Principles of GIS unit 1

Mumbai University, T.Y.B.Sc.(I.T.), Semester VI, Principles of Geographic Information System, USIT604, Discipline Specific Elective Unit 1: Introduction to GIS

1. Prof. Sanjana Khemka
Prahladrai Dalmia Lions College

2. Unit 1:Introduction to GIS
ThenatureofGIS
Therealworldandrepresentationsofit
GeographicInformationandSpatialDatabase
ModelsandRepresentationsoftherealworld
GeographicPhenomena
ComputerRepresentationsofGeographicInformation
OrganizingandManagingSpatialData
TheTemporalDimension

3. What is GIS?
Gstandsforgeographic,soGIShassomething
todowithgeography.
Istandsforinformation,soGIShassomething
todowithinformation,namelygeographic
information.
Sstandsforsystem,soGISisanintegrated
systemofgeographyandinformationtied
together.

4. What is GIS?
•Acomputersystemfor
-collecting,
-storing,
-manipulating,
-analyzing,
-displaying,and
-querying
geographicallyrelated
information.

5. Definitions of GIS
GISisaparticularformofInformationSystemapplied
togeographicaldata.
GISisacomputerbasedtoolthatanalyzes,stores,
manipulatesandvisualizesgeographicinformationon
amap.
AGeographicInformationSystemisasystemof
computersoftware,hardwareanddata,andthe
personnelthatmakeitpossibletoenter,manipulate,
analyze,andpresentinformationthatistiedtoa
locationontheearth’ssurface.

6. AGISisacomputer-basedsystemthatprovidesthe
followingfoursetsofcapabilitiestohandle
georeferenceddata:
1.Datacaptureandpreparation
2.Datamanagement,includingstorageandmaintenance
3.Datamanipulationandanalysis
4.Datapresentation

7. Data capture and preparation
Datacaptureandinputisdoneusingexistingdataor
bycreatingnewdata.
Newdatacanbecreatedfromsensedimages,GPS
devices,fieldsurvey,userinputandtextfilesetc.

8. Data Management
Datamanagementreferstothestorageand
maintenanceofthedata.
Dataisusuallystoredintablesinrowandcolumn
format.
Datamanipulationincludesdataverification,attribute
datamanagement,insertion,updation,deletionand
retrievalindifferentforms.

9. Data Manipulation and analysis
Oncethedatahasbeencollectedandorganized,analysis
canbedoneusingdifferentanalysistools.
DataPresentation
Afterthedataisgatheredandstored,itispreparedfor
producingoutput.
Thedatapresentationphasedealswithputtingitall
togetherintoaformatthatcommunicatestheresultofdata
analysisinthebestpossibleway.
Foreffectivepresentation,followingpointshouldbekept
inmind.Whatismessagewewanttoportray,whothe
audienceis,whatkindofpresentationmediumisusedand
whattechniquesareavailableforrepresentation.

10. GI System
GISystemisacombinationofafunctionalGIS
softwareandhardwarecomponents,userstoworkon
softwareandinfrastructuresupport.
Itisspecializedsoftwaretofacilitateinput,process,
transformandanalyzegeospatialdata.

11. GIS Application
GISsoftwarecanbeappliedtomanydifferenttomany
differentapplications.

12. GIS Applications
Naturalresource-based
wildlifehabitatanalysis,migrationroutesplanning
NaturalResourceManagement
LandUsePlanning
NaturalHazardassessment
Environmentalimpactanalysis(EIA)
Groundwatermodelingandcontaminationtracking
Streetnetwork-based
addressmatching-findinglocationsgivenstreetaddresses
vehicleroutingandscheduling
locationanalysis,siteselection
developmentofevacuationplans

13. Landparcel-based
Zoning,subdivisionplanreview
Landrecordmanagement
environmentalimpactstatements
waterqualitymanagement
maintenanceofownership
Facilitiesmanagement
locatingundergroundpipes,cables
balancingloadsinelectricalnetworks
planningfacilitymaintenance
Others
Crimeanalysis
Marketanalysis
Locationbasedservices
Incarnavigationsystem

14. Who Uses GIS?
PlanningStrategies
PoliceandLawEnforcementAgencies
Foresters
Industry
EnvironmentalEngineers
RealEstateProfessionals
TelecommunicationsProfessionals
EmergencyResponseOrganizations
LocalandFederalGovernment
Health
Transportation
Geographers
MarketDevelopers

15. GIS components
Computersystem
Hardware
Software
Geographicdata
Peopletocarryoutvariousmanagementandanalysis
tasks

16. Hardware–itisthecomputeronwhichaGISoperates
Software–itprovidesfunctionsandtoolsneededtoinput
andstore,query,performsanalysis,anddisplays
geographicinformationintheformofmapsorreports.All
GISsoftwarepackagesrelyonanunderlyingdatabase
managementsystem(DBMS)forstorageandmanagement
ofthegeographicandattributedata.

17. Data-Dataisoneofthemostimportant,andoften
mostexpensive,componentsofaGIS.
ItisenteredintoaGISusingatechniquecalled
digitizing.
Digitizingisdonebytracingthelocation,pathor
boundaryofgeographicfeatureseitheronacomputer
screenusingascannedmapinthebackground,ora
papermapthatisattachedtoadigitizingtablet.
Evendataisavailableforfreeorforpurchasefromthe
dataproviderorfromaspatialdataclearinghouse.

18. The real world and representations of it
OneofthemainusesofGISisasatooltohelpus
makedecisions.
Todosoweneedtorestrictourselvesto‘somepart’of
therealworldsimplybecauseitcannotberepresented
completely.
Itwillallowustoenterandstoredata,analyzethedata
andtransferittohumansortoothersystems.

19. MODELS
Amodelisarepresentationofwholeorsomepartof
therealworldhavingcertaincharacteristicsin
commonwiththerealworld.
Itisusedtostudyandoperateonthemodelitself
insteadoftherealworldinordertotestwhathappens
undervariousconditions,andhelpusanswer‘whatif’
analysisbychangingthedataoraltertheparameters
ofthemodel,andinvestigatetheeffectsofthe
changes.
Modelsareofdifferenttypes
Staticmodel-itrepresentasinglestateofaffairsatany
pointoftime.
Dynamicmodel-itisusedforsuchsystems,

20. Static model and Dynamic model
Itrepresentasinglestateofaffairsatanypointoftime.
Mostmapsanddatabasescanbeconsideredstaticmodels.
Usually,developmentsorchangesintherealworldarenot
easilyrecognizedinthesemodels
Dynamicmodels–itemphasizechangesthathavetaken
place,aretakingplaceormaytakeplacesometimeinthe
future.
Dynamicmodelsareinherentlymorecomplicatedthan
staticmodels,andusuallyrequiremuchmore
computation.
Simulationmodelsareanimportantclassofdynamic
modelsthatallowthesimulationofrealworldprocesses.

21. Models as representations
Models—asrepresentations—comeinmanydifferent
forms.
Themostfamiliarmodelisthatofamap.Amapisa
miniaturerepresentationofsomepartoftherealworld.
Papermapsarethemostcommon,butdigitalmapsalso
exist.
Databasesareanotherimportantclassofmodels
Digitalmodelshaveenormousadvantagesoverpaper
models(suchasmaps).
Theyaremoreflexible,andthereforemoreeasilychanged
forthepurposeathand.
Applicationmodels-itrefertomodelswithaspecific
application

22. Maps
Amapisagraphicrepresentationatacertainlevelof
detail,whichisdeterminedbythescale,having
physicalboundariesandfeatures.
Mapisaminiaturerepresentationofsomeportofthe
re
Cartography,isthescienceandartofmapmaking,
functionsasaninterpreter,translatingrealworld
phenomenaintocorrect,clearandunderstandable
representationsforouruse.
Mapsarealsoadatasourceforotherapplications,
includingthedevelopmentofothermaps.

23. Database
Adatabaseisarepositoryforstoringlargeamountsofdata
Adatabaseoffersanumberoftechniquesforstoringand
analyzingdata.
Adatabasecanbeusedbymultipleusersatthesame
time—i.e.itallowsconcurrentuse
Adatabaseallowstheimpositionofrulesonthestored
data
Adatabaseoffersaneasytousedatamanipulation
language
Databasescanstorealmostanykindofdata

24. Spatial databases
Spatialdatabasealsoknownasgeo-databasecanstore
representationsofrealworldgeographicphenomena
foruseinaGIS.
Itstoresaboutspatialreferencessystems,andsupports
allkindsofanalysisthataregeographicinnature,such
ascomputationofdistanceandarea.
Itmayhavepoint,line,andareaorimage
characteristics.

25. Spatial Analysis
Spatialanalysisisthegeneraltermforallmanipulationsof
spatialdatacarriedouttoimproveone’sunderstandingof
thegeographicphenomenathatthedatarepresents.
Itinvolvesquestionsabouthowthedatainvariouslayers
mightrelatetoeachother,andhowitvariesoverspace
Theaimofspatialanalysisisusuallytogainabetter
understandingofgeographicphenomenathrough
discoveringpatternsthatwerepreviouslyunknowntous,
ortobuildargumentsonwhichtotakeimportant
decisions.
GISfunctionsforspatialanalysisaresimpleandeasy-to-
use,muchmoresophisticated,anddemandhigherlevelsof
analyticalandoperatingskills

27. Models and representations of the real world
Modelingisheprocessofproducinganabstractionof
therealworldtoobserveandstudyiteasily.
Itistheprocessofrepresentingkeyaspectsofthereal
worldusingcomputersystem.
Theserepresentationaremadeupofspatialdata,
storedincomputermemory.
Modelingbeginswiththeprocessoftranslatingthe
relevantaspectsoftherealworldintoacomputer
representation.
Itcanbedoneusingdirectobservationsusingsensors,
anddigitizingthesensoroutputforcomputerusageor
byindirectmeans.

28. world phenomena inside
a GIS to build models or
simulations.
Representing real world Phenomena inside GIS

29. Geographic phenomena
Ageographicphenomenonissomethingthat
❖Canbenamedordescribed,
❖Canbegeoreferenced,and
❖Canbeassignedatime(interval)atwhichitis/was
present.
Forinstance,inwatermanagement,theobjectsofstudymightberiverbasins,
measurementsofactualevaporation,groundwaterlevels,irrigationlevels,
waterbudgetsandmeasurementsoftotalwateruse.
Aspatialphenomenaoccurinatwo-orthree-dimensionalEuclideanspace.
Euclideanspacecanbeinformallydefinedasamodelofspaceinwhich
locationsEuclideanspacearerepresentedbycoordinates—(x,y)in2D;(x,y,z)
in3D—anddistanceanddi-rectioncandefinedwithgeometricformulas.Inthe
2Dcase,thisisknownastheEuclideanplane

30. Types of geographic phenomena
InordertorepresentaphenomenoninaGIS,itrequiresto
statewhatitis,andwhereitis.
Somephenomenaexistsessentiallyeverywhereinthe
studyarea,whileothersonlydosoincertainlocalities.
GeographicFields
A(geographic)fieldisageographicphenomenonfor
which,foreverypointinthestudyarea,avaluecanbe
determined.Exairtemperature,barometricpressureand
elevation.
Afieldisamathematicalfunctionfthatassociatesa
specificvaluewithanypositioninthestudyarea.
If(x,y)isapositioninthestudyarea,thenf(x,y)standsfor
thevalueofthefieldatlocality(x,y).

31. Fieldscanbediscreteorcontinuous
Inacontinuousfield,theunderlyingfunctionis
assumedtobe‘mathematicallysmooth’,meaningthat
thefieldvaluesalonganypaththroughthestudyarea
donotchangeabruptly,butonlygradually.
Example-airtemperature,barometricpressure,
soilsalinityandelevation
Discretefieldsdividethestudyspaceinmutually
exclusive,boundedparts,withalllocationsinonepart
havingthesamefieldvalue.
Example-soiltype,landusetype,croptypeornatural
vegetationtype

32. Data types and values
Differentkindsofdatavalueswhichwecanusetorepresent
geographic‘phenomena’
1.Nominaldatavalues–itprovideanameoridentifiersothat
wecandiscriminatebetweendifferentvalues.Thiskindofdata
valueiscalledcategoricaldata
2.Ordinaldatavaluesaredatavaluesthatcanbeputinsome
naturalsequencebutthatdonotallowanyothertypeof
computation.Ex-Householdincome‘low’,‘average’or‘high’
3.Intervaldatavaluesarequantitative,inthattheyallowsimple
formsofcomputationlikeadditionandsubtraction.Interval
datahasnoarithmeticzerovalue,anddoesnotsupport
multiplicationordivision
4.Ratiodatavaluesallowmost,ifnotall,formsofarithmetic
computation.Rationaldatahaveanaturalzerovalue,and
multiplicationanddivisionofvaluesarepossibleoperators

33. Geographic Objects
Itpopulatethestudyareaandareusuallywell
distinguished,discrete,andboundedentities.
Positionofgeographicobjectsisdeterminedbya
combinationofthefollowingparameters
Location
Shape
Size
orientation

34. Boundaries
Boundaryisrequiredwhereshapeand/orsizeof
contiguousareasmatter
Boundaryisusedforgeographicobjectandfordiscrete
geographicfield.
Acrispboundaryisonethatcanbedeterminedwith
almostarbitraryprecision,dependentonlyonthedata
acquisitiontechniqueapplied.
Fuzzyboundariescontrastwithcrispboundariesinthat
theboundaryisnotapreciseline,butratheritselfanarea
oftransition.
Crispboundariesaremorecommoninman-made
phenomena,whereasfuzzyboundariesaremorecommon
withnaturalphenomena.

35. Computer representations of geographic information
Geographicphenomenoncanberepresentedincomputermemoryas
Storeasmany(location,elevation)observationpairsaspossible,or
Findasymbolicrepresentationoftheelevationfieldfunction,asa
formulainxandy—like(3.0678x
2
+20.08x-7.34y)orso—whichcan
beevaluatedtogiveustheelevationatanygiven(x,y)location.
Bothoftheseapproacheshavetheirdrawbacks
Thefirstsuffersfromthefactthat,thereareinfinitelymanylocations.
Insecondapproach,itisextremelydifficulttoderivefunctionforlarger
areas.
InGISs,acombinationofbothapproachesistaken.
Westoreafinite,butintelligentlychosensetof(sample)locationswith
theirelevation.
Interpolationfunctionallowsustoinferareasonableelevationvalue
forlocationsthatarenotstored.
Interpolationismadepossiblebyaprinciplecalledspatial
autocorrelation
fieldsareusuallyimplementedwithatessellationapproach,and
objectswitha(topological)vectorapproach

36. Regular tessellations
Atessellation(ortiling)isapartitioningofspaceinto
mutuallyexclusivecellsthattogethermakeupthe
completestudyspace.
Witheachcell,some(thematic)valueisassociatedto
characterizethatpartofspace.
Inallregulartessellations,thecellsareofthesame
shapeandsize,andthefieldattributevalueassigned
toacellisassociatedwiththeentireareaoccupiedby
thecell.

37. Raster
Arasterisasetofregularlyspaced(andcontiguous)
cellswithassociated(field)values.Theassociated
valuesrepresentcellvalues,notpointvalues.
Thesizeoftheareathatasinglerastercellrepresents
iscalledtheraster’sresolution.
Toimproveonthiscontinuityofcell
Makethecellsizesmaller,soastomakethe‘continuity
gaps’betweenthecellssmaller
Assumethatacellvalueonlyrepresentselevationfor
onespecificlocationinthecell.

38. Advantage and disadvantage of
Regular Tesselations
Regulartessellationsknowhowtheypartitionspace,
andcanmakecomputationsspecifictothis
partitioning.Thisleadstofastalgorithms
Anobviousdisadvantageisthattheyarenotadaptive
tothespatialphenomenonwewanttorepresent.
Thecellboundariesarebothartificialandfixed:they
mayormaynotcoincidewiththeboundariesofthe
phenomenaofinterest.
anotherdisadvantageisdatabasesizeinbigand
increaseswiththeincreaseinresolution.

39. Irregular tessellations
Irregulartessellationsarepartitionsofspaceinto
mutuallydisjointcells,butthecellsmayvaryinsize
andshape,allowingthemtoadapttothespatial
phenomenathattheyrepresent
Irregulartessellationsaremorecomplexthanthe
regularones,buttheyarealsomoreadaptive.
Itleadstoareductionintheamountofmemoryused
tostorethedata

40. Quadtrees

41. Itisbasedonaregulartessellationofsquarecells,but
takesadvantageofcaseswhereneighbouringcells
havethesamefieldvalue,sothattheycantogetherbe
representedasonebiggercell.
Thequadtreethatrepresentsarasterisconstructedby
repeatedlysplittinguptheareaintofourquadrants,
whicharecalledNW,NE,SE,SW.
Thisprocedurestopswhenallthecellsinaquadrant
havethesamefieldvalue.Theprocedureproducesan
upside-down,tree-likestructure,knownasaquadtree.
Inmainmemory,thenodesofaquadtreeare
representedasrecords.
Quadtreesareadaptivebecausetheyapplythespatial
autocorrelationprinciple,i.e.thelocationsthatare
nearinspacearelikelytohavesimilarfieldvalues.

42. Vector representations
Tessellationsprovideageoreferenceofthelowerleft
corneroftheraster,plusanindicatoroftheraster’s
resolution
Vectorrepresentations,explicitlyassociate
georeferenceswiththegeographicphenomena.
Ageoreferenceisacoordinatepairfromsome
geographicspace,andisalsoknownasavector.

43. TIN (Triangulated Irregular Network)
Itisarepresentationforgeographicfieldsthatcanbe
consideredahybridbetweentessellationsandvector
representations.
ATINisavectorrepresentation
ItisacommonlyuseddatastructureinGISsoftware
Itisoneofthestandardimplementationtechniques
fordigitalterrainmodels,butitcanbeusedto
representanycontinuousfield.
TheprinciplesbehindaTINaresimple.Itisbuiltfrom
asetoflocationsforwhichwehaveameasurement,
forinstanceanelevation.

45. Delaunay triangulation
Itisanoptimaltriangulation.
Firstpropertyistrianglesareasequilateral(‘equal-
sided’)astheycanbe,giventhesetofanchorpoints.
Thesecondpropertyisthatforeachtriangle,the
circumcirclethroughitsthreeanchorpointsdoesnot
containanyotheranchorpoint.

46. Point representations
Pointsaredefinedassinglecoordinatepairs(x,y)in
2D,orcoordinatetriplets(x,y,z)in3D.
Pointsareusedtorepresentobjectsthatarebest
describedasshape-andsize-less,zero-dimensional
features.

47. Line representations
Linedataareusedtorepresentone-dimensionalobjectssuchas
roads,railroads,canals,riversandpowerlines.
Thetwoendnodesandzeroormoreinternalnodesorvertices
definealine.
Othertermsfor’line’thatarecommonlyusedinsomeGISsare
polyline,arcoredge.
Anodeorvertexislikeapointbutitonlyservestodefinethe
line,andprovideshapeinordertoobtainabetterapproximation
oftheactualfeature.
Thestraightpartsofalinebetweentwoconsecutiveverticesor
endnodesarecalledlinesegments.
ManyGISsstorealineasasimplesequenceofcoordinatesofits
endnodesandvertices,assumingthatallitssegmentsare
straight.

48. Area representations
Areasastheyarerepresentedbytheirboundaries.
Eachboundaryisacyclicsequenceoflinefeatures;
Eachlineasisasequenceoftwoendnodes,within
betweenzeroormorevertices.
Areafeatureisrepresentedbycollectionofarc/node
structurethatdeterminesapolygonasthearea’s
boundary.

49. Topology and spatial relationships
Topologyreferstothespatialrelationshipsbetween
geographicalelementsinadatasetthatdonotchange
underacontinuoustransformation.
AreaEisstillinsideareaD,Theneighbourhood
relationshipsbetweenA,B,C,D,andEstayintact,and
theirboundarieshavethesamestartandendnodes
Theareasarestillboundedbythesameboundaries,only
theshapesandlengthsoftheirperimetershave
changed.

50. Topological relationships
Topologicalrelationshipsarebuiltfromsimple
elementsintomorecomplexelements:nodesdefine
linesegments,andlinesegmentsconnecttodefine
lines,whichinturndefinepolygons.
Themathematicalpropertiesofthegeometricspace
usedforspatialdatacanbedescribedasfollows:
Thespaceisathree-dimensionalEuclideanspacewhere
foreverypointwecandetermineitsthree-
dimensionalcoordinatesasatriple(x,y,z)of
realnumbers

51. Thespaceisametricspace,wecanalwayscomputethe
distancebetweentwopointsaccordingtoagiven
distancefunction.
Thespaceisatopologicalspace,foreverypointinthe
spacewecanfindaneighborhoodarounditthatfully
belongstothatspaceaswell.
Interiorandboundaryarepropertiesofspatialfeatures
thatremaininvariantundertopologicalmappings.

52. Wecandefinewithinthetopologicalspace,features
thatareeasytohandleandthatcanbeusedas
representationsofgeographicobjects.
Thesefeaturesarecalledsimplicesastheyarethe
simplestgeometricshapesofsomedimension:point
(0-simplex),linesegment(1-simplex),triangle(2-
simplex),andtetrahedron(3-simplex).
Whenwecombinevarioussimplicesintoasingle
feature,weobtainasimplicialcomplex

53. The topology of two dimensions
Topologicalpropertiesofinteriorandboundarycanbe
usedtodefinerelationshipsbetweenspatialfeatures.
WecandefinetheinteriorofaregionRasthelargest
setofpointsofRforwhichwecanconstructadisk-like
environormentarounditthatalsofallscompletely
insideR.
TheboundaryofRisthesetofthosepointsbelonging
toRbutthatdonotbelongtotheinteriorofR,i.e.one
cannotconstructadisk-likeenvironmentaroundsuch
pointsthatstillbelongstoRcompletely.

54. Set theory
ConsideraspatialregionA.Ithasaboundaryandan
interior,bothseenas(infinite)setsofpoints,and
whicharedenotedbyboundary(A)andinterior(A),
respectively.
Weconsiderallpossiblecombinationsof
intersections(∩)betweentheboundaryandthe
interiorofAwiththoseofanotherregionB,andtest
whethertheyaretheemptyset(∅)ornot.
Fromtheseintersectionpatterns,wecanderiveeight
(mutuallyexclusive)spatialrelationshipsbetweentwo
regions.

55. AmeetsB=
interior(A)∩interior(B)=∅∧
boundary(A)∩boundary(B)=∅∧
interior(A)∩boundary(B)=∅∧
boundary(A)∩interior(B)=∅.
Theserelationshipscanbeusedinqueriesagainsta
spatialdatabase,andrepresentthe‘buildingblocks’of
morecomplexspatialqueries.

56. The five rules of topological consistency in
two-dimensional space

57. Scale and resolution
Mapscalecanbedefinedastheratiobetweenthe
distanceonapapermapandthedistanceofthesame
stretchintheterrain.
A1:50,000scalemapmeansthat1cmonthemap
represents50,000cm,i.e.500m,intheterrain.
Whenappliedtospatialdata,thetermresolutionis
commonlyassociatedwiththecellwidthofthe
tessellationapplied

58. Representations of geographic fields
Ageographicfieldcanberepresentedthrougha
tessellation,throughaTINorthroughavector
representation.
Rasterrepresentationofafield
Rasterrepresentsacontinuousfieldlikeelevation.
Arastercanbethoughtofasalonglistoffieldvalues

59. Vector representation of a field
Thistechniqueusesisolinesofthefield.
Anisolineisalinearfeaturethatconnectsthepoints
withequalfieldvalue.
Whenthefieldiselevation,wealsospeakofcontour
lines.
BothTINsandisolinerepresentationsusevectors.

60. Representation of geographic
objects
Itissupportedwithvectors.All,objectsareidentified
bytheparametersoflocation,shape,sizeand
orientationandmanyoftheseparameterscanbe
expressedintermsofvectors.
However,tessellationsarestillcommonlyusedfor
representinggeographicobjects

61. Organizing and managing spatial
data
ThemainprincipleofdataorganizationappliedinGIS
systemsisthatofaspatialdatalayer.
Aspatialdatalayeriseitherarepresentationofa
continuousordiscretefield,oracollectionofobjects

62. The temporal dimension
Geographicphenomenaaredynamic,theychangeover
time.
Somefeatureschangesslowly,whileotherphenomena
changeveryrapidly.
Thetemporaldimensionisofacontinuousnature.
Thereforeinordertorepresentitinacomputer,wehaveto
‘discretize’thetimedimension.
Spatiotemporaldatamodelsarewaysoforganizing
representationsofspaceandtimeinaGIS.
Themostcommontechniqueisa‘snapshot’statethat
representsasinglepointintimeofanongoingnaturalor
man-madeprocess.
Wemaystoreaseriesofthesesnapshotstatestorepresent
change

63. Different ‘concepts’ of time
Discreteandcontinuoustime:Timecanbe
measuredalongadiscreteorcontinuousscale.
Discretetimeiscomposedofdiscreteelements
(seconds,minutes,hours,days,months,oryears).In
continuoustime,foranytwodifferentpointsintime,
thereisalwaysanotherpointinbetween.
Validtimeandtransactiontime:Validtimeisthe
timewhenaneventreallyhappened,orastringof
eventstookplace.Transactiontime(ordatabasetime)
isthetimewhentheeventwasstoredinthedatabase
orGIS

64. Linear,branchingandcyclictime-Timecanbe
consideredtobelinear,extendingfromthepasttothe
present(‘now’),andintothefuture.Thisviewgivesa
singletimeline.
Branchingtime—inwhichdifferenttimelinesfroma
certainpointintimeonwardsarepossible—and
cyclictime—inwhichrepeatingcyclessuchasseasons
ordaysofaweekarerecognized,makemoresenseand
canbeuseful.
Timegranularity-granularityistheprecisionofa
timevalueinaGISordatabase
Absoluteandrelativetime-Absolutetimemarksa
pointonthetimelinewhereeventshappen
Relativetimeisindicatedrelativetootherpointsin
time

65. References
PrinciplesofGeographicInformationSystem–Sheth
Publication
PrinciplesofGeographicInformationSystems-An
IntroductoryTextBook–Publication-The
internationalInstituteofGeoInformationScienceand
EarthObservation