Chapter 4 Readings and Notes

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
            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