月尺度农作物提取中GF-1 WFV纹理特征的应用及分析-豆柴文库

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月尺度农作物提取中GF-1WFV纹理特征的应用及分析
Title:ApplicationandAnalysisofGF-1WFVTextureFeaturesinMonthly-ScaleCropExtraction
Abstract:
Withtherapiddevelopmentofremotesensingtechnology,satelliteimageryhasbecomeanessentialtoolformonitoringandanalyzingagriculturalconditions.TheGF-1(Gaofen-1)satellite,launchedbyChinainApril2013,hasprovidedhigh-resolutionsatelliteimagery,whichenablestimelyandaccuratemonitoringofcropgrowth.Inthispaper,weexploretheapplicationandanalysisoftexturefeaturesextractedfromGF-1WFV(WideFieldofView)dataatthemonthlyscaleforcropextraction.
1.Introduction
Cropextractionplaysavitalroleinmonitoringagriculturalconditions,predictingyields,andsupportingdecision-makingforagriculturalmanagement.Textureanalysisisaneffectivemethodtoextractinformationfromsatelliteimagery.TheGF-1WFVdatacanprovidedetailedspatialandtemporalinformation,whichmakesitsuitableformonitoringcropsonamonthlyscale.
2.Methodology
2.1DataCollection
GF-1WFVdataiscollected,whichconsistsofmultispectralimagesacquiredbythesatellite.Thedatacoversaspecificstudyareaandiscollectedatdifferenttimepointsoveraperiodofseveralmonths.
2.2TextureFeatureExtraction
Texturefeaturescapturethespatialpatternsandvariationswithinanimage.Inthisstudy,weapplycommonlyusedtextureanalysismethods,suchasgraylevelco-occurrencematrix(GLCM)andlocalbinarypatterns(LBP),toextractthetexturefeaturesfromGF-1WFVimages.
3.ResultsandDiscussion
3.1TextureFeaturesandCropGrowth
Theobtainedtexturefeaturescanbecorrelatedwithcropgrowthandcondition.Forexample,GLCM-basedfeatures,suchascontrastandentropy,canprovideinformationaboutthespatialvariationandcomplexityofthecropcoverage.LBP-basedfeatures,suchasuniformityandentropy,cancapturethelocalpatternsandtextureirregularitiesrelatedtocrophealthandstress.
3.2ClassificationandAccuracyAssessment
Theextractedtexturefeaturescanbeusedasinputvariablesforcropclassificationalgorithms,suchassupportvectormachines(SVM)orrandomforests(RF).Theclassificationresultscanbevalidatedandassessedusinggroundtruthdata,suchasfieldsurveysor