincludingsingle-dayMODIS,level2(gridded)dailyMODISsurfacereflectance(MOD09),16-daycompositedMODIS(MOD13)wasperformedutilizingmultisensordatafromMODIS,ThematicMapper(TM),andfieldradiometer,forarice-plantingregioninsouthernChina.Thevalidationapproachinvolvedscalingupindependentfine-graineddatasets,includinggroundmeasurementandhighspatialresolutionimagery,tothecoarserMODISspatialresolutions.The16-daycompositedMODISreflectanceandVImatchedwellwiththegroundmeasurementreflectanceandVI.TheVIofTMandMODISwerelowerthanthegroundVI.Theresultsdemonstratedtheaccuracy,reliability,andutilityoftheMODIS-VIproductsforthestudyregion.
简介:摘要利用遥感影像获取地表温度信息,对于检测地表状况和生态环境变化有重要意义。在对地观测卫星MODIS的16个热红外波段中,其中有6个波段是针对地表温度来设计的,其中第31(10.78~11.28um)和32(11.77~12.27um)与TM的第6波段区间基本相同。运用单窗算法分别对这2个波段建立方程,然后通过对Planck方程的辐射率和温度计算模拟,发现温度和辐射率近似线性相关,本文通过对MODIS遥感影像进行数据读取、辐射定标、反演温度、区域裁剪预处理,得到了研究区地表温度的空间分布变化,最后运用单窗算法对31通道的影像反演了研究区的温度分布。
简介:与逐渐地变得的产品改变了并且可以证明改善了的遥感信息,如此的产品的科学应用依靠他们的优秀评价。在象NASA(国家航空学和空间管理)那样的运作的上下文信息生产基于MODIS(中等分辨率成像分光辐射函数)在观察系统(曙光女神)地和水卫星的土上的仪器,检测产品异例的有效方法,即,为了在地球进程在产品人工制品和真实变化之间区别,被监视,是极其重要的在刺关于潜在的unreliability帮助并且通知用户社区为异例察觉的一种技术,是知道疯(中部绝对背离从中部)在经由系列分析被描述的时间的MODIS陆地产品,它能处理intra--并且在由使用原来的数据和他们的一阶的差别的疯统计的数据的内部年度的变化。这个方法被显示柔韧并且越过主要陆地产品工作,包括NDVI,活跃的火,雪盖子,和表面反射,并且它到多学科的产品的适用性被期望。
简介:Basedonacurrentfogdetectiontheory,amultibandthresholdmethodforMODISdatawasputforwardtodetectdaytimefogintheSouthChinaSea.ItusedBands1,2,18,20and31ofMODISdatatoseparatefogfromthecloudandtheseasurface.Thedigitaldetectionindexeswereasfollows.IfRB1<20%,RB2<20%andRB1>RB2,thepixelwasidentifiedtobetheseasurface.IfRB1>55%,RB2>55%andTB31<273K,thepixelwasidentifiedtobeamiddle-andhigh-levelcloud.IfIFC>20,thepixelwasclassifiedtobeseafog.ThemethodwasverifiedwithseafogdataobservedfromthecoastalregionofGuangdongduringJanuary-April2011.Outofthe13samplesofsatellitedetection,ninewereconsistentwiththesurfaceobservations,threewereidentifiedtobelow-levelthecloudaccordingtothesatellitedetectionbutfogaccordingtothesurfaceobservations,andonlyonesamplewasidentifiedtobetheoceansurfacebythesatellitedetectionbutfogbythesurfaceobservations.BecausetheMODISdatacannotpenetratethecloudorfog,themodelwasdesignedforasinglefieldofviewwhichhadonlyonelayerofcloudorfog.Itcanaccuratelydistinguishfogwhichisnotcoveredbythecloud,butitidentifiesfogascloudiftheformeriscoveredbyacloud.Generallyspeaking,themodeliseffectiveandfeasible.
简介:Forestgrowthismainlycurrentlymonitoredusingin-situmeasurementsinnortheastofChina.Toeffectivelymonitorforestgrowthdisturbanceatlargescale,weattemptedtouseremotesensingtechnique,particularly,timeseriesMODISdatafrom2004to2006.Theannualtimeseriesof8-dayenhancedvegetationindex(EVI)datasetwasgeneratedandsmoothedusingaSavitzky-Golayfilter.TheEVItrajectoryduringgrowthseasonwassimulatedusingalogisticmodel.Fromthesimulatedtrajectory,theEVIareaofgrowthseasonandannualEVIentropywerecalculated.Thesetwofactorswerecombinedtomapthedisturbanceregionsofforestgrowth.Finally,thedisturbanceregionswereverifiedusingasetofrandomsamples.Theresultindicatesthatthedisturbancepointshavedistinctivelyhigherentropyandlowerpeak.SomeofthesepointsalsoshowabruptEVIdeclineduringthemidseasonofthepeakphasesordoublepeaks.Thisapproachisdemonstratedtobefeasiblefordisturbancemonitoringofforestgrowth.
简介:基于地物光谱特征的监督分类一直是用遥感影像解译土地覆被类型的常规方法。基于可见光和近红外波段的光谱反射率构建的NDVI指数的水平高低及时序变化特征对土地覆被类型有高度敏感性和较好的指示性。本文基于时序MODIS-NDVI数据,通过合理选择训练样区对MODIS影象进行监督分类,最终实现对秦岭中部地区各种土地覆被的分类,通过与实地GPS调查数据比较,结果显示分类总体精度达到76.77%,kappa系数为67.22%,分类等级为较好。
简介:Background:Monitoringforesthealthandbiomassforchangesovertimeintheglobalenvironmentrequirestheprovisionofcontinuoussatelliteimages.However,opticalimagesoflandsurfacesaregenerallycontaminatedwhencloudsarepresentorrainoccurs.Methods:Toestimatetheactualreflectanceoflandsurfacesmaskedbycloudsandpotentialrain,3DsimulationsbytheRAPIDradiativetransfermodelwereproposedandconductedonaforestfarmdominatedbybirchandlarchinGenheCity,DaXing’AnLingMountaininInnerMongolia,China.Thecanopyheightmodel(CHM)fromlidardatawereusedtoextractindividualtreestructures(location,height,crownwidth).Fieldmeasurementsrelatedtreeheighttodiameterofbreastheight(DBH),lowestbranchheightandleafareaindex(LAI).SeriesofLandsatimageswereusedtoclassifytreespeciesandlandcover.MODISLAIproductswereusedtoestimatetheLAIofindividualtrees.CombiningalltheseinputvariablestodriveRAPID,high-resolutionopticalremotesensingimagesweresimulatedandvalidatedwithavailablesatelliteimages.Results:Evaluationsonspatialtexture,spectralvaluesanddirectionalreflectancewereconductedtoshowcomparableresults.Conclusions:Thestudyprovidesaproof-of-conceptapproachtolinklidarandMODISdataintheparameterizationofRAPIDmodelsforhightemporalandspatialresolutionsofimagereconstructioninforestdominatedareas.