GIS应用Chapter 6.docx
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GIS应用Chapter 6.docx
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GIS应用Chapter6
Chapter6
Preprocessing
PreprocessingproceduresareusedtoconvertadatasetintoaformsuitableforpermanentstoragewithintheGISdatabase.Often,alargeproportionofthedataenteredintoaGISrequiressomekindofprocessingandmanipulationinordertomakeitconformtoadatatype,georeferencingsystem,anddatastructurethatiscompatiblewiththesystem.Theendresultofthepreprocessingphaseisacoordinatedsetofthematicdatalayers.
Theessentialpreprocessingproceduresinclude:
⏹formatconversion;
⏹datareductionandgeneralization;
⏹errordetectionandediting;
⏹mergingofpointsintolinesandofpointsandlinesintopolygons,whereappropriate;
⏹edgematching;
⏹rectification/registration;
⏹interpolation;and
⏹photointerpretation.
We'llexamineeachoftheseinturninthischapter.Atthesametime,manyoftheseproceduresarevaluableatotherstagesintheend-to-endspatialanalysisproblem.Wewillpointouttheseadditionalusesastheycomeupinlaterchapters.
6.1FormatConversion
Formatconversioncoversmanydifferentproblems,butcanbediscussedintermsoftwofamilies:
conversionbetweendifferentdigitaldatastructuresandconversionbetweendifferentdatamedia.Theformeristheproblemofmodifyingonedatastructure(suchasthosediscussedinChapter4)intoanother.Thelattertypicallyinvolvesconvertingsourcematerialsuchaspapermaps,photographicprints,andprintedtablesintoausefulcomputer-compatibleform.Notethatthereverseofdatamediumconversion--changingthedatastoredwithinthedigitaldatabaseintomaps,printsandtables--istheproblemofgeneratingoutputproducts,whichwediscussinChapter9.
6.1.1DataStructureConversions
InChapter4,wediscussedseveraldifferentdatastructures.Therearemanytimeswhendifferentdatasetsgatheredforthesameprojectareexpressedindifferentdatastructures.Partofthecauseofthislackofhomogeneityisthenatureofthedatasetsthemselves,somedatastructuresbeingmoresuitabletosomekindsofdatathanothers.Thisproblemisbecomingmoreacuteasincreasingamountsofcurrentdataarecreatedandmaintainedinvariousdigitalforms,whilehistoricalrecordsarealmostuniversallystoredonpaperorfilm.Anotherkindofproblemthatarisesfrequentlyiswhenwehaverasterdatasets,suchasdigitizedphotographyandmultispectralscannerdata(discussedinChapter10),andourGISisbasedonavectordatastructure.Inthesecases,wemustbeabletointer-convertbetweenthedatastructures.Similarconversionswillberequiredinordertodevelopfinaloutputproductsaswell(seeChapter9).
Thesimplestformsofconversionarebetweenmembersofafamilyofstructures.Forexample,thereareseveralcommonrasterformatsforrasterdata.TypicalrasterGISdatasetsincludearraysofelevation,rainfall,andclassesoflandcover.Thisisalsothekindofdatathatisproducedbymultispectralscanners,whicharecommonsensorsonbothaircraftandspacecraftplatforms(someapplicationsofthesesystemsarediscussedinChapters10and12).Thedataproducedbysuchsystemsmaybethoughtofasanarrayofbrightnessvaluesforeachwavelengthbandinthesensor.Thesesystemsgeneratedatasetsthatarecomparabletoanyothermultivariatecollectionofrasterdata,includingproblemsofgeometricregistrationbetweenthewavelengthbandsorbetweendifferentdatesofacquisition(Welch,1985).
Thereare,however,severalwaystoorganizesuchdatasets.Keepingeachvariable'sdata(forexample,elevationandannualrainfall,orthedifferentspectralchannelsfromamultispectralscanner)asaseparatearrayisonecommonmethod.Thismethodisoftencalledbandsequential(BSQ),sinceeacharrayiskeptasaseparatefileonthemagneticdiskortape.Inthiscase,onedatafilewouldcontaintheelevationarray,andaseparatefilewouldcontainrainfallvalues.Acommonalternative,calledbandinterleavedbypixel(BIP),placesallofthedifferentmeasurementsfromasinglepixeltogether.Thisorganizationmaybethoughtofasasinglearraycontainingmultivariatepixels(Figure6.1).Thefirstelementinthissecondformatwouldcontaintheelevationvalueforthepixelinthefirstrowandcolumn;thesecondelementwouldcontaintherainfallvalueforthesamepixel.
Whenoperationsonthedatainvolveasinglethemeorlayeratatime,aBSQrasterdatabasecanbethemostefficientorganization.Thisisbecausethespecificthemeofinterest(orspectralchannel)canbeanalyzedandmanipulatedasaphysicallyindependententity.Conversely,whenworkingwithmorethanonedatathemeatatime,theBIPorganizationcanbethemostefficient.Forexample,considerarasterdatasetwithtwothemes:
elevationdatapointsandclassesofforestcover.Ifaprincipalactivityistooperateonasingledatalayeratatime,suchasderivingslopefromtheelevationdatapoints,theBSQorganizationmakestheelevationdatadirectlyavailable,withouthavingtoreadthedatafilespastland-usevalues.If,ontheotherhand,ananalyticoperationrequirescomparisonofboththemesonapixel-by-pixelbasis,suchasfindingthelocationofthehighestelevationforeachofseveralforest-typeclasses,theBIPorganizationmakesgoodsense,asthevaluesofthetwothemesforeachpixelareadjacentinthedatabase.
Thebandinterleavedbyline(BIL)rasterorganizationisamiddle-groundbetweentheextremesofBSQandBIP.Inthisform,adjacentgroundlocations(intherowdirection)forasinglethemeareadjacentinthedatafile,andsubsequentthemesarethenrecordedinsequenceforthatsameline.Inthisway,thedifferentthemescorrespondingtoarowinthefilearerelativelyneareachotherinthefile.Thus,oneexpectsthatitsperformanceonspecifiedtaskswillfallbetweenthepuresequentialorpurepixel-interleavedforms.Thisintermediatetypeofmultivariaterasterisusedinsomecommercialrastersystems.
Forthosereaderswithadataprocessingbackground,wewillbrieflyaddtothecomplexity.TherearetwocommonphysicaldataorganizationsforBIL-structureddata.Inone,thephysicalrecordsholdallthethemesfromasinglerowinthearray,orderedasdescribedinthepreviousparagraph.Thus,thenumberofphysicalrecordsisthesameasthenumberofrowsinthearray.IntheothercommonBILformat,aphysicalrecordcorrespondstoasinglethematiccategory.Thusinthissecondcase,thenumberofphysicalrecordsinthedatasetistheproductofthenumberofrowsinthearraytimesthenumberofuniquethemes.
Theproblemofconvertingbetweenthedifferentrasterdataformatsdescribedaboveisrelativelysimple.Typically,aportionofthedatainoneformatisreadintoamemory-basedstoragearray,andtheappropriatepointerscreatedtoextractthedatavaluesinwhateversequenceisrequiredforthenewformat.Optimizingsuchconversionsoftwareonagivencomputerisstraightforward.WediscussanotherfamilyofdataformatcomplicationsinChapter10.
Thereareawidevarietyofproblemsthatdevelopwhenconvertingdatasetsbetweendifferentvectordatastructures.AswenotedinChapter4,therearemanydifferentvectororganizations.Asaguidingprinciple,itisexpensivetogeneratetopologicalinformationwhenitisnotexplicitlypresentinthevectordatastructure.Toillustratethispoint,convertingdatafromanarc-nodeorganizationtoarelationaloneisveryeasy.Asweobservedinthelastchapter,theseareverysimilardatastructures,intermsofthewaytopologicalinformationaboutspatialobjectsareorganized.Ineffect,thesetwodatastructuresarereallystoringtheexactsamesemanticinformation,withaslightlydifferentsyntax..
Attheotherendofthespectrum,considertheproblemofconvertingdatainawholepolygonstructuretoanarc-nodestructure.Inadatasetstoredinwholepolygonstructure,thereisverylittleexplicitlyidentifiedtopology.Thelistofnodesthatformtheboundariesofeachindividualpolygonisstored.Considerjusttheproblemofextractingthearc-nodenodelist.Wemustgothroughtheentirelistofpolygons,andcreatealistoftheuniquenodes.Thismightrequireadouble-sortofallthepointsinthepolygonfile,andthenapassthroughthesortedlisttoidentifytheuniquenodes.Creatingthearclistrequiresanotherpassthroughthewholepolygonfile,thistimecross-referencingedgesofeachpolygontothecorrespondingelementsinthenodelistandgeneratingtheappropriatepointers.Furthermore,toidentityallthepolygonsthatborderagivenvectorrequiresanothercomplexsortingoperationtoidentifyallthesharededges.
Convertingvectordataintoarasterdatastructureisconceptuallystraightforward,althoughpracticallydifficult.Forpointdataelements,thecellorpixelintherasterarraywhosecenterisclosesttothegeographiccoordinateofthepointiscodedwiththeattributeofthepoint.Thus,theelevationvaluefromasurveyedbenchmarkistransferredtotherastercellwhoselocationisclosesttothatoftheoriginalpoint.Ofcourse,thisoperationusuallychangesthestoredlocationofthepoint--itisunlikelythattheoriginalpointlocationexactlycoincideswiththecenterofarastercell.Thisapproachalsoignorestheproblemofdifferentobjectsoccupyingthesamecell.Becauseoftheseimportantlimitations,theconversionfromvectortoarasterdatastructureisnotnormallyreversible:
wecannotretrievetheoriginaldatapointsfromthederivedrasterdatawithouterror.Forsomeoperations,thiscanbeafatalflaw.
Forlineardataelements,thedatastructureconversioncanbevisualizedbyoverlayingtheve
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