GIS Tutorial 1

1
GIS Tutorial 1

• Lecture 2
• Map design

2
Outline

• Choropleth maps
• Colors
• Vector GIS display
• GIS queries
• Map layers and scale thresholds
• Hyperlinks and map tips

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Choropleth maps

• Lecture 2

4
Choropleth maps

• Color-coded polygon maps
• Use monochromatic scales or saturated colors
• Represent numeric values (e.g. population, number
  of housing units, percentage of vacancies)

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Choropleth map example

• Percentage of vacant housing units by county

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Classifying data

• Process of placing data into groups (classes or
• bins) that have a similar characteristic or value
• Break points
• Breaks the total attribute range up into these
  intervals
• Keep the number of intervals as small as
  possible (5-7)
• Use a mathematical progression or formula
  instead of picking arbitrary values

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Classifications

• Natural breaks (Jenks)
• Picks breaks that best group similar values
  together naturally and maximizes the differences
  between classes
• Generally, there are relatively large jumps in
  value between classes and classes are uneven
• Based on a subjective decision and is the best
  choice for combining similar values
• Class ranges specific to the individual dataset,
  thus it is difficult to compare a map with
  another map

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Classifications

• Quantiles
• Places the same number of data values in each
  class
• Will never have empty classes or classes with too
  few or too many values
• Attractive in that this method produces distinct
  map patterns
• Analysts use because they provide information
  about the shape of the distribution.
• Example 025, 2550, 5075,75100

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Classifications

• Equal intervals
• Divides a set of attribute values into groups
  that contain an equal range of values
• Best communicates with continuous set of data
• Easy to accomplish and read
• Not good for clustered data
• Produces map with many features in one or two
  classes and some classes with no features

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Classifications

• Use mathematical formulas when possible.
• Exponential scales
• 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, 12, 34, 58, 916, and so forth

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Classifications

• Use mathematical formulas when possible
• Increasing interval widths
• Long-tailed distributions
• Data distributions deviate from a bell-shaped
  curve and most often are skewed to the right
  with the right tail elongated
• Example Keep doubling the interval of each
  category, 05, 515, 1535, 3575 have interval
  widths of 5, 10, 20, and 40.

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Original map (natural breaks)
U.S. population by state, 2000
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Equal interval scale

• Not good because too many values fall into low
  classes

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Quantile scale

• Shows that an increasing width (geometric) scale
  is needed

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Custom geometric scale

• Experiment with exponential scales with powers of
  2 or 3.

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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 number of vacant housing units by
  the total number of housing units yields the
  percentage of vacant units
• Dividing the population by area of the feature
  yields a population density

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Nonnormalized data

• Number of vacant housing units by state, 2000

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Normalized data

• Percentage vacant housing units by state, 2000

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Nonnormalized data
California population by county, 2007
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Normalized data
California population density, 2007
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colors

• Lecture 2

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Color overview

• Hue is the basic color
• Value is the amount of white or black in the
  color
• Saturation refers to a color scale that ranges
  from a pure hue to gray or black

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Color wheel

• Device that provides guidance in choosing colors

• Use opposite colors to differentiate graphic
  features
• Three or four colors equally spaced around the
  wheel are good choices for differentiating
  graphic features
• Use adjacent colors for harmony, such as blue,
  blue green, and green or red, red orange, and
  orange

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Light vs. dark colors

• Light colors associated with low values
• Dark colors associated with high values
• Human eye is drawn to dark colors

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Contrast

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

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Monochromatic color scale

• Series of colors of the same hue with color value
  varied from low to high
• Common for choropleth maps
• The darker the color in a monochromatic scale,
  the more important the graphic feature
• Use more light shades of a hue than dark shades
  in monochromatic scales
• The human eye can better differentiate among
  light shades than dark shades

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Monochromatic map

• Values too similar

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Monochromatic map

• A better map, more contrast

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Dichromatic color scale

• An exception to the typical monochromatic scale
  used in most choropleth maps
• Two monochromatic scales joined together with a
  low color value in the center, with color value
  increasing toward both ends
• Uses a natural middle point of a scale, such as 0
  for some quantities (profits and losses,
  increases and decreases)

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Dichromatic map

• Symmetric break points centered on 0 make it easy
  to interpret the map

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Color tips

• Colors have meaning
• Political and cultural
• Cool colors
• Calming
• Appear smaller
• Recede
• Warm colors
• Exciting
• Overpower cool colors

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Color tips

• Do not use all of the colors of the color
  spectrum, as seen from a prism or in a rainbow,
  for color coding
• If you have relatively few points in a point
  layer, or if a user will normally be zoomed in to
  view parts of your map, use size instead of color
  value to symbolize a numeric attribute

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Color tips

• If you have many polygons to symbolize, it is
  better to
• use polygon centroid points with color rather
  than
• polygon choropleth maps.

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Changing colors in ArcMap

• Choose color, more colors

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Learn more about GIS colors

• Website
• http//colorbrewer2.org/
• Books
• Brewer, Cynthia A. 2008. Designed Maps A
  Sourcebook for GIS Users. Redlands ESRI Press
• Brewer, Cynthia A. 2005. Designing Better Maps A
  Guide for GIS Users. Redlands ESRI Press

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Vector gis display

• Lecture 2

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Points, lines, polygons

• Point
• x,y coordinates
• Line
• starting and ending point and may have
  additional shape vertices (points)
• Polygon
• three or more lines joined to form a closed area

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Feature attribute tables

• Store characteristics for vector features
• Layers can be displayed using attributes

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Displaying points

• Single symbols
• All CAD calls

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Displaying points

• Same features, different points
• Based on attributes

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Displaying points

• Industry specific (e.g. crime analysis)
• Good for large scale (zoomed in) maps

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Displaying points

• Industry specific (e.g. schools)
• Not good for multiple features at smaller scales
• Simple points better for analysis

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Displaying points

• Quantities
• Use exaggerated sizes

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Displaying lines

• For analytical maps, most lines are ground
• features and should be light shades (e.g. gray
• or light brown)

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Displaying lines

• Consider using dashed lines to signify less
• important line features and solid lines for the
• important ones

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Displaying polygons

• Consider using no outline or dark gray for
• boundaries of most polygons
• Dark gray makes the polygons prominent enough,
  but not so much that they compete for attention
  with more important graphic features

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Displaying polygons

• Consider using texture for black and white
• copies

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Graphic hierarchy

• Assign bright colors (red, orange, yellow, green,
  blue) to important graphic elements
• Features are known as figure

All features in figure
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Graphic hierarchy

• Assign drab colors to the graphic elements that
  provide orientation or context, especially shades
  of gray
• Features known as ground

Circles in figure, squares and lines in ground
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Graphic hierarchy

• Place a strong boundary, such as a heavy black
  line, around polygons that are important to
  increase figure
• Use a coarse, heavy cross-hatch or pattern to
  make some polygons important, placing them in
  figure

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Graphic hierarchy example
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Gis queries

• Lecture 2

53
GIS queries

• Powerful relationship between data table and
  vector-based graphicsunique to GIS
• Records from a feature attribute table are
  selected by using query criteria
• Query will automatically highlight the
  corresponding graphic features

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Simple attribute queries

• Simple query criterion
• ltdata attributegtlt logical operatorgtltvaluegt
• NatureCode 'DRUGS'
• DATE gt '20040701'
• wild card
• symbol stands for zero, one, or more characters
  of any kind
• NAME like ' BUR'
• Selects any crime with names starting with the
  letters BUR, including burglaries (BUR), business
  burglaries(BURBUS), and residential burglaries
  (BURRES)

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Simple attribute queries
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Compound attribute queries

• Compound query criteria
• Combine two or more simple queries with the
  logical connectives AND or OR
• "NATURE_COD" 'DRUGS' AND "DATE" gt 20040801
• Selects records that satisfy both criteria
  simultaneously
• Result are drug crimes that were committed after
  August 1, 2004

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Compound attribute queries
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Layer groups, scale thresholds

• Lecture 2

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Layer groups

• Organizes layers
• Groups and names logically

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Minimum scale threshold

• When zoomed out beyond this scale, features will
  not be visible
• Tracts not visible when zoomed to the USA

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Minimum scale threshold

• Tracts displayed when zoomed in

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Maximum scale threshold

• When zoomed in, features will not be visible
• State population will disappear when zoomed in to
  a state

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Hyperlinks and map tips

• Lecture 2

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Hyperlinks

• Links images, documents, Web pages, etc. to
  features on a map

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Map tips

• Provide an additional way to find information
  about map features
• Pop up as you hover the mouse pointer over a
  feature

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Summary

• Choropleth maps
• Colors
• Vector GIS display
• GIS queries
• Map layers and scale thresholds
• Hyperlinks and Map tips