Cartographic abstractionCartographic abstraction

Summary sessionSummary session

GEO381/550GEO381/550

October 5October 5thth, 2004, 2004

OutlinesOutlines

BasicsBasics Geographic phenomenonGeographic phenomenon Describing data distributionDescribing data distribution

Components of cartographic abstractionComponents of cartographic abstraction Data classificationData classification

Quantitative classification methodsQuantitative classification methods

SimplificationSimplification Map symbolizationMap symbolization

Visual variables by measurement scaleVisual variables by measurement scale Map types by the behavior of geographic phenomenonMap types by the behavior of geographic phenomenon

BasicsBasics

GGeographic phenomenoneographic phenomenon

MMeasurement scaleeasurement scale

DData distributionata distribution

Geographic phenomenonGeographic phenomenon

Location, ScaleLocation, ScaleSpatial dimensionSpatial dimensionContinuous vs. discrete Continuous vs. discrete

Q. number, Mars, human organQ. number, Mars, human organQ. Tornado path, elevationQ. Tornado path, elevationQ. Temperature, cold/hot, population, Q. Temperature, cold/hot, population,

population densitypopulation density

Measurement scale Measurement scale of geographic phenomenonof geographic phenomenon

NominalNominal OrdinalOrdinal Interval/Interval/RatioRatio

ConceptConcept Type, Type, categorycategory

Result of Result of rankingranking

Result of Result of measuringmeasuring

ExampleExample Male/female, Male/female, agricultural agricultural regionregion

Mega/Mega/large/large/medium/medium/small citysmall city

TemperatureTemperature, Mortality , Mortality raterate

Year, land use, elevation, strongly agree/strongly disagree, religion, coffee consumption, national income, occupation

Describing data distributionDescribing data distribution

NominalNominal OrdinalOrdinal Interval/Interval/RatioRatio

Central Central tendencytendency

Mode: most Mode: most frequently frequently occurring occurring valuevalue

Median: Median: value exactly value exactly in half when in half when rankedranked

Mean: Mean:

= = ΣΣx x / N/ N

DispersionDispersion Variation Variation ratioratio

Quartile Quartile deviationdeviation

Standard Standard deviationdeviation

ΣΣ ( (xx--))22 / N / N

Histogram and descriptive statisticsHistogram and descriptive statistics

Components of Components of cartographic abstractioncartographic abstraction

SSelectionelectionCClassificationlassificationSSimplificationimplificationSSymbolizationymbolization

SelectionSelection preliminary stepspreliminary steps

ClassificationClassificationSimplificationSimplification data processingdata processing

SymbolizationSymbolization choosing symbolschoosing symbols

ClassificationClassification

Group values into class such that Group values into class such that geographic pattern can be better revealedgeographic pattern can be better revealed

How do you determine class How do you determine class boundary?boundary?

Equal intervalEqual interval put any number of values into class with the same put any number of values into class with the same

intervalinterval QuantileQuantile

put the same number of values into classput the same number of values into class Natural breakNatural break

marginal change in valuesmarginal change in values Standard deviationStandard deviation

how much deviated from the mean?how much deviated from the mean?

Data classification methodData classification method

σ

l1 l2 l3 l4 l5 a1 a2 a5 a4 a5

Equal interval Quantile

Natural break Standard deviation

SimplificationSimplification

Alter geometry such that relevant details Alter geometry such that relevant details are pronounced while irrelevant details are are pronounced while irrelevant details are suppressedsuppressed

Line simplification Area dissolution

Criteria for symbolizationCriteria for symbolization

Measurement scale Measurement scale visual variables visual variables Use ordering visual var. for quantitative scaleUse ordering visual var. for quantitative scale Use distinguishing visual var. for qualitative scaleUse distinguishing visual var. for qualitative scale

The behavior of phenomenon The behavior of phenomenon map types map types Observed in a discrete/continuous scale & in a Observed in a discrete/continuous scale & in a

abrupt/smooth frequencyabrupt/smooth frequency Maps sometimes reflect the way data collected rather Maps sometimes reflect the way data collected rather

than phenomenon. (e.g. crime is reported in the unit than phenomenon. (e.g. crime is reported in the unit of jurisdiction)of jurisdiction)

Appropriate use of visual variablesAppropriate use of visual variables- measurement scale -- measurement scale -

qualitativequalitative quantitativequantitative

pointpoint ShapeShape SizeSize

lineline Shape, HueShape, Hue SizeSize

areaarea Hue, ArrangementHue, Arrangement Value, TextureValue, Texture

Appropriate choice of map types Appropriate choice of map types - behavior of phenomenon -- behavior of phenomenon -

abruptabrupt smoothsmooth

discretediscrete Graduated Graduated symbol mapsymbol map

Dot density Dot density mapmap

ChorodotChorodot

continuouscontinuous Choropleth Choropleth mapmap

Isopleth Isopleth mapmap

Because of the discrepancy between phenomenon and data, we need to process data by manipulating spatial scale…. Handling GIS data well is an essential skill for advanced map-making!