測繪工程專業(yè)英語：Section 9 CONCEPTS OF REMOTE SENSING

Section9CONCEPTSOFREMOTESENSINGINTRODUCTIONRemotesensingisthescienceandartofobtaininginformationaboutanobject,area,orphenomenonthroughtheanalysisofdataacquiredbyadevicethatisnotincontactwiththeobject,area,orphenomenonunderinvestigation.Asyoureadthesewordsyouareemployingremotesensing.Youreyesareactingassensorsthatrespondtothelightreflectedfromthispage.The"data"youreyesacquireareimpulsescorrespondingtotheamountoflightreflectedfromthedarkandlightareasonthepage.Thesedataareanalyzed,orinterpreted,inyourmentalcomputertoenableyoutoexplainthedarkareasonthepageasacollectionof'lettersformingwords.Beyondthis,yourecognizethatthewordsformsentences,andinterprettheinformationthatthesentencesconvey.Inmanyrespects,remotesensingcanbethoughtofasareadingprocess.Usingvarioussensorsweremotelycollectdatathatmaybeanalyzedtoobtaininformationabouttheobjects,areas,orphenomenabeinginvestigated.Theremotelycollecteddatacanbeofmanyforms,includingvariationsinforcedistributions,acousticwavedistributions,orelectromagneticenergydistributions.Forexample,agravitymeteracquiresdataonvariationsinthedistributionoftheforceofgravity.Sonar,likeabat'snavigationsystem,obtainsdataonvariationsinacousticwavedistributions.OureyesacquiredataonvariationsinelectromagneticenergydistributionsThisbookisaboutelectromagneticenergysensorsthatarecurrentlybeingoperatedfromairborneandspaceborneplatformstoassistininventorying,mapping,andmonitoringearthresources.Thesesensorsacquiredataonthewayvariousearthsurfacefeaturesemitandreflectelectromagneticenergyandthesedataareanalyzedtoprovideinformationabouttheresourcesunderinvestigation.Figure1schematicallyillustratesthegeneralizedprocessesandelementsinvolvedinelectromagneticremotesensingofearthresources.Thetwobasicprocessesinvolvedaredataacquisitionanddataanalysis.Theelementsofthedataacquisitionprocessareenergysources(a),propagationofenergythroughtheatmosphere(b),energyinteractionswithearthsurfacefeatures(c),re-transmissionofenergythroughtheatmosphere(d),airborneand/orspacebornesensors(e),resultinginthegenerationofsensordatainpictorialand/ordigitalform(f).Inshort,weusesensorstorecordvariationsinthewayearthsurfacefeaturesreflectandemitelectromagneticenergy.Thedataanalysisprocess(g)involvesexaminingthedatausingvariousviewingandinterpretationdevicestoanalyzepictorialdata,and/oracomputertoanalyzedigitalsensordata.Referencedataabouttheresourcesbeingstudied(suchassoilsmaps,cropstatistics,orfield-checkdata)areusedwhenandwhereavailabletoassistinthedataanalysis.Withtheaidofthereferencedata,theanalystextractsinformationaboutthetype,extent,location,andconditionofthevariousresourcesoverwhichthesensordatawerecollected.Thisinformationisthencompiled(h),generallyintheformofhardcopymapsandtables,orascomputerfilesthatcanbemergedwithother"layers"ofinformationinaGeographicInformationSystem(GIS).Finally,theinformationispresentedtousers(i)whoapplyittotheirdecision-makingprocess.Intheremainderofthischapter,wediscussthebasicprinciplesunderlyingtheremotesensingprocess.Webeginwiththefundamentalsofelectromagneticenergy,thenconsiderhowtheenergyinteractswithearthsurfacefeatures.Wealsotreattherolethatreferencedataplayinthedataanalysisprocedure.Thesebasicswillpermitustoconceptualizean"ideal"remotesensingsystem.Withthatasaframework,weconsiderthelimitationsencounteredin"real"'remotesensingsystems.Attheendofthisdiscussion,thereadershouldhaveagraspofthegeneralconceptsandfoundationsofremotesensing.DATAACQUISITIONANDINTERPRETATIONUptothispoint,wehavediscussedtheprincipalsourcesofelectromagneticenergy,thepropagationof'thisenergythroughtheatmosphere,andtheinteractionofthisenergywithearthsurfacefeatures.Combined,theseFactorsresultinenergy"signals"fromwhichwewishtoextractinformation.Wenowconsidertheproceduresbywhichthesesignalsaredetected,recorded,andinterpreted.Thedetectionofelectromagneticenergycanbeperformedeitherphotographicallyorelectronically.Theprocessofphotographyuseschemicalreactionsonthesurfaceof'alightsensitivefilmtodetectenergyvariationswithinascene..Photographicsystemsoffermanyadvantages:theyarcrelativelysimpleandinexpensiveandprovideahighdegreeofspatialdetailandgeometricintegrity.Electronicsensorsgenerateanelectricalsignalthatcorrespondstotheenergyvariationsintheoriginalscene.Afamiliarexampleofanelectronicsensorisavideocamera.Althoughconsiderablymorecomplexandexpensivethanphotographicsystems,electronicsensorsoffertheadvantagesofabroaderspectralrangeofsensitivity,improvedcalibrationpotential,andtheabilitytoelectronicallytransmitdata.Bydevelopingaphotograph,weobtainarecordofitsdetectedsignals.Thus,thefilmactsasboththedetectingandtherecordingmedium.Electronicsensorsignalsaregenerallyrecordedontomagnetictape.Subsequently,thesignalsmaybeconvertedtoanimageformbyphotographingaTV-likescreendisplayofthedata,orbyusingaspecializedfilmrecorder.Inthesecases,photographicfilmisusedonlyasarecordingmedium.Inremotesensing,tiletermphotographisreservedexclusivelyforimagesthatweredetectedaswellasrecordedonfilm.Themoregenerictermimageisusedforanypictorialrepresentationofimagedata.Thus,apictorialrecordfromathermalscanner(anelectronicsensor)wouldbecalleda"thermalimage,"nota"thermalphotograph,"becausefilmwouldnotbetheoriginaldetectionmechanismfortheimage.Becausethetermimagerelatestoanypictorialproduct,allphotographsareimages.Notallimages,however,arephotographs.Wecanseethatthedatainterpretationaspectsofremotesensingcaninvolveanalysisofpictorial(image)and/ordigitaldata.Visualinterpretationofpictorialimagedatahaslongbeentheworkhorseofremotesensing.Visualtechniquesmakeuseoftheexcellentabilityofthehumanmindtoqualitativelyevaluatespatialpatternsinascene.Theabilitytomakesubjectivejudgmentsbasedonselectivesceneelementsisessentialinmanyinterpretationefforts.Visualinterpretationtechniqueshavecertaindisadvantages,however,inthattheymayrequireextensivetrainingandarelaborintensive.Inaddition,spectralcharacteristicsarenotalwaysfullyevaluatediiivisualinterpretationefforts.Thisispartlybecauseofthelimitedabilityoftheeyetodiscerntonalvaluesonanimageandthedifficultyforaninterpretertosimultaneouslyanalyzenumerousspectralimages.Inapplicationswherespectralpatternsarehighlyinformative,itisthereforepreferabletoanalyzedigital,ratherthanpictorial,imagedata.ThebasiccharacterofdigitalimagedataisillustratedinFigure1.11.Thoughtheimageshownin(a)appearstobeacontinuoustonephotograph,itisactuallycomposedofatwo-dimensionalarrayofdiscretepictureelementsorpixels.Theintensityofeachpixelcorrespondstotheaverage"brightness"orradiancemeasuredelectronicallyoverthegroundareacorrespondingtoeachpixel.Atotalof320rowsand480columnsofpixelsareshowninFigure1.1la.Whereastheindividualpixelsarevirtuallyimpossibletodiscernin(a),theyarereadilyobservableintheenlargementsshownin(b)and(c).Theseenlargementscorrespondtosubareaslocatedinthevicinityofthe"×"in(a).A19rowx27columnenlargementisshownin(b)anda10rowx15columnenlargementisincludedin(c).Part(d)showstheindividualdigitalnumber(DN)correspondingtotheaverageradiancemeasuredineachpixelshownin(c).Thesevaluesaresimplypositiveintegersthatresultfromquantizingtheoriginalelectricalsignalfromthesensorintopositiveintegervaluesusingaprocesscalledanalog-to-digital(A-to-D)signalconversion.Typically,theDN’sconstitutingadigitalimagearerecordedoversuchnumericalrangesas0to63,0to127,0to255,0to511,or0to1023.Theserangesrepresentthesetofintegersthatcanberecordedusing6-,7-,S-,9-,and10-bitbinarycomputercodingscales,respectively.(Thatis,26=64,27=128,28=256,29=512,and210=1024.)Insuchnumericalformats,theimagedatacanliereadilyanalyzedwiththeaidofacomputer.Theuseofcomputerassistedanalysistechniquespermitsthespectralpatternsinremotesensingdatatobemorefullyexamined.Italsopermitsthedataanalysisprocesstobelargelyautomated,providingcostadvantagesovervisualinterpretationtechniques.However,justashumansaresomewhatlimitedintheirabilitytointerpretspectralpatterns,computersaresomewhatlimitedintheirabilitytoevaluatespatialpatterns.Therefore,visualandnumericaltechniquesarecomplementaryinnature,andconsiderationmustbegiventowhichapproach(orcombinationofapproaches)bestfitsaparticularapplication.REFERENCEDATAAswehaveindicatedinthepreviousdiscussion,rarely—ifever—isremotesensingemployedwithouttheuseofsomeformofreferencedata.Theacquisitionofreferencedatainvolvescollectingmeasurementsorobservationsabouttheobjects,areas,orphenomenathatarebeingsensedremotely.Thesedatacantakeonanyofanumberofdifferentformsandmaybederivedfromanumberofsources.Forexample,thedataneededforaparticularanalysismightbederivedfromasoilsurveymap,awaterqualitylaboratoryreport,oranaerialphotograph.Theymayalsostemfroma"fieldcheck"ontheidentity,extent,andconditionofagriculturalcrops,landuses,treespecies,orwaterpollutionproblems.Referencedatamayalsoinvolvefieldmeasurementsoftemperatureandotherphysicaland/orchemicalpropertiesofvariousfeatures.Referencedataareoftenreferredtobythetermgroundtruth.Thistermisnotmeantliterally,sincemanyformsofreferencedataarenotcollectedonthegroundandcanonlyapproximatethetruthofactualgroundconditions.Forexample,"ground"truthmaybeCollectedintheair,intheformofdetailedaerialphotographsusedasreferencedatawhenanalyzinglessdetailedhighaltitudeorsatelliteimagery.Similarly,the"ground"truthwillactuallybe"water"truthifwearestudyingwaterfeatures.Inspiteoftheseinaccuracies,groundtruthisawidelyusedtermforreferencedata.Referencedatamightbeusedtoserveanyorallofthefollowingpurposes:toaidintileanalysisandinterpretationofremotelysenseddata.tocalibrateasensor.toverifyinformationextractedfromremotesensingdata.Hence,referencedatamustoftenbecollectedinaccordancewiththeprinciplesofstatisticalsamplingdesign.Referencedatacanbeveryexpensiveandtimeconsumingtocollectproperly.Theycanconsistofeithertime-criticaland/ortime-stablemeasurements.Time-criticalmeasurementsarethosemadeinceaseswheregroundconditionschangerapidlywithtime,suchasintheanalysisofvegetationconditionorwaterpollutionevents.Time-stablemeasurementsareinvolvedwhenthematerialsunderobservationdonotchangeappreciablywithtime.Forexample,geologicapplicationsoftenentailfieldobservationsthatcanbeconductedatanytimeandthatwouldnotchangeappreciablyfrommissiontomission.Oneformofreferencedatacollectionistheground-basedmeasurementofthereflectanceand/oremittanceofsurfacematerialstodeterminetheirspectralresponsepatterns.Thismightbedoneinthelaboratoryorinthefield,usingtheprinciplesofspectroscopy.Spectroscopicmeasurementprocedurescaninvolvetheuseofavarietyofinstruments.Often,aspectroradiometerisusedinsuchmeasurementprocedures.Thisdevicemeasures,asafunctionofwavelength,theenergycomingfromanobjectwithinitsview.Itisusedprimarilytopreparespectralreflectancecurveslotvariousobjects.InLaboratoryspectroscopy,artificialsourcesofenergymightbeusedtoilluminateobjectsunderstudy.IntheIab,otherfieldparameterssuchasviewinggeometrybetweenobjectandsensorarealsosimulated.Moreoften,therefore,insitufieldmeasurementsarepreferredbecauseofthemanyvariablesofthenaturalenvironmentthatinfluenceremotesensordatathataredifficult,ifnotimpossible,toduplicateintheLaboratory.Intheacquisitionoffieldmeasurements,spectroradiometersmaybeoperatedinanumberofmodes,rangingfromhand-heldtohelicopteroraircraftmounted.Figure1.12illustratesahighlyportableinstrumentthatiswellsuitedtohand-heldoperation.Thisparticularsystemacquiresacontinuousspectrumbyrecordingdatain256bandssimultaneously.Thespectraloutputgoestoamicroprocessor-basedcontrollerthatrecordsdataonabuilt-intapedeck,andalsodisplaysandcommunicatesthedatainastandardcomputer-compatibleformat.Figure1.13showsamultibandradiometerthatmeasuresradiationinaseriesofdiscretespectralbands,ratherthanoveracontinuousrange.Thisparticulardeviceoperatesineightspectralbands,sevenofwhichmatchthoseusedbytheThematicMappersensoronboardtheLandsatsatellites.Theinstrumentisshownheresuspendedfromatruck-mountedtelescopingboom.Mountedinthismanner,theradiometercanbedriventomultiplefieldlocationswherespectralresponsemeasurementscanbemadequiteconveniently.Alldataareagainstoredusingamicroprocessor-baseddatalogger(locatedinthecabofthetruck).Usingaradiometertoobtainspectralreflectancemeasurementsisnormallyathree-stepprocess.First,theinstrumentisaimedatacalibrationpanelofknown,stablereflectance.Thepurposeofthisstepistoquantifytheincomingradiationorirradianceincidentuponthemeasurementsite.Next,theinstrumentissuspendedoverthetargetofinterestandtheradiationreflectedbytheobjectismeasured.Finally,thespectralreflectanceoftheobjectiscomputedbyratioingthereflectedenergymeasurementineachhandofobservationtotheincomingradiationmeasuredineachband.Normally,thetermreflectancefactorisusedtorefertotheresultofsuchcomputations.Areflectancefactorisdefinedformallyastheratiooftheradiantfluxactuallyreflectedbyasamplesurfacetothatwhichwouldbereflectedintothesamesensorgeometrybyanideal,perfectlydiffuse(Lamhertian)surfaceirradiatedinexactlythesamewayasthesample.DIGITALIMAGEPROCESSINGDigitalimageprocessinginvolvesthemanipulationandinterpretationofdigitalimageswiththeaidofacomputer.Thisformofremotesensingactuallybeganinthe1960swithalimitednumberofresearchersanalyzingairbornemulti-spectralscannerdataanddigitizedaerialphotographs.However,itwasnotuntilthelaunchofLandsat-1,in1972,thatdigitalimagedatabecamewidelyavailableforlandremotesensingapplications.Atthattime,notonlywasthetheoryandpracticeofdigitalimageprocessinginitsinfancy,thecostofdigitalcomputerswasveryhighandtheircomputationalefficiencywasverylowbymodernstandards.Today,accesstolowcost,efficientcomputerhardwareandsoftwareiscommonplaceandthesourcesofdigitalimagedataaremanyandvaried.Thesesourcesrangefromcommercialearthresourcesatellitesystems,tothemeteorologicalsatellites,toairbornescannerdata,toairbornesolid-statecameradata,toimagedatageneratedbyscanningmicrodensitometersandhigh-resolutionvideocameras.Alloftheseformsofdatacanbeprocessedandanalyzedusingthetechniquesdescribedinthischapter.Digitalimageprocessingisanextremelybroadsubjectanditofteninvolvesprocedureswhichcanbemathematicallycomplex.Ourobjectiveinthischapteristointroducethebasicprinciplesofdigitalimageprocessingwithoutdelvingintothedetailedmathematicsinvolved.Also,weavoidextensivetreatmentofthehardwareassociatedwithdigitalimageprocessing.Thereferencesattheendofthischapterareprovidedforthosewishingtopursuesuchadditionaldetail.Thecentralideabehinddigitalimageprocessingisquitesimple.Thedigitalimageisfedintoacomputeronepixelatatime.Thecomputerisprogrammedtoinsertthesedataintoanequation,orseriesofequations,andthenstoretheresultsofthecomputationforeachpixel.Theseresultsformanewdigitalimagethatmaybedisplayedorrecordedinpictorialformatormayitselfbefurthermanipulatedbyadditionalprograms.Thepossibleformsofdigitalimagemanipulationareliterallyinfinite.However,virtuallyalltheseproceduresmaybecategorizedintoone(ormore)ofthefollowingfourbroadtypesofcomputerassistedoperations:1.Imagerectificationandrestoration.Theseoperationsaimtocorrectdistortedordegradedimagedatatocreateamorefaithfulrepresentationoftheoriginalscene.Thistypicallyinvolvestheinitialprocessingofrawimagedatatocorrectforgeometricdistortions,tocalibratetiledataradiometrically,andtoeliminatenoisepresentinthedata.Thus,thenatureofanyparticularimagerestorationprocessishighlydependentuponthecharacteristicsofthesensorusedtoacquiretheimagedata.Imagerectificationandrestorationproceduresareoftentermedpreprocessingoperationsbecausetheynormallyprecedefurthermanipulationandanalysisoftheimagedatatoextractspecificinformation.WebrieflydiscusstheseproceduresinSection10.2withtreatmentofvariousgeometriccorrections,radiometriccorrections,andnoisecorrections.2.Imageenhancement.Theseproceduresareappliedtoimagedatainordertomoreeffectivelydisplayorrecordthedataforsubsequentvisualinterpretation.Normally,imageenhancementinvolvestechniquesforincreasingthevisualdistinctionbetweenfeaturesinascene.Tireobjectiveistocreate"new"imagesfromtheoriginalimagedatainordertoincreasetheamountofinformationthatcanbevisuallyinterpretedfromthedata.Theenhancedimagescanbedisplayedinteractivelyonamonitorortheycanberecordedinahardcopyformat,eitherinblackandwhiteorincolor.Therearenosimplerulesforproducingthesingle"best"imageforaparticularapplication.Oftenseveralenhancementsmadefromthesame"raw"imagearenecessary.WesummarizethevariousbroadapproachestoenhancementinSection10.3.InSection10.4,wetreatspecificproceduresthatmanipulatethecontrastofanimage(levelslicingandcontraststretching).InSection10.5,wediscussspatialfeaturemanipulation(spatialfiltering,convolution,edgeenhancement,andFourieranalysis).InSection10.6,weconsiderenhancementsinvolvingmultiplespectralbandsofimagery(spectralratioing,principalandcanonicalcomponents,vegetationcomponents,andintensity-hue-saturationcolorspacetransformations).3.Imageclassification.Theobjectiveoftheseoperationsistoreplacevisualanalysisoftheimagedatawithquantitativetechniquesforautomatingtheidentificationoffeaturesinascene.Thisnormallyinvolvestheanalysisofmultispectralimagedataandtheapplicationofstatisticallybaseddecisionrulesfordeterminingthelandcoveridentityofeachpixelinanimage.Whenthesedecisionrulesarebasedsolelyonthespectralradiancesobservedinthedata,werefertotheclassificationprocessasspectralpatternrecognition.Incontrast,thedecisionrulesmaybebasedonthegeometricalshapes,sizes,andpatternspresentintheimagedata.Theseproceduresfallintothedomainofspatialpatternrecognition.Ineithercase,theintentoftheclassificationprocessistocategorizeallpixelsinadigitalimageintooneofseverallandcoverclasses,or"themes."Thesecategorizeddatamaythenbeusedtoproducethematicmapsofthelandcoverpresentinanimage,and/ortoproducesummarystatisticsontheareascoveredbyeachlandcovertype.Duetotheirimportance,imageclassificationprocedurescomprisethesubjectofhalfofthematerialinthischapter(Sections10.7to10.14).Weemphasizespectralpatternrecognitionproceduresbecausethecurrentstate-of-the-artfortheseproceduresismoreadvancedthanforspatialpatternrecognitionapproaches.(Substantialresearchisongoinginthedevelopmentofspatialandcombinedspectral/spatialimageclassification.)Wetreatboth"supervised"and"unsupervised"approachestospectrallybasedimageclassification.Wealsodescribevariousproceduresforassessingtheaccuracyofimageclassificationresults.4.Datamerging.Theseproceduresareusedtocombineimagedataforagivengeographicareawithothergeographicallyreferenceddatasetsforthesamearea.Theseotherdatasetsmightsimplyconsistofimagedatageneratedonotherdatesbythesamesensor,orbyotherremotesensingsystems.Frequently,theintentofdatamergingistocombineremotelysenseddatawithothersourcesofinformationinthecontextofaGeographicInfo