Second quiz cartography Flashcards
Types of thematic maps
Dot density
Choropleth
Isarithmic
Flow
Cartogram
Proprotional symbol
When to use Choropleth maps
-Regional patterns
- One variable
- Enumeration units
- The big picture
- Relative data (ratios,proportions,etc)
Pros of Choropleth maps
- Good for geographic areas
- Easy to identify patterns
- Easy to create
- Works with all data measurement scales (nominal, ordinal, interval, ratio)
Cons of Choropleth maps
- Not great at showing population relative to geographic space
- easy to misinterpret
- Color selection can be challenging
- Class breaks can change story quickly
- Data has to be standardized/normalized
When to use Dot Density maps
- no enumeration units
- one or two variables
- cant use color
- absolute data
Pros of Dot Density maps
- Easy to create
- Shows concentrations over space
- Ratio level data
- Can use more than one variable
Cons of Dot Density maps
- must be drawn on equal area map projection
- hard to retrieve rates/numbers from map
- Reader might infer dot locations as absolute locations
When to use Proportional Symbol maps
- Data is attached to geographic points or areas
- More than one variable
- Want to show difference of size or magnitude
- What to show absolute or relative data
Pros of Proportional Symbol Maps
- Easy to make
- Can show ordinal or ratio data
- Easy for reader to conceptualize
- Enumeration unit size doesnt matter
- Can use discrete categories/ range grading
Cons of proportional Symbols maps
- Symbol overload/congestion
- Readers do not estimate the symbol area well
- Tend to require manual maneuvering of symbols because of overload issues
- Large variation in values and data locations is problematic
When to use Isarithmic Maps
- Data is continuous
- Data needs to be visualized on a surface
- Need to connect same values to each other
- Large geographic area
- Control points arent tied to political boundaries
- Want to map natural phenomena
Pros of Isarithmic maps
- Good for mapping real or conceptual surface level data
- Total form of distribution is displayed
- Adaptable to different kinds of generalization
- Precision is easily changed
- Relative or absolute data
Cons of Isarithmic maps
- Values between control points are a guess
- Level of precision determines how readable a map is
- Interval units may be hard for reader to conceptualize
- Can involve a stats understanding of data
When to use Cartogram
- Want to leave an impression
- Want an alternative to a choropleth map
- Data has strong and unexpected size disparities between locations
Pros of Cartogram maps
- Unique
- Multiple types
- Basemap performs the funcion of geography AND attribute
- An increase in popularity with technology advancements
Cons of Cartogram maps
- Reader needs to be familiar with geographic area to understand
- Multiple types
- Reader does not estimate size of areas well
- Geographic shapes become hard to read
- Not all software creates these wll
When to use Flow map
- Showing movement of something
- Data has line geometry
- Want to show qualitative OR quantitative data
Pros of Flow maps
- Unique
- Differences are easily seen and understood
- Good for numeric and categorical data
Cons of Flow maps
- Limited use
- map designer has lots of choices to make
- Can become easily cluttered
Choro-
-pleth
choro - place
pleth - fill
Rules for Choropleth map
- 1 stat per enumeration unit
- 4-7 classes
- cannot be raw data, must be derived
Types of scaling for Proportional symbols
- absolute
- apparent (Flannerys compensation)
- range grading
Coalescence
overlap dense areas to show how dense in dot density maps
Iso-
-rithmic
Iso - equal
-rithmic - numbers
2 types of interpolation for Isarithmic maps
Isometric - made from point data
Isoplethic - generated from conceptual point data with enumeration units
Isometric map examples
- Total values - elevation, precipitation, temperature
- Elevation
Isoplethic map examples
- Directly involved areas - ratios, proportions; uses political boundaries
- Indirectly involved areas - ratios, props, averages
Isarithmic - Inverse Distance Weighted
Estimates cell values by averaging value of sample data points by each processing cell
Isarithmic - Kirging
Consiers point proximity and spatial autocorrelation
Isarithmic - Natural neighbors
Uses “area-stealing” interpolation to generate best proportional area
