Harvard Government 90dn Lecture 5
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Government 90dn Mapping the Census Lecture 5: Cartography
Sumeeta Srinivasan [email protected]
Outline Map Audiences Vector GIS representation Graphic Elements – based on vectors Colors Graphical Hierarchy Map Types Normalizing Data Map Layouts Exporting Maps
Map Audiences Map Use:
Exploration
Presentation
Audience:
Trained Analyst
General Public
Map Audiences Map Use:
Exploration
Presentation
Audience: Purpose:
Trained Analyst Visual Thinking
General Public Communication
Map Audiences Map Use:
Exploration
Presentation
Audience: Purpose:
Trained Analyst Visual Thinking
General Public Communication
Advantages: Graphical
Believable
Map Audiences Map Use:
Exploration
Presentation
Audience: Purpose:
Trained Analyst Visual Thinking
General Public Communication
Advantages: Graphical Granularity: Fine
Believable Coarse
Map Audiences Map Use:
Exploration
Presentation
Audience: Purpose:
Trained Analyst Visual Thinking
General Public Communication
Advantages: Graphical Granularity: Fine
Believable Coarse
Symbols:
Mimetic
capital railroad
Abstract
Vector GIS Point Line Polygon
Points Data Attached to Points
Points Same data displayed as different points
Lines
Polygons Point Line Polygons Green Spaces Buildings Census Blocks
Jacques Bertin “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
Bertin’s Graphic Variables Shape
Texture
Orientation
Size
Value
Hue
More Value
Saturation
Point Symbols Shape
Texture
Orientation
Size
Value
Hue
More Value
Saturation
Use Solid Point Markers
Use Three to Seven Categories Max
Orientation Shape
Texture
Orientation
Size
Value
Hue
More Value
Saturation
Texture Shape
Texture
Orientation
Size
Value
Hue
More Value
Saturation
Texture Black and White Prints Polygons Large Areas
Texture Brings object to the front (figure) long wavelength hues coarse texture
Size Shape
Texture
Orientation
Size 0-25 4-9 >9
Value
Hue
More Value
Saturation
Size Graduated Symbols Show Size or Amount
Elevated Blood Levels ( !
1 - 25
! (
26 - 50
( !
51 - 150
Value Shape
Texture
Orientation
Size
Value
Hue
More Value
Saturation
Value Increase/Decrease Contrast The greater the difference in value between an object and its background, the greater the contrast
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
Value
Value
Hue Shape
Texture
Orientation
Size
Value
Hue
More Value
Saturation
Value Shape
Texture
Orientation
Size
Value
Hue
More Value
Saturation
Saturation Shape
Texture
Orientation
Size
Value
Hue
More Value
Saturation
Saturation You can change the saturation of a hue by adding black (shadow) or white (light). The amount of saturation gives us our shades and tints.
Percentage Female-Headed Households with Children 0% to 4% 4% to 8% 8% to 12 % Grea ter than 12%
Saturation Customize the Properties…of a layer
Color Hues and Values Each of individual color is a hue Colors have meaning (i.e. cool colors, warm colors, etc) -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
Color Wheel red orange
violet
yellow
blue green
Color Wheel Harmony two adjacent hues
red orange
violet
yellow
blue green
Color Wheel Harmony two adjacent hues
red orange
violet
yellow
blue green
Color Wheel Harmony two adjacent hues
red orange
violet
yellow
blue green
Color Wheel Harmony two adjacent hues
red orange
violet
yellow
blue
Contrast two hues with one hue skipped in between
green
Color Wheel Harmony two adjacent hues
red orange
violet
yellow
blue
Contrast two hues with one hue skipped in between
green
Color Wheel Harmony two adjacent hues
red orange
violet
yellow
blue
Contrast two hues with one hue skipped in between
green
Color Wheel Harmony two adjacent hues
red orange
violet
yellow
blue
Contrast two hues with one hue skipped in between
green
Non-Contrasting vs. Contrasting
Color Wheel Harmony two adjacent hues
red orange
violet
yellow
blue
Contrast two hues with one hue skipped in between Clash Opposites
green
Double-Ended Scales Extremes Emphasized critical value of zero regression residuals, blue and red contrast white center is ground
red
white
blue
<-4
-4 to -2 time change -2 to 2 2 to 4 <=4
Change Map Example
Color Spot White background allows yellow color spot to be visualized
0903 0809
0604 0605
0802 0804 0507 0810
Color Spot Ramps
Graphical Hierarchy Goal direct attention toward or away from available Information
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)
Graphical Hierarchy Ground larger of two contrasting areas
Graphical Hierarchy Ground grays, light browns, heavily saturated hues
Graphical Hierarchy Figure long wavelength hues coarse texture
Graphical Hierarchy Ground
Figure long wavelength hues coarse texture strong edge
Maps (Types) 1. 2. 3. 4.
Choropleth maps Isopleth maps Proportional symbol maps Dot maps
Maps (Isopleth)
Proportional symbol maps http://www.colorado.edu/geography/course s/geog_3053_s05/Lectures/Proportional%2 0Symbol%20Maps.htm
Maps (Dot density)
Cartograms (2004 Elections by County)
http://www-personal.umich.edu/~mejn/election/
Choropleth Maps
Classifications Process of placing data into groups that have a similar characteristic or value
Classifications Natural Breaks Classes are based on natural groupings inherent in the data Looks for where there are big jumps in data
Quantiles Each class contains an equal number of features Good for linearly distributed data
Equal Interval Divides the range of attribute values into equal-sized Subranges (e.g. 0–100, 101–200, and 201–300)
Standard Deviation Calculates mean and then maps 1-2standard deviations above / below mean
Custom Scales Know your data!
Custom Scales Edit the classifications and layer properties
Original Map
Legend State s
Total Population POP2003 -99 - 124,013 124,014 - 447,485 447,486 - 1,12 9,78 8 1,129,789 - 2,498,338 2,498,339 - 5,393,431 5,393,432 - 9,873,548
Custom Map
Total U.S. Population, 2003 0 - 9,99 9 10,000 - 24,999 25,000 - 49,999 50,000 - 99,999 100 ,000 - 499 ,999 500 ,000 - 9,873,548
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
Normalizing Data
Normalizing Data
Percent Population 5-17 6.9% - 1 2.4 % 12.5% - 17.9% 18.0% - 23.4% 23.5% - 28.9% 29.0% - 34.4%
Map Layouts
Printed Map Layouts Concise Title Topic, place, time
Legend Word “Legend” or “Key” not needed
Data Source Source and date data was obtained
U.S. Population by County
Total U.S. Population, 2003 0 - 9,99 9 10,000 - 24,999 25,000 - 49,999 50,000 - 99,999 100 ,000 - 499 ,999 500 ,000 - 9,873,548
Data obtained from U.S. Census
Map Elements
Scale Direction Indicator Photos / Images Neat-lines
Example of a bad map...
Sumeeta Srinivasan [email protected]
Outline Map Audiences Vector GIS representation Graphic Elements – based on vectors Colors Graphical Hierarchy Map Types Normalizing Data Map Layouts Exporting Maps
Map Audiences Map Use:
Exploration
Presentation
Audience:
Trained Analyst
General Public
Map Audiences Map Use:
Exploration
Presentation
Audience: Purpose:
Trained Analyst Visual Thinking
General Public Communication
Map Audiences Map Use:
Exploration
Presentation
Audience: Purpose:
Trained Analyst Visual Thinking
General Public Communication
Advantages: Graphical
Believable
Map Audiences Map Use:
Exploration
Presentation
Audience: Purpose:
Trained Analyst Visual Thinking
General Public Communication
Advantages: Graphical Granularity: Fine
Believable Coarse
Map Audiences Map Use:
Exploration
Presentation
Audience: Purpose:
Trained Analyst Visual Thinking
General Public Communication
Advantages: Graphical Granularity: Fine
Believable Coarse
Symbols:
Mimetic
capital railroad
Abstract
Vector GIS Point Line Polygon
Points Data Attached to Points
Points Same data displayed as different points
Lines
Polygons Point Line Polygons Green Spaces Buildings Census Blocks
Jacques Bertin “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
Bertin’s Graphic Variables Shape
Texture
Orientation
Size
Value
Hue
More Value
Saturation
Point Symbols Shape
Texture
Orientation
Size
Value
Hue
More Value
Saturation
Use Solid Point Markers
Use Three to Seven Categories Max
Orientation Shape
Texture
Orientation
Size
Value
Hue
More Value
Saturation
Texture Shape
Texture
Orientation
Size
Value
Hue
More Value
Saturation
Texture Black and White Prints Polygons Large Areas
Texture Brings object to the front (figure) long wavelength hues coarse texture
Size Shape
Texture
Orientation
Size 0-25 4-9 >9
Value
Hue
More Value
Saturation
Size Graduated Symbols Show Size or Amount
Elevated Blood Levels ( !
1 - 25
! (
26 - 50
( !
51 - 150
Value Shape
Texture
Orientation
Size
Value
Hue
More Value
Saturation
Value Increase/Decrease Contrast The greater the difference in value between an object and its background, the greater the contrast
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
Value
Value
Hue Shape
Texture
Orientation
Size
Value
Hue
More Value
Saturation
Value Shape
Texture
Orientation
Size
Value
Hue
More Value
Saturation
Saturation Shape
Texture
Orientation
Size
Value
Hue
More Value
Saturation
Saturation You can change the saturation of a hue by adding black (shadow) or white (light). The amount of saturation gives us our shades and tints.
Percentage Female-Headed Households with Children 0% to 4% 4% to 8% 8% to 12 % Grea ter than 12%
Saturation Customize the Properties…of a layer
Color Hues and Values Each of individual color is a hue Colors have meaning (i.e. cool colors, warm colors, etc) -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
Color Wheel red orange
violet
yellow
blue green
Color Wheel Harmony two adjacent hues
red orange
violet
yellow
blue green
Color Wheel Harmony two adjacent hues
red orange
violet
yellow
blue green
Color Wheel Harmony two adjacent hues
red orange
violet
yellow
blue green
Color Wheel Harmony two adjacent hues
red orange
violet
yellow
blue
Contrast two hues with one hue skipped in between
green
Color Wheel Harmony two adjacent hues
red orange
violet
yellow
blue
Contrast two hues with one hue skipped in between
green
Color Wheel Harmony two adjacent hues
red orange
violet
yellow
blue
Contrast two hues with one hue skipped in between
green
Color Wheel Harmony two adjacent hues
red orange
violet
yellow
blue
Contrast two hues with one hue skipped in between
green
Non-Contrasting vs. Contrasting
Color Wheel Harmony two adjacent hues
red orange
violet
yellow
blue
Contrast two hues with one hue skipped in between Clash Opposites
green
Double-Ended Scales Extremes Emphasized critical value of zero regression residuals, blue and red contrast white center is ground
red
white
blue
<-4
-4 to -2 time change -2 to 2 2 to 4 <=4
Change Map Example
Color Spot White background allows yellow color spot to be visualized
0903 0809
0604 0605
0802 0804 0507 0810
Color Spot Ramps
Graphical Hierarchy Goal direct attention toward or away from available Information
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)
Graphical Hierarchy Ground larger of two contrasting areas
Graphical Hierarchy Ground grays, light browns, heavily saturated hues
Graphical Hierarchy Figure long wavelength hues coarse texture
Graphical Hierarchy Ground
Figure long wavelength hues coarse texture strong edge
Maps (Types) 1. 2. 3. 4.
Choropleth maps Isopleth maps Proportional symbol maps Dot maps
Maps (Isopleth)
Proportional symbol maps http://www.colorado.edu/geography/course s/geog_3053_s05/Lectures/Proportional%2 0Symbol%20Maps.htm
Maps (Dot density)
Cartograms (2004 Elections by County)
http://www-personal.umich.edu/~mejn/election/
Choropleth Maps
Classifications Process of placing data into groups that have a similar characteristic or value
Classifications Natural Breaks Classes are based on natural groupings inherent in the data Looks for where there are big jumps in data
Quantiles Each class contains an equal number of features Good for linearly distributed data
Equal Interval Divides the range of attribute values into equal-sized Subranges (e.g. 0–100, 101–200, and 201–300)
Standard Deviation Calculates mean and then maps 1-2standard deviations above / below mean
Custom Scales Know your data!
Custom Scales Edit the classifications and layer properties
Original Map
Legend State s
Total Population POP2003 -99 - 124,013 124,014 - 447,485 447,486 - 1,12 9,78 8 1,129,789 - 2,498,338 2,498,339 - 5,393,431 5,393,432 - 9,873,548
Custom Map
Total U.S. Population, 2003 0 - 9,99 9 10,000 - 24,999 25,000 - 49,999 50,000 - 99,999 100 ,000 - 499 ,999 500 ,000 - 9,873,548
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
Normalizing Data
Normalizing Data
Percent Population 5-17 6.9% - 1 2.4 % 12.5% - 17.9% 18.0% - 23.4% 23.5% - 28.9% 29.0% - 34.4%
Map Layouts
Printed Map Layouts Concise Title Topic, place, time
Legend Word “Legend” or “Key” not needed
Data Source Source and date data was obtained
U.S. Population by County
Total U.S. Population, 2003 0 - 9,99 9 10,000 - 24,999 25,000 - 49,999 50,000 - 99,999 100 ,000 - 499 ,999 500 ,000 - 9,873,548
Data obtained from U.S. Census
Map Elements
Scale Direction Indicator Photos / Images Neat-lines
Example of a bad map...
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