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1、34AutomatedRemoteSensingwithNearInfraredReflectanceSpectra:CarbonateRecognitionJosephRamsey,PaulGazis,TedRoush,PeterSpirtesandClarkGlymourInorder,theassociationsoftheauthorsare:DepartmentofPhilosophy,CarnegieMellonUniversity,Pittsburgh,PA(jdramsey@andrew.cmu
2、.edu);NASAAmesResearchCenter,MountainView,CA(troush@mail.arc.nasa.gov);NASAAmesResearchCenter,MountainView,CA(pgazis@mail.arc.nasa.gov);DepartmentofPhilosophy,CarnegieMellonUniversity,Pittsburgh,PA(ps7z@andrew.cmu.edu);DepartmentofPhilosophyandCenterforAutom
3、atedLearningandDiscovery,CarnegieMellonUniversity;andDepartmentofPhilosophy,CarnegieMellonUniversityandInstituteforHumanandMachineCognition,UniversityofWestFlorida(cg09@andrew.cmu.edu).Questionsandcommentsshouldbedirectedtothefirstorlastauthors.Thisresearchw
4、assupportedbyagranttothelastauthorfromtheNASAAmesResearchCenter(AwardNumberNCC2-1026)andtheNASAAISRPprogram(AwardNumberNAG5-9309).AbstractReflectancespectroscopyisastandardtoolforstudyingthemineralcompositionofrockandsoilsamplesandforremotesensingofterrestri
5、alandextraterrestrialsurfaces.Wedescriberesearchonautomatedmethodsofmineralidentificationfromreflectancespectraandgiveevidencethatasimplealgorithm,adaptedfromawell-knownsearchprocedureforBayesnets,identifiesthemostfrequentlyoccurringclassesofcarbonateswithre
6、liabilityequaltoorgreaterthanthatofhumanexperts.Wecomparethereliabilityoftheproceduretothereliabilityofseveralotherautomatedmethodsadaptedtothesamepurpose.Evidenceisgiventhattheprocedurecanbeappliedtosomeothermineralclassesaswell.Sincetheprocedureisfastwithl
7、owmemoryrequirements,itissuitableforon-boardscientificanalysisbyorbitersorsurfacerovers.1.Introduction.Theidentificationofsurfacecompositionfromreflectancespectrahastraditionallyreliedontwomethods.Theolderofthetwoisadirectexaminationofspectrabyexperts,seekin
8、glinesorbandscharacteristicofparticularsubstances,sometimestakingaccountofoverallluminosityofthespectrum,andsometimes,withcomputationalaids,takingaccountoftheshapesofbands.Thestandardalternative
