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GIS Lecture 2Map Design

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Outline

•Vector GIS•Graphic Elements•Colors•Graphical Hierarchy•Choropleth Maps•Map Layers•Scale Thresholds•Hyperlinks

Vector GIS

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Graphic Features on the World

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Turned into a GIS Map

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Vector GIS

Point

Line

Polygon

Lines

Polygons

Points

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Points

Data Attached to Points

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Points

Burglaries

Drug Calls

Same data displayed as two different points

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Queries and Restrictions•Restricts the features to a specific subset

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Lines

Highways, Major Roads

Street Centerlines

Curbs

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Polygons

Point

Line

Polygon

GreenSpaces

Buildings

Census Blocks

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Graphic Elements

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Jacques Bertin

Visualization Information

“What should be printed to facilitate “communication”, that is, to tell others what we know without a loss of information”

-Jacques Bertin, Paris, February 1983

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Bertin’s Graphic Variables

Saturation

Value Hue

More Value

Shape

Texture

Size

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Saturation

Value Hue

More ValueTexture

SizeShape

Shape Symbols

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Shape (Point) Guidelines

•Use simple shapes •Use point markers that have boundary lines and solid-color fill for important points

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Simple, Solid Points

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Boundary Lines

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Saturation

Value Hue

More Value

Shape

Texture

Size

Size

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Size Make the differences in size as large as possible

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Saturation

Value Hue

More Value

Shape Size

Texture

Texture

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Texture

•Black and White Prints•Polygons•Large Areas

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Shape

Texture

Size

Saturation

Hue

More Value

Value

Value

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Value

Increase/Decrease Contrast

The greater the difference in value between an object and its background, the greater the contrast.

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Value

By creating a pattern of dark to light values, even when the objects are equal in shape and size, it leads the eye in the direction of dark to light

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Value

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Shape

Texture

Orientation

Size Saturation

Value Hue

More Value

Value

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More Value

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Shape

Texture

Orientation

Size Saturation

Value

More Value

Hue

Hue

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Color Hues

Each of individual color is a hue

Colors have meaning (i.e. cool colors, warm colors, political meanings)

-Cool colors calming

-Warm colors exciting

-Cool colors appear smaller than warm colors and they visually recede on the page so red can visually overpower and stand out over blue even if used in equal amounts.

www.colormatters.com

www.colorbrewer.org

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Color Wheel red

violet

blue

orange

yellow

green

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Color Wheel Harmony

•two adjacent huesred

violet

blue

orange

yellow

green

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Color Wheel Harmony

•two adjacent huesred

violet

blue

orange

yellow

green

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Color Wheel Harmony

•two adjacent huesred

violet

blue

orange

yellow

green

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Color Wheel Harmony

•two adjacent hues

Contrast •two hues with one hue skipped in between

red

violet

blue

orange

yellow

green

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Color Wheel Harmony

•two adjacent hues

Contrast •two hues with one hue skipped in between

red

violet

blue

orange

yellow

green

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Color Wheel Harmony

•two adjacent hues

Contrast •two hues with one hue skipped in between

red

violet

blue

orange

yellow

green

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Color Wheel Harmony

•two adjacent hues

Contrast •two hues with one hue skipped in between

red

violet

blue

orange

yellow

green

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Non-Contrasting vs. Contrasting

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Shape

Texture

Orientation

Size

Value Hue

More Value Saturation

Saturation

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Saturation

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Saturation

Customize the Properties…of a layer

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Double-Ended Scales

Extremes Emphasized•Example: gains or loss over time•purple and orange contrast•white center is ground

purple

orange

white

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Change Map Example

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Color Spot

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White background allows yellow color spot to be visualized

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Color Spot Ramps

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Graphical Hierarchy

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Graphical Hierarchy Goal

•direct attention toward or away from available Information

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Graphical Hierarchy Goal

•direct attention toward or away from available Information

Figure-Ground•visual separation of a scene into recognizable figures and inconspicuous background (ground)

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Graphical Hierarchy Ground

•larger of two contrasting areas

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Graphical Hierarchy Ground

•larger of two contrasting areas

•grays, light browns, heavily saturated hues

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Graphical Hierarchy Ground

•larger of two contrasting areas

•grays, light browns, heavily saturated hues

Figure•long wavelength hues•coarse texture

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Graphical Hierarchy Ground

•larger of two contrasting areas

•grays, light browns, heavily saturated hues

Figure•long wavelength hues•coarse texture•strong edge

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Choropleth Maps

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Choropleth Maps

Map using different colors or patterns to show different values

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Classifying Data Process of placing data into groups that have a similar characteristic or value

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Numeric Intervals Non-overlapping and exhaustive intervals covering the range of values for an attribute

•Keep the number of intervals as small as possible to help simplify the user’s ability to absorb information

•Cut points (break points) are points at which we choose to break the total attribute range up into these intervals

•Use a mathematical progression or formula instead of picking arbitrary values – less likely to be accused of manipulating data

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Numeric Intervals (Continued)

Numeric interval options: Equal intervals-Consistent widths-Easy to understand-Use equal width intervals in multiples of 2,5, or 10.-Example: 0-100, 100-200, 200-300, 300 and greater

Increasing interval widths-Long-tailed distributions-Example: 0-5, 5-15, 15-35, 35-75

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Numeric Intervals (Continued)

Exponential Scale-Popular method of increasing intervals-Use break values that are powers such as 2n or 3n-Generally start out with zero as an additional class if that value appears in your data -Example: 0, 1–2, 3–4, 5–8, 9–16, and so forth

Quantiles-Separating a distribution into equal sizes of feature attribute records per interval-Example: 0-25%, 25%-50%, 50%-75%,75%-100%

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Numeric Intervals (Continued)

•Use quantile numeric scales for analytical maps, but use equal interval scales for general public maps

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Custom Scales

Edit the classifications and layer properties

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Original Map (Natural Breaks)

Uninsured U.S. Population, 2005

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Custom Map (Equal Intervals)

Uninsured U.S. Population, 2005

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Other Numeric Intervals

BMI! 18.5 - 24.9

25.0 - 29.9

30.0+

Percentage in Poverty0 - 12.5%

12.51% - 19.99%

20.0% - 39.99%

40.0% - 70.10%

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Data Sources: BRFSS data, 2000; Reference USA,City of Pgh City Planning Dept., U.S. Census 2000

Pittsburgh, PA: Neighborhood proportion under poverty and average BMI per neighborhood

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Normalizing Data

Divides one numeric attribute by another in order to minimize differences in values based on the size of areas or number of features in each area

Examples:•Dividing the 5 to 17 year-old population by the total population yields the percentage of people aged 5-17

•Dividing a value by the area of the feature yields a value per unit area, or density

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Normalizing Data

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Normalizing Data

Percent Population 5-17

6.9% - 12.4%

12.5% - 17.9%

18.0% - 23.4%

23.5% - 28.9%

29.0% - 34.4%

Map Layers, Scale Thresholds, and Hyperlinks

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Map Layers

Organizes your layersGroup logically and rename

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Scale ThresholdsMinimum Scale Range-If you zoom out beyond this scale, the layer will not be visible

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Scale ThresholdsWhen you zoom in, the layers are visible

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Scale ThresholdsMaximum Scale Range-If you zoom in beyond this scale, the layer will not be visible -State Capitals not visible at this scale

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Hyperlinks Links images, documents, WEB pages, etc. via features on a map

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Summary

•Vector GIS•Graphic Elements•Colors•Graphical Hierarchy•Choropleth Maps•Map Layers•Scale Thresholds•Hyperlinks