Geographic Info Systms
Geographic Info Systms GEOG 350
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This 19 page Class Notes was uploaded by Cortney Leuschke on Saturday September 12, 2015. The Class Notes belongs to GEOG 350 at West Virginia University taught by Staff in Fall. Since its upload, it has received 55 views. For similar materials see /class/202690/geog-350-west-virginia-university in Geography at West Virginia University.
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Date Created: 09/12/15
4 The Nature afGeagraphic Data Geog5pm Information Systems and SUEice stcowo EDITION m A min i when m M 1 m nzmdw 25 mmnmq W m Italm m Liam in Why GIS oSmaII things can be intricate eG can aldentify structure at all sca es a Show how spatial and temporal context affecls what we do sAllows generalization and accommo a s err r e Accom modates spa e heterogeneity um mu m anm m Spatial Autocorrelation oSpatiaI autocorrelation is determined both by similarities in position and by similarities in attri u 5 a sampling interval Selfsimilarity um mu m anm m Overview Spatial is Special sThe ItrueI nature of geographic data eThe special tools needed to work with them eHow we sample and interpolate gaps eWhat is spatial autocorrelation and how n it be measured eFractaIs and geographic representation um mu m Ime m r 1 Building Representations eTemporal and spatial autocorrelation Understanding scale and spatial structure ampe a How to I39nDerpoabe between observations sObject dimensions a Natural vs arti cial unils um mu m Ime m eEventhing is related to eventhing else but nar thin s are more related than distant things Waldo Tobler a Distance Decay eSpatiaI Autocorrelation um mu m Ime m anmum xm in Sample Designs sTypes of samples om samp 5 a Strati ed samples 5 Clustered sampls a Purposive samples not statistical eWeighting of obsenations mm in m m Distance Decay Spatial Interpolation GSpecifying the likely distance decay d 5 negative exponential WV em eIsotropic and regular relevance to all geographic phenomena 5 Inductive vs deductive approaches See p94 minim Mu m m Spatial Sampling oUniverse Population eSample frames e Probability of selection sAll geographic representations are mples aGeographic data are only as good as the sampling scheme used to create them mum in an m independence statistically Bias representability general popn See p91 mum in an m Distance Decay mum in an m Spatial Autocorrelation Measures 0 Measures ofspatial autocorTelation a G ary Moran nature of observations p100 0 Establishing dependence in space regression analysi y eznnslemvlley 550m ud ommwlwm Lid Spatial interaction modeling in ARCINFO UK Department of the Environment DOE predicted 44 million new households in England between 1991 and 2016 DOE 19 a Local Admonuee must pl Scenm39iox 7 What if an nodsng polloes wnen corrpr Wldn EU and UK sustall39ldale development guldelll les a in tens or uansport new nodsng and sevlces snould be planned to reduce me need to travel theeby mll llmzil lg me co 0 Spatial interaction modeling in ARCINFO was used to predict travel flows to libraries in Gloucestershire eznnslomwleyssons ud hum Slrmnmll ommwlwm Lid Sampling From Space 3 Points s Lines networks aAreas regions aVolumes 3D eznnslemvlley 550m ud Line Features wy network 39 Southern Ontario ii it um mu m anm m Form 7 Process reasoning 6 Functional form SInferring Procss a cause39 and ffect39 OThe assumptions of inference Tobler39s Law a Multicollinearity um mu m Ime m Discon nuous Variation 0 Fractal geometry 5 Se Ifsimilarity s Scale dependent measurement 5 Regression analysis of scale 39 i um mu m anm m Summary oInduction and deduction sRepresentations build on our understanding ofspatial and temporal structures sSpatial is special and geographic data have a unique na ure um mu m Ime m w 39 l i 39 GEOG 350 Geographic GIS Data Stores I Spatial data stored in digital format in a GIS allows for 39 39 rapid access for traditional as well as innovative Information Scrence purposes I Nature of maps creates dif culties when used as Lecture 6 sources for digital data Most cis take no account of differences between datasets derived from rnaps at different scales idiosyncrasies e g generalization procedures in rnaps ecorne locked in to tne data derived from tnern Such errors often o orn apparent only during later processing ofdigitai data derived from tnern GIS as Data Stores 2 I Maps still remain an excellent way of compiling spatial information eg field survey I Maps can be designed to be easy to convertto digital form eg by the use of different colors which have distinct signatures when scanned by electronic sensors I Paper maps can be produced by GIS as cheap high density stores of information for the end user however consistent accurate retrieval of data from rnaps is difficult I only limited amounts of data can be Shown due to constraints ofthe Dapermedlum Types of Attributes Censusm M110 7 BlockGroups I Nominal eg land cover class WWW I Ordinal eg a ranking I Interval eg Celsius temperature I Differences make sense I Ratio eg Kelvin temperature I Ratios make sense I Cyclic eg wind direction 39 WVEcore 39nnBoundar39as NOMINAL 939 39 ORDINAL 1 Hood Hlnm mu sum UE antsnmcl Swauk Creek Study Area cvcuc Eastern Cascade Range WA Cyclic Attributes GIS Data Indexes I Do not behave as other attributes I Data indexing function can be performed I What isthe average oftwo compass bearings eg much better by a good GIS due to the ability 350 and 10 to provide multiple and efficient cross I Occur commonly in GIS referencing and searching Wind direction I Spatial Query l Slope aspect I Flow direction I Special methods are needed to handle and analyze GIS Data Analysis I GIS is a powerful tool for map and spatial analysis I Traditional impediments to the accurate and rapid measurement ofarea or to map overlay no longer exist I Many new techniques in spatial analysis available GIS Data Display I GIS display offers signi cant advantages over the P Ablllty to browse across an area Witnout interruption by rnap sneetbound res Ablllty to Zoom and cnange scale rreel Potentlal rortne anirnation ortirne dependent data Display in 3 dlrnel39lslol39ls perspectiye VleWS Witn realr H e 3 c Q a 6 2 o 5 o E 2 L0 Potential ror continuous scales or intensity and tne use or color and snading independent or tne constraints or tne printing process ability to cnange colors as required or interpre ation Speclal purpose products are possible and ll lexpel lslve Areal Units and Scale Areallhlits and Scale Md GEOGRAPHIC REFERENCIN Areal Units and Scale DATA INPUT I Data Sources I Data Input Methods I Drawing I Digitizing I Scannin I Coordinate geometry COGO I Global Positioning Systems I Data Editing SPATIAL DATA MODELS I GEOMETRIC DATA I Raste r I Quadtree I Vecto r I Objectoriented I ATTRIBUTE DATA I Flat les I Indexed Files I easy searches and retrieval Linking Values to Location I Database tables I Relational DBMS I Separate tables for storage of spatial objects topology and attributes I Unique identifier for each spatial object I Attribute tables record variables I ID links records to geometry of points lines polygons Linking Attributes to Locations Points Lines Polygons Feature ambute table ft Geocoding Street City City onLe on Right Left eyien D DALLAS DAuAs p Prestng R d DALLAS DAuAs address matching S art C Address Address Address Address Code Right Right 13ml 13mg lgsm 13398 Ml 14543 14733 14642 14795 mi SPATIAL RELATIONSHIPS I Distance Direction I Topological Relationships Contains Contained by I Adjacent next near by I Connected to intersects crosses North of Second right after the lights at K Mart I Toute Droite toute droite en francais GIS Analysis I Data manipulation and analysis I Organization update and maintenance I Query and retrieval I Selection I Presentation I Projection Transformation warping GIS QUERY AND RETRIEVAL 2 I Relational Databases I Joi ing databases I Querying Databases I Standard Query Language SQL Result of Database Query AnnREss cn 5m ZIP spscmm UMSPEWDNDR Mus m M 75240 DenialF w mxswzsmeu mus m 752 GeneralFle mamzmmw mus H mm GeneralFle 2x35 immune mus M 7m GeneralFle maummtz mus M 75234 GeneralFle mm ssr ALLAS x 752m GeneralF w wwsaucKNERaLuAuAs m 75227 GeneralF w smrwwumsr mus m 752m GeneralFle 553i mew mus m 75235 wealFle mammal DAL M 7m GeneralFle annmwswu mus m 7523i GeneralFle niNchuLLAv mus H mm GeneralF w ammer mus m 752m GeneralF w nxzatucKHEEuAv mus m 752m GeneralFle n UN sr m 752m wealFle Viewwusm mus M 7m GeneralFle Mapping is crucial for I Creating and communicating plans I Knowing where affected ltarget populations and places are located I Spatialtrends er prevalence Numbers nlEvents hylnczlinn Sprezd Dmusinn Clusters I identifieatiun uflucatiuns in need DflntENEntan Individuzb Sources of Geographic Data I Vector data I Digital line graphs I Raster pixel data I Digital terrain models elevation I Satellite and airborne imagery I Orthophotographs I Data on the web liy EISData rg a Cle ghouse v Interactive map sewers allow 3 mm mm rmv umw cis and realrtzme data 39nm the eld helps in disasterrespunse damage assessment Abanduned structures are asenuus pmblem m seme eities ill prufitgruups ean use GlS tn develup aetiun plans furseal u and demulitiuns and tn munitur prugress mm Spatial Analysis I Measurement l ModifyAttributes I Overlay I Buffer I Generalize I Network Analysis Geocoding I Surface and olume Modeling I Slope Aspect lViewsheds Lineof sight Spatial Analysis I Spatial patterns Geugrapnie distributiuris Cnange Trends TimerSpace Madeling I Spatial association Spatial covariation n I Understanding 30 Km Bunemmund Interstate Highways i HCFA Demunstratiun Region 7 lnlelsmte Highways 30 rn Butler outside 30 Km Within 30 Km MAP ovEHLAV mm mi iewdtlriuw ml tummile leinglmyn Cn39me incidents in calculated using tlne total distance ficin each event to a 39 numbei of nearest 39 incidents GIS helps human services staff access the transit accessibility for welfaretowork clients to j obs day care and training facilities Hardware Summary I Data Display I Spatial Query I Spatial Data I Spatial Ralatlonsillps St I Creating Information ore and knowle ge l Spatial Index I Asking why when and where I Spatial AnaIySIs I WHAT IF Representing Spatial Phenom ena Oblects as connnuous varlauun symbuls Surface Themaue M an cno lsulme ma Cuntuurs mpleth wlmms x l I I V39V 1 V W quotY 7quot a A f v GIS responds to three fundamental quesu39ons by automating spatial data What is Where Lecture 5 Why is it there GIS reveals linkages unevenly distributed social economic and Putting Maps m 613 vironmental in uences What if GIS provides geographical context for alternative policy analysis wlmms 2 w r 139 i Because everyt 9 we manage is A somewh re Census Tracts Rn a shopping Centers and is somehow connected vlrw r Hrwlr GIS Coordinates Multiple Map Layers Mapsfrnm di a39ent Smlrces Different matures and symhnls States n Ierentscalesaml areal c as llmts quotmquot Areacades CensusTxaELs ZIP Cadas Streets wlmms Maps and GIS 2Maps are the main source ofdata for GIS Traditions of cartography are fundamentally important to GIS GIS has roots in the analysis of information on maps and overcomes many of the limitations of manual anal sis 39thls lecture is abuut cartugaphy audits relauunshlp tn GIS Huw dues Gls differ 39nm canngraphy 7 r xfr WHAT IS A MAP 00 Definition 00 Maps show more than the Earth39s surface 00 Types of maps z Thematic maps in GIS z Line maps versus photo maps 00 Characteristics of maps nae crown DefEition According to the International Cartographic Association ICA a o a representation normally to scale and on a at medium ofa selection of matenal or abstract features on or in relation to the surface of the Earth Maps show more than the Earth39s surface the term quotmapquot is o en used in mathematics to convey the notion of transferring information another just as cartographers transfer information from the surface ofthe Earth to asheet ofpaper E 0 rm mapquot is used loosely refer to any visual display of inform 39 rr jr De nition of Map o NOUN or VERB o STATIC or ACTIVE o OBJECT or PROCESS 00 All of the above alloauns Wri Types of maps z In practice we normally think oftwo types ofmap z To ographic map a reference tool showing the outlines ofselected natural an manmade features ofthe E often acts as r ase mapfor other information quotTopographyquot refers to the shape ofthe surface represented by hadin 39 L quot and other prominent features Th matic map atool to communicate geographic concepts such as the distribution of popul ch al ation densities 39mate movement ofgoods land use t0 ation particularly if it atic is abstract generalized sc em AWN Maps show more than the Earth s surface z Production of a map requires Selection ofthe few features in the real world to include classification ofselected features into groups i e bridges hurches railways simplification ofjagged lines like coastlines 1Exaggeration offeatures to be included that are to small to show at the scale ofthe Symbolization to represent the different classes offeatures osen gwmet Themauc maps in GIS o Several types ofthematlc map are important in GIS 39239 choropleth map uses reporting zones such as counties or census tracts to show data such as average incomes percent female or rates of morta ity thebuundanes ufthezunes uraral umts are established indepmdently ofthe data and maybe used to report many differmt sets ufdata 1 area class map shows zones ofconstant attributes such as vegetation soil type or forest species the buundanes are diffa39mt fur ach map as they are deterrmned by the wnatiun ofthe attribute being mapped e g breaks of soil type may uerur independently ufbraks ufyegetatiun lrwr w r f taterrew f Thematic maps in GIS tzo An isopleth map shows an imaginary surface by means of lines joining points of equal value quotisolinesquot eg contours on a topographic map o used for phenomena which vary smoothly aeross the map sueh as temperature pressure rainfall or population density 0 Surface and Volumetric Maps o Goingbeyond2 dimensions animus Line maps versus photo maps An important distinction for GIS is between a line map and a photo map A line map shows features by conventional symbols or by boundaries A photo map is derived from a photographic image taken th air from e o features are interpreted by the eye as it views the map o certain features may be identi ed by overprin ng labels quotAyn t free of distortions Digital Orthophotograph 1 12 000 Digital Orthophotograph 14000 Schematic representation of the lives of three US citizens in space two horizontal axes and time vertical axis 00 Maps are o en stylized generalized or abstracted requiring careful interpretation 00 Usually out of date 00 Show only a static situation one slice in time 00 Often highly eleganUaItistic 00 Easy to use to answer certain types of questions Where is it But not How much v t 1 l t ml Characteristics of Maps The Traditional Map A long and rich history Has a scale or representarive action o The iatjd of distance on the map to distance on the ground Is a major source of data for G18 0 obtained by digitizing of scanning the map andregistering it to arth surface Digital representations are much more power il than their paper equiva en s EllstS The earliest map Catal Hyuk BZUUBC v r k r r W7er r WHAT ARE MAPS USED FOR Data Display z Traditionally maps are used as aids to navigation as 4 Maps provide useful ways of displaying reference documents and as Wall decorations information in a meaningful way z maPS haVe four r0135 tOdaY z In practice the cost of making and printing a map is DATA DISPL Y high DATA STORE z Map contents are o en a compromise between different 2 SPATIAL INDEX needs DATA ANALYSIS A producing useful information rEFv kjr r W DW ii r Data Storage Spatial Indexes 00 As a means of storing data maps can be very Coordinate systems location EffiCith high density StOreS A map can show the boundaries of areas eg land use za typical l50000 map might have 1000 place names zones soil or rock types and identify each area With a O i label zthe information printed on the typical l50000 oa separate manual with corresponding entries may provide topographic map sheet in the UK requires 25 million greater detail about each are bytes of storage When it is converted to digital form equivalent to one standard computer tape or 10 full length nove s I JWW D t A 1 THE USE OEMAPS FOR a a 1 VS INVENTORY AND ANALYSIS z Examples demonstrate how maps have been used for sophisticated applications in inventory and analysis z Maps are used in analysis to and point out some limitations oMake or test hypotheses such as the identi cation of cancer clusters oExamine the relationship between two distributions using simple transparent overlays r xfr Measuring land use change Two major land use surveys were carried out in the UK in the late 1930s by Sir Dudley Stamp and in the 1960s by Professor Alice Coleman he resu1ts were pub1ished as maps n order to compare changes in 1and use between 1930s and 1960s the area ofeach 1and use type was measured using a hand p1animeter and counting overlaid dots Despite interest in measuring the amount of change ofland use through time particularly from agricultural to urban few resulm d th 39 al were produce using this me od because the tra ition techniques are slow and tedious and because ofthe difficulty of overlaying or working from very different map sources WVW M V Landscape architecture z Ian McHarg pioneered the use of transparent map overlays for planning locations of highways ansmission corridors and other facilities in environrnen ly sensitive areas McHarg 1969 despite the popu1arity ofthis technique and numerous armliratinn 39 39 39 L 439 without the use ofcomputers and GIS re4 jr GIS and Mapping mioauus z WFv KFW H V AUTOMATED 1WD COMPUTER ASSISTED CARTOGRAPHY oz Change to computer mapping persona1ities were critically important in the 1960s and ear1y 1970s individual interests determined the direction and focus of research and development in computer cartography see Rhind 1988 tztImpetus for change began in two communities Two Communities 00 Community 1 z Scientists wishing to make maps quickly to see the resulw of modeling or to display data from large archives already in digital form eg census tables 9 quality not a major concern 0 SYMAP was the first Significant package for this purpose released by the Harvard Lab in 1967 00 Community 2 Cartographers seeking to reduce the cost and time of map production and e 39tin 0 hardware eusts hmited interest in this teehmdugy pnur to 19m to the major mapping ageneies enuwuis universally ayadabie un Fes an FDAs o the eusts ufeumpuang have dropped by an order ufmaputude every six years 0 an early beliefthat the more mzprmakmg pmeess euuid be automated dimimshed by 1975 beeause ufdif culnes urgenerahaaaun and design gwmw Advantages of computer cartography z Lower cost for simple maps faster production z Greater exibility in output easy scale or projection c ange maps can be tailored to user needs z Many other uses for digital data r fr Disadvantages of Computer Cartography 00 High initial capital cost though this is now much reduced 00 Computer methods do not ensure production of maps of high quality oLoss ofregard for the cartographic tradition with the consequent production of cartojunk 0 GIS easy to make Bad Maps Costbenefit analysis difficult r WVW M GIS and Computer Cartography z Computer cartography has a primary goal of producing maps Systems have advanced tools for map layout placement labels large symbol and font libraries inteifaces for exp high quality output devices Not an analytical tool of ensive Unlike data for GIS cartographic data does not need to be stored in my which allow anal sis ofrelationships between different as population density and housing prices or the routing of ows along connecting highway or river segments Display only