Geographic Information Geographic Information SystemsSystems

SGO 1910, SGO 4030SGO 1910, SGO 4030

October 10, 2006October 10, 2006

UpdatesUpdates

Midterm quiz 1 (will be returned next week)Midterm quiz 1 (will be returned next week) ArcGIS CDs – Geodata will give us more, and ArcGIS CDs – Geodata will give us more, and

I hope to pick them up before next week.I hope to pick them up before next week. GIS Day – November 15GIS Day – November 15 Oslo Project: Will be described next week – Oslo Project: Will be described next week –

please start thinking about groups (of 3).please start thinking about groups (of 3).

Masters students: start thinking about papers Masters students: start thinking about papers as an alternative to the Oslo Project (both are as an alternative to the Oslo Project (both are options)options)

Read Steinberg and SteinbergRead Steinberg and Steinberg

Where are we?Where are we?

What is GIS?What is GIS? Geographic representations: discrete objects Geographic representations: discrete objects

and fieldsand fields Digital representations: vector and raster Digital representations: vector and raster

modelsmodels Geographic data: scale, spatial autocorrelation, Geographic data: scale, spatial autocorrelation,

sampling, interpolationsampling, interpolation Georeferencing systemsGeoreferencing systems Map projections Map projections

Where are we going?Where are we going?

One more theoretical issue: uncertaintyOne more theoretical issue: uncertainty

Then onto more practical issues: Then onto more practical issues: GIS data collection (including GPS)GIS data collection (including GPS) GIS databasesGIS databases Cartography and map production Cartography and map production Geographical analysisGeographical analysis GIS and societyGIS and society

UncertaintyUncertainty

Uncertainty arises from the way that we Uncertainty arises from the way that we conceive of the world (geographic conceive of the world (geographic representation), how we measure and represent representation), how we measure and represent it (digital model), and how we analyze the it (digital model), and how we analyze the representations. representations.

All of these add up – uncertainty increases All of these add up – uncertainty increases from the start of the project to the end. from the start of the project to the end.

Terms to considerTerms to consider

Error (differences between observers or between Error (differences between observers or between measuring instruments)measuring instruments)

Accuracy (difference between reality and Accuracy (difference between reality and ourour representation of reality)representation of reality)

Precision (the repeatability of measurements)Precision (the repeatability of measurements) Quality (attribute accuracy, positional accuracy, Quality (attribute accuracy, positional accuracy,

logical consistency, completelness, and lineage)logical consistency, completelness, and lineage)

Filter 1: ConceptionFilter 1: Conception

Spatial uncertaintySpatial uncertainty Do NaturalDo Natural geographic units exist? geographic units exist? Scales for bivariate/multivariate analyses?Scales for bivariate/multivariate analyses? Discrete objects more reliant on “natural units”Discrete objects more reliant on “natural units”

Vagueness (in boundaries, membership)Vagueness (in boundaries, membership) Statistical, cartographic, cognitiveStatistical, cartographic, cognitive

AmbiguityAmbiguity Different labels by different national or cultural groups, Different labels by different national or cultural groups,

language (GIS is not value-neutral!!)language (GIS is not value-neutral!!)

IndicatorsIndicators

Direct – a clear correspondence with mapped Direct – a clear correspondence with mapped phenomenonphenomenon

Indirect (or proxy) – best available measureIndirect (or proxy) – best available measure Selection of indicators is subjectiveSelection of indicators is subjective Differences in definitions are a major Differences in definitions are a major

impediment to integration of geographic data impediment to integration of geographic data over wide areasover wide areas

Direct indicator for joblessness: Number of Direct indicator for joblessness: Number of unemployed (measured as those collecting unemployed (measured as those collecting unemployment benefits)unemployment benefits)

Indirect indicators of joblessness: crime rates, Indirect indicators of joblessness: crime rates, visits to soup kitchens visits to soup kitchens

Fuzzy Approaches to UncertaintyFuzzy Approaches to Uncertainty

In fuzzy set theory, it is possible to have In fuzzy set theory, it is possible to have partial membership in a setpartial membership in a set membership can vary, e.g. from 0 to 1membership can vary, e.g. from 0 to 1 this adds a third option to classification: yes, no, this adds a third option to classification: yes, no,

and maybeand maybe Fuzzy approaches have been applied to the Fuzzy approaches have been applied to the

mapping of soils, vegetation cover, land use, mapping of soils, vegetation cover, land use, and vulnerabilityand vulnerability

Scale & Geographic IndividualsScale & Geographic Individuals

RegionsRegions Uniformity (internal homogeneity)Uniformity (internal homogeneity) Functional zones (boundaries as breakpoints)Functional zones (boundaries as breakpoints)

Relationships typically grow stronger when Relationships typically grow stronger when based on larger geographic unitsbased on larger geographic units

Scale and Spatial Scale and Spatial AutocorrelationAutocorrelation

No. of geographicNo. of geographic CorrelationCorrelation

areasareas

4848 .2189.2189

2424 .2963.2963

1212 .5757.5757

66 .7649.7649

33 .9902.9902

Filter 2: Filter 2: Measurement/representationMeasurement/representation

Representational models filter reality Representational models filter reality differentlydifferently Vector (requires a priori conceptualization of Vector (requires a priori conceptualization of

geographic features as discrete objects)geographic features as discrete objects) Raster (boundaries seldom resemble natural Raster (boundaries seldom resemble natural

features, but convenient and efficient…)features, but convenient and efficient…)

0.9 – 1.0

0.5 – 0.9

0.1 – 0.5

0.0 – 0.1

Other issuesOther issues

Measurements only Measurements only accurateaccurate to a limited to a limited extentextent

‘‘Continuous’ scales are in practice discreteContinuous’ scales are in practice discrete Discrete isopleth/choropleth map displayDiscrete isopleth/choropleth map display Choropleth mapping in multivariate casesChoropleth mapping in multivariate cases Box 4.3 explains the difference!Box 4.3 explains the difference!

Spatially Intensive versus Extensive Spatially Intensive versus Extensive VariablesVariables

Choropleth maps use values describing properties of Choropleth maps use values describing properties of non-overlapping areas (municipalities, states, non-overlapping areas (municipalities, states, countries)countries)

Extensive variables: values true for the entire area are Extensive variables: values true for the entire area are the same color: E.g. Total populationthe same color: E.g. Total population

Intensive variables: values could potentially be true Intensive variables: values could potentially be true for every part of the area (but actuall represent an for every part of the area (but actuall represent an average). E.g. Population density. average). E.g. Population density.

Measurement ErrorMeasurement Error

Digitizing errorsDigitizing errors Automated solutionsAutomated solutions Conflation of adjacent map sheetsConflation of adjacent map sheets

Data Integration and LineageData Integration and Lineage

ConcatenationConcatenation E.g. polygon overlayE.g. polygon overlay

ConflationConflation E.g. rubber sheetingE.g. rubber sheeting

Persistent error indicates shared lineagePersistent error indicates shared lineage Errors tend to exhibit strong positive spatial Errors tend to exhibit strong positive spatial

autocorrelationautocorrelation

Filter 3: AnalysisFilter 3: Analysis

Can good spatial analysis develop on uncertain Can good spatial analysis develop on uncertain foundations?foundations? Can rarely correct Can rarely correct sourcesource More usually tackle More usually tackle operation operation (internal validation)(internal validation) Conflation/concatenation allows Conflation/concatenation allows external validation external validation of of

zonal averaging effectszonal averaging effects Error propagation measures impacts of uncertainty in Error propagation measures impacts of uncertainty in

data on the resultsdata on the results

Ecological FallacyEcological Fallacy

Inappropriate inference from aggregate data Inappropriate inference from aggregate data about the characteristics of individualsabout the characteristics of individuals

Fundamental difference between geography Fundamental difference between geography and other scientific disciplines is that and other scientific disciplines is that definitions of objects of study is almost always definitions of objects of study is almost always ambiguous.ambiguous.

Modifiable Areal Unit Problem Modifiable Areal Unit Problem (MAUP)(MAUP)

Scale + aggregation = MAUPScale + aggregation = MAUP can be can be investigatedinvestigated through simulation of large through simulation of large

numbers of alternative zoning schemesnumbers of alternative zoning schemes Apparent spatial distributions which are Apparent spatial distributions which are

unrepresentative of the scale and configuration of unrepresentative of the scale and configuration of real-world geographic phenomena (example: urban real-world geographic phenomena (example: urban density)density)

SummarySummary

Uncertainty is more than errorUncertainty is more than error Richer representations can Richer representations can createcreate uncertainty! uncertainty! Need for Need for a prioria priori understanding of data and understanding of data and

sensitivity analysissensitivity analysis Spatial analysis is often context-sensitive (you Spatial analysis is often context-sensitive (you

need to know your data and place!)need to know your data and place!)

Living with UncertaintyLiving with Uncertainty

Acknowledge that uncertainty is inevitableAcknowledge that uncertainty is inevitable Data should never be taken as truth (assess whether it Data should never be taken as truth (assess whether it

is suitable)is suitable) Uncertainties in outputs may exceed uncertainties in Uncertainties in outputs may exceed uncertainties in

inputs because many GIS processes are highly non-inputs because many GIS processes are highly non-linearlinear

Rely on multiple sources of dataRely on multiple sources of data Be honest and informative in reporting the results of Be honest and informative in reporting the results of

GIS analysis.GIS analysis.

The more scientific knowledge we gain, the more uncertain we are likely to be: “Richness of representation and computational power only make us more aware of the range and variety of established uncertainties, and challenge us to integrate new ones” (Longley et al. 2005, p. 152).

Data Acquisition:Data Acquisition:Getting the Map Getting the Map

into the Computerinto the Computer

Data transferData transfer

Input of data from other systems (via Internet, Input of data from other systems (via Internet, CD ROMs, tapes, etc.)CD ROMs, tapes, etc.)

Data captureData capture

Primary (direct measurement, e.g. remote Primary (direct measurement, e.g. remote sensing and surveying)sensing and surveying)

Secondary (derivation from other sources; Secondary (derivation from other sources; digitizing, scanning, etc.)digitizing, scanning, etc.)

GIS maps are digitalGIS maps are digital

Real maps: traditional paper maps that can be Real maps: traditional paper maps that can be touchedtouched

Virtual maps: an arrangement of information Virtual maps: an arrangement of information inside the computer; the GIS can be used to inside the computer; the GIS can be used to generate the map however and whenever generate the map however and whenever necessary. necessary.

GIS Data ConversionGIS Data Conversion

Traditionally the Traditionally the most time-consuming and most time-consuming and expensive part expensive part of a GIS projectof a GIS project

Involves a one-time Involves a one-time costcost Digital maps can be reused and shared.Digital maps can be reused and shared. Requires maintenanceRequires maintenance (eg. updating) (eg. updating)

GIS data can beGIS data can be

Purchased.Purchased. Found from existing sources in digital form.Found from existing sources in digital form. Captured from analog maps by Captured from analog maps by GGEOCODING.EOCODING.

Finding Existing Map DataFinding Existing Map Data

Map librariesMap libraries Reference booksReference books State and local agenciesState and local agencies Federal agenciesFederal agencies Commercial data suppliersCommercial data suppliers

Existing Map DataExisting Map Data

Existing map data can be found through a map Existing map data can be found through a map library, via network searches, or on media library, via network searches, or on media such as CD-ROM and disk.such as CD-ROM and disk.

Many major data providers make their data Many major data providers make their data available via the Internet.available via the Internet.

StatenskartverkStatenskartverkhttp://ngis.statkart.no/katalog/java/katalog.asphttp://ngis.statkart.no/katalog/java/katalog.asp

RasterdataRasterdata TemakartTemakart VektordataVektordata PrimærdataPrimærdata ProsjekterProsjekter

1. Accessing GIS Data1. Accessing GIS Data

Example: Costa RicaExample: Costa Rica

Data CollectionData Collection

One of most expensive GIS activitiesOne of most expensive GIS activities Many diverse sourcesMany diverse sources Two broad types of collectionTwo broad types of collection

Data capture (direct collection)Data capture (direct collection) Data transfer (exchange)Data transfer (exchange)

Two broad capture methodsTwo broad capture methods Primary (direct measurement)Primary (direct measurement) Secondary (indirect derivation)Secondary (indirect derivation)

Data Collection Techniques Data Collection Techniques

RasterRaster VectorVector

PrimaryPrimary Digital remote Digital remote sensing imagessensing images

GPS measurementsGPS measurements

Digital aerial Digital aerial photographsphotographs

Survey Survey measurementsmeasurements

SecondarySecondary Scanned mapsScanned maps Topographic Topographic surveyssurveys

DEMs from mapsDEMs from maps Toponymy data Toponymy data sets from atlasessets from atlases

Toponymy?Toponymy?

ToponymyToponymy is the scientific study of is the scientific study of toponymstoponyms (place-names), their origins, meanings, use and (place-names), their origins, meanings, use and typology. The word is derived from the typology. The word is derived from the GreekGreek τόπος τόπος topostopos, place, and oνομα , place, and oνομα ōnomaōnoma, name. It is itself a , name. It is itself a branch of branch of onomasticsonomastics, the study of names of all kinds., the study of names of all kinds.

A toponym is a A toponym is a namename of a locality, region, or some of a locality, region, or some other part of Earth's surface or an artificial feature. In other part of Earth's surface or an artificial feature. In some cultures, most or all such place names have a some cultures, most or all such place names have a definite meaning in the language; this is not the case, definite meaning in the language; this is not the case, generally, for place names in the generally, for place names in the EnglishEnglish languagelanguage..

GEOCODINGGEOCODING

Geocoding is the conversion of spatial Geocoding is the conversion of spatial information into digital form.information into digital form.

Geocoding involves capturing the map, and Geocoding involves capturing the map, and sometimes also capturing the attributes.sometimes also capturing the attributes.

Primary Data CapturePrimary Data Capture

Capture specifically for GIS useCapture specifically for GIS use Raster – remote sensingRaster – remote sensing

e.g. SPOT and IKONOS satellites and aerial photographye.g. SPOT and IKONOS satellites and aerial photography Passive and active sensorsPassive and active sensors

Resolution is key considerationResolution is key consideration SpatialSpatial SpectralSpectral TemporalTemporal

Secondary Geographic Data Secondary Geographic Data CaptureCapture

Data collected for other purposes can be Data collected for other purposes can be converted for use in GISconverted for use in GIS

Raster conversionRaster conversion Scanning of maps, aerial photographs, documents, Scanning of maps, aerial photographs, documents,

etcetc Important scanning parameters are spatial and Important scanning parameters are spatial and

spectral (bit depth) resolutionspectral (bit depth) resolution

Vector Primary Data CaptureVector Primary Data Capture

SurveyingSurveying Locations of objects determines by angle and distance Locations of objects determines by angle and distance

measurements from known locationsmeasurements from known locations Uses expensive field equipment and crewsUses expensive field equipment and crews Most accurate method for large scale, small areasMost accurate method for large scale, small areas

GPSGPS Collection of satellites used to fix locations on Earth’s Collection of satellites used to fix locations on Earth’s

surfacesurface Differential GPS used to improve accuracyDifferential GPS used to improve accuracy

Vector Secondary Data CaptureVector Secondary Data Capture Collection of vector objects from maps, photographs, Collection of vector objects from maps, photographs,

plans, etc.plans, etc. DigitizingDigitizing

Manual (table) Manual (table) Heads-up and vectorizationHeads-up and vectorization

Photogrammetry – the science and technology of Photogrammetry – the science and technology of making measurements from photographs, etc.making measurements from photographs, etc.

COGO – Coordinate GeometryCOGO – Coordinate Geometry

Managing Data Capture Managing Data Capture ProjectsProjects

Key principlesKey principles Clear plan, adequate resources, appropriate funding, and Clear plan, adequate resources, appropriate funding, and

sufficient timesufficient time Fundamental tradeoff between Fundamental tradeoff between

Quality, speed and priceQuality, speed and price Two strategiesTwo strategies

IncrementalIncremental ‘‘Blitzkrieg’ (all at once)Blitzkrieg’ (all at once)

Alternative resource optionsAlternative resource options In houseIn house Specialist external agencySpecialist external agency

SummarySummary

Data collection is very expensive, time-consuming, Data collection is very expensive, time-consuming, tedious and error pronetedious and error prone

Good procedures required for large scale collection Good procedures required for large scale collection projectsprojects

Main techniquesMain techniques PrimaryPrimary

Raster – e.g. remote sensingRaster – e.g. remote sensing Vector – e.g. field surveyVector – e.g. field survey

SecondarySecondary Raster – e.g. scanningRaster – e.g. scanning Vector – e.g. table digitizingVector – e.g. table digitizing

DigitizingDigitizing

Captures map data by tracing lines from a map Captures map data by tracing lines from a map by handby hand

Uses a cursor and an electronically-sensitive Uses a cursor and an electronically-sensitive tablettablet

Result is a string of points with (x, y) valuesResult is a string of points with (x, y) values

DigitizerDigitizer

The Digitizing TabletThe Digitizing Tablet

Digitizer cursor transmitsa pulse from an electomagneticcoil under the view lens.

Pulse is picked up bynearest grid wires undertablet surface.

Result is sent tocomputer afterconversion tox and y units.

map

DigitizingDigitizing

Stable base mapStable base map Fix to tabletFix to tablet Digitize controlDigitize control Determine coordinate transformationDetermine coordinate transformation Trace featuresTrace features Proof plotProof plot EditEdit Clean and buildClean and build

Selecting points to digitizeSelecting points to digitize

ScannerScanner

Scanning Scanning

Places a map on a glass plate, and passes a Places a map on a glass plate, and passes a light beam over itlight beam over it

Measures the reflected light intensityMeasures the reflected light intensity Result is a grid of pixelsResult is a grid of pixels Image size and resolution are importantImage size and resolution are important Features can “drop out”Features can “drop out”

Scanning exampleScanning example

This section of map was scanned, resulting in a file in TIF format that was bytes in size. This was a file of color intensities between 0 and 255 for red, green, and blue in each of three layers spaced on a grid 0.25 millimeter apart. How much data would be necessary to capture the features on your map as vectors? Would it be more or less than the grid (raster) file?

Field data collectionField data collection

Pen Portable PC and GPSPen Portable PC and GPS

Data TransferData Transfer

Buy vs build is an important questionBuy vs build is an important question Many widely distributed sources of GIMany widely distributed sources of GI Key catalogs includeKey catalogs include

US NSDI Clearinghouse networkUS NSDI Clearinghouse network Geography NetworkGeography Network

Access technologiesAccess technologies TranslationTranslation Direct readDirect read

Attribute data Attribute data

Logically can be thought of as in a flat fileLogically can be thought of as in a flat file Table with rows and columnsTable with rows and columns Attributes by recordsAttributes by records Entries called values.Entries called values.

Database Management SystemsDatabase Management Systems

Data definition module sets constraints on the attribute valuesData definition module sets constraints on the attribute values Data entry module to enter and correct valuesData entry module to enter and correct values Data management system for storage and retrievalData management system for storage and retrieval DData definitions can be listed as a data dictionaryata definitions can be listed as a data dictionary Database manager checks values with this dictionary, Database manager checks values with this dictionary,

enforcing data validation.enforcing data validation.

The Role of ErrorThe Role of Error

Map and attribute data errors are the data Map and attribute data errors are the data producer's responsibility, but the GIS user producer's responsibility, but the GIS user must understand error.must understand error.

Accuracy and precision of map and attribute Accuracy and precision of map and attribute data in a GIS affect all other operations, data in a GIS affect all other operations, especially when maps are compared across especially when maps are compared across scales.scales.