Data SymbolizationScales of MeasurementThe Nominal ScaleThe Ordinal ScaleThe Interval ScaleThe Ratio ScaleThe Ratio ScaleData SymbolizationData SymbolizationData SymbolizationData SymbolizationData SymbolizationMap Design – Thematic MappingChoropleth MapsThematic Mapping Issue:Modifiable Area Unit ProblemClassifying Thematic DataCreating ClassesCreating ClassesThe Effect of ClassificationThe Effect of ClassificationThe Effect of ClassificationThe Effect of ClassificationThe Effect of ClassificationThematic Mapping Issue:Counts Vs. RatiosThematic Mapping Issue:Counts Vs. RatiosProportional Symbol MapsDot Density MapsDot Density MapsCartogramsConventional Map of 2004 Election Results by StatePopulation Cartogram of 2004 Election Results by StateElectoral College Cartogram of 2004 Election Results by StateConventional Map of 2004 Election Results by CountyPopulation Cartogram of 2004 Election Results by CountyGraduated Color Map of 2004 Election Results by CountyGraduated Color Population Cartogramof 2004 Election Results by CountyDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005• The cartographer/map designer must make decisions about how to display thematic data in a map-- generally decisions about what symbols to use to represent real-world geographic phenomena• Variety of issues for symbolization...– discrete vs. continuous geographic phenomena– point, line, and area symbols– recognize and understand nominal, ordinal, interval, and ratio thematic data typesData SymbolizationDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005Scales of Measurement• Thematic data can be divided into four types1. The Nominal Scale2. The Ordinal Scale3. The Interval Scale4. The Ratio ScaleAs we progress through these scales, the types of data they describe have increasing information contentDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005The Nominal Scale• Nominal data - information that is simply grouped into categories on the basis of qualitative considerations– Example: Place namesDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005The Ordinal Scale• Ordinal data - grouped by rank on the basis of some quantitative measure– Example: Small, medium and large townsDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005The Interval Scale• Interval data - information that can be arranged using a standard scale along which operations of addition and subtraction have meaning– Example: Temperature is an interval measure• Interval data is one type of continuous dataDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005The Ratio Scale• Ratio data - other type of continuous data that can be arranged along a scale but, in addition, the scale begins at a non-arbitrary zero point– At the zero point, no features are present– Multiplication and division can be employed with ratio data to consider proportions and magnitudes– Examples: Elevation above sea level, precipitation, populationDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005The Ratio Scale• Ratio dataDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005Data Symbolization•There are a number of characteristics of symbols that we can use of to make visual distinctions in thematic information (Jacques Bertin’s Visual Variables):•Size•Shape•Color Hue (color)•Color Value (intensity)•Texture•Orientation•ArrangementDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005Size• difference in geometric dimensions (e.g. length, height, diameter) of symbols • useful for ordinal, interval, & ratio data; bad for nominal • convention: larger size = greater quantityShape• differences in forms of symbols can be abstract and "geometric", or iconographic • useful for nominal data; bad for for ordinal, interval, & ratio • too many shapes = cluttered & difficult for map reader to discriminateData SymbolizationDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005Color Hue (color)• differences in wavelengths of light reflected (or emitted, in the case of computer monitors)• useful for nominal data, can be used for ordinal & interval/ratio data but is tricky • perceptual difficulties for some map readers is a problem (e.g. 6-8% males color-blind)Color Value (intensity)• relative lightness or darkness of symbols• useful for ordinal, interval, & ratio data• convention: darker = higher numerical values• difficult for map readers to perceive more than four or five valuesData SymbolizationDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005Texture• size and spacing of elements that make up a single symbol • dense vs. sparse • can be used for all data scales • danger of aesthetically unpleasing appearanceOrientation• direction of symbols • useful for nominal (e.g. wind direction)Data SymbolizationDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005Arrangement• configuration (random vs. organized or systematic patterns) of symbols• useful for nominal, less so for ordinal, interval, & ratio data • convention: random arrangements are often used to symbolize natural phenomena, systematic used to symbolize human-made phenomenaData SymbolizationDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005Our objectives: • We will consider four thematic map types• choropleth• proportional symbol• dot density• cartograms• understand decisions involved in classifying quantitative data in thematic mapsMap Design – Thematic MappingDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005• Greek: choros (place) + plethos (filled)• These are used to map categorical and quantitative data over defined areas– polygonal enumeration unitse.g. census tract, counties, watersheds, etc.• Data values are generally classified into ranges– allow map reader to readily interpret the map• Polygons can produce misleading impressions– area/size of polygon vs. quantity of thematic data valueChoropleth MapsDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005• Assumption: – Mapped phenomena are uniformly spatially distributed within each polygon unit– This is usually not true!• Boundaries of enumeration units are frequently unrelated to the spatial distribution of the phenomena being mapped• This issue is always present when dealing with data collected or aggregated by polygon unitsThematic Mapping Issue:Modifiable Area Unit ProblemDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005• Data values are classified into ranges for many thematic maps (especially choropleth) – This aids the reader’s