Thematic Mapping: Points Flashcards

1
Q

Thematic Map

A

Map that portrays the form or function of the spatial distribution of one, or a combination of variables
- Statistical Mapping, map data, manipulate data

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2
Q

Classification of Thematic Maps: Qualitative

A
  • Location
  • Boundaries (Administrative etc.)
  • Routes (roads maps)
  • Chorochromatic (Nominal)
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3
Q

Classification of Thematic Maps: Quantitative

A
  • Isopleths
  • Proportional Symbols
  • Dot Maps
  • Cartograms
  • Flow Maps
  • Choropleths
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4
Q

NOIR

A

Nominal, Ordinal, Interval, Ratio

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5
Q

Important Design Criteria

A
  • Points can represent actual points or centroids of areas
  • Idea is to show symbols at each location where the symbol tells the audience something about the data value(s) associated with that location
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6
Q

Nominal Scale: Geometric Symbol

A

Shape (square, triangle, circle)

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7
Q

Nominal Scale: Mimetic symbol

A

Looks like what it is

  • Mime=copy something
  • Fishing location has a symbol that looks like a fish and fish hook for example
  • Sometimes easy to understand, sometimes difficult to interpret (i.e. not doing their job!)
  • Still need legend
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8
Q

Primary design variables

A

Shape
Hue
Orientation

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9
Q

How can you differentiate relative magnitude of symbols?

A
  • Size (Small, medium, large)
  • Value (colour/texture when same size)
  • Both (Useful for multiple variables, shaded colours in small, med, large etc.)
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10
Q

Two Options for Thematic mapping of interval or ratio point data

A
  • Generalize data into range grades (implies loss of detail, not ideal)
  • Make size of symbol directly proportional to size of each data value (complex, can be many symbols)
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11
Q

Design considerations for ratio scaling

A
  • What symbols to use
  • What attribute of the symbol to scale
  • What scaling factor to use (can be psychological)
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12
Q

What are 3 deciding variables for symbol selection?

A
  • Symbol complexity (less intricacy when scaling size
  • Data Complexity
  • Audience
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13
Q

4 steps for generating a mathematical scale for symbols

A
  • Determine radius of largest circle by visual examination of map
  • Select values for observed (Vi) and the value of the largest (Vl)
  • Calculate using ri=(Vi/Vl)^0.5 x rl
  • Draw symbol of calculated radius
  • Repeat until desired effect is reached
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14
Q

Ebbinghaus illusion

A

When a larger circle is seen among smaller circles it appears 10-15% larger
and when the same circle is seen among larger circles it appears smaller
- The effect creates an illusion that the data is different than it actually is
- Effect of illusion can be reduced by drawing internal boundaries

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15
Q

Over & Under estimation of circle sizes

A
  • Overestimate the importance of small circles
  • Underestimate the importance of large circles
  • Adjust by using a psychological scaling factor
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16
Q

Psychological scaling of circles

A
  • Aids perception
  • Change exponent so that bigger looks bigger and smaller looks smaller
  • ri=(Vi/Vl)^0.5716 x rl
  • Flannery scale is often used
  • Psychological scaling factor should be listed in legend (Flannery, directly proportional, etc.)
  • Dent has a table that can be used if data doesn’t work but best option is to fix data
17
Q

Flannery

A
  • Type of psychological scaling factor
  • Often used
  • Used in ArcGIS appearance compensation
18
Q

Range-Graded Proportional Symbols

A
  • Use Dent table
  • Don’t just select random sizes
  • Size choices must be contiguous
19
Q

Proportional Breakdown of Pie Charts

A
  • Find % of total occupied by breakdown category
  • Multiply % by 3.6 (360 degrees/100%)
  • Irrespective of size the angle will always be the same
  • Try to always start a pie chart with a north line, draw largest sector first
20
Q

Legend Design

A
  • Nested (multiple proportional symbols inside each other with value inside or with a leader line)
  • Linear vertical or horizontal
  • Map is key focus so don’t make legend massive
  • Don’t put every size circle on legend
21
Q

Key element of final project

A
  • Don’t leave any empty polygons
  • No Data? Find it or represent another way w/o the proportional symbol
  • Data must have suitable amount of variability