4.1.1 Spatial Arrangement of Geographic Phenomena
spatial dimensions, point, linear, 2-D, 2½-D and 3-D
point- zero dimension, can be in 2-D or 3-D space with coordinates
examples: oil wells, weather stations
linear- one dimension, having length, no width, can be in 2-D or 3-D space with coordinates
examples: boundaries, path of a plane or car
areal- 2-D, having length and width,
examples: lakes, political units (states, countries)
2½-D- volumetric, but just a surface, can not have at true cross section,
examples: height above sea level, or precipitation over a region
3-D- are multivalued, X,Y,Z coordinates (unusual to find true 3-D map)
map scale
small scale: points can indicate small areas eg: buildings
large scale: what were points on a small scale may be 2-D like building outlines
4.1.2 Models of Geographic Phenomena
discrete phenomena- have distinct locations, whole numbers integers
example: people in a city
continuous phenomena- occur throughout the region
example: rainfall, different amounts happen through an area
smooth phenomena- changes suddenly
abrupt phenomena- changes are smooth
4.1.3 Phenomena versus Data
phenomena-
data-
prism map- (map B in Figure 4.2) shows abrupt changes
fishnet map- (map A in Figure 4.2) sooth and continuous
*To create the most representative map of the phenomenon, but to stress that the mapmaker must distinguish between
data that have been collected and the phenomenon that is being mapped
4.2 Levels of Measurement
Level of measurement- refers to the different ways that we measure attributes; we commonly consider nominal,
ordinal, interval, and ratio levels.
Qualitative- descriptive
Nominal- involves grouping or categories but no order
eg: religious groups
Quantitative: involves numbers
Ordinal- involves categorizing and ranking (ordering of) the data.
eg: low, moderate, high;
Interval: involves ordering the data plus indication of number (arbitrary zero)
eg: (temp) SAT scores (a person who got 800 did four times better than the person with 200)
Ratio: involves a real zero (can use arithmetic) associated with numerical data
eg: Kelvin scale, number of crops
Bipolar data- either natural or meaningful dividing points
Eg: a value of zero population change
Balanced data- two phenomenon that coexist in a complementary fashion
Eg: In Canada a high percentage of English speaking people implies a low percentage of French speaking people (they balance one another)
Uniploar data- no natural break or dividing points
Eg: per capital income
4.3 Visual Variables
Visual variables- describe various perceived differences on map symbols, and how they show the phenomena
Spacing- involves changes in the distance between symbols
Size- 2 ways of using it
Perspective Height- 3-D eg; using “lollipop” like symbols to show amount that symbols is representing
Orientation- direction of symbols are varied (eg: line segments to indicate wind direction
Shape- forms of symbols are varied (eg squares stars circles)
Arrangement- marks symbols by arranging in different fashions – breaking lines into dots or dashes for different boundaries
Hue- color (eg; red blue)
Lightness: (value) how dark or how light
Saturation: (chroma) the intensity of the color
4.3.7 Some Considerations in working with Visual Variables
Pictographic symbols- look like the phenomenon (children’s atlases)
Geometric symbols- change in size indicates increase in phenomena
Location- position of symbol
4.4 Comparison of Choropleth Proportional symbol, isopleths, and dot mapping
Choropleth map- enumerated data are shaded with an intensity proportional to the data value units
Data standardization- which raw totals are adjusted for different sizes of enumeration units
Proportional Symbols Maps- scales symbols in proportion to the magnitude of the data
Isarithmic Map- (contour map) created by interpolating a set of isolines between sample points of known values
Isopleths map- specialized Isarithmic map with sample points are associated wit enumeration units
Dot Mapping- one dot is equal an amount of phenomena and dots are placed where the phenomena occur
4.4.5 Discussion
Dasymetric map- like a dot map, but can show detailed information and uses standardized data
Pie chart- by altering the proportional symbol to a pie chart you can show other relationships in the geographic phenomena