Textbook: Slocum, T. A. 1999. Thematic Cartography and
Visualization. Prentice Hall: New Jesey. See Page
1-17
List the main types of mapping techniques with
respect to "symbols"?
There are mainly four types of maps with regards to symbolization (Chapter 2, page 18-39). These are choropleth, proportional symbol, isopleth, and dot maps (Draw Figure 2.8, page 28).
Choropleth map: A choropleth map is a map in which data collection units are shaded to represent different magnitude of variables (e.g. population density).
Proportional symbol map: Proportional symbol map is constructed by scaling symbols in proportion to the magnitude of data occurring at point locations (true location).
Isopleth map (contour map): Isopleth map is created by interpolating a set of isolines between sample points of known values.
Dot map: Dot map is created by setting one dot equal to a certain amount of phenomena, and dots are placed where that phenomena is most likely to occur (dot = 500 people).
List the factors that governing the use of
special type of symbol?
The use of specific type of symbol to a certain map is depending on many factors such as:
1. The spatial arrangement of geographic phenomena (whether a phenomena can be conceived as points (wells), lines (river), or areas (district). Another way of thinking about spatial arrangements is whether the feature is continuous or discrete. A continuous feature has no definite boundary (e.g. elevation, temperature) and discrete feature has definite boundary (e.g. road, house, well).
2. The various levels at which we can measure geographic phenomena. This refers to the various ways in which a phenomena can be measured, for example, nominal, ordinal, interval, and ratio scale.
What is
meant by visual variables, illustrate by figure?
Visual variables is commonly used to describe the various perceived differences in map symbols that are used to represent spatial phenomena. The variables include spacing, size, perspective height, orientation, shape, arrangement, hue and lightness (Draw Figure 2.2, page 23).
List the
main elements that must be included in a map?
The important elements that must be included in a map include:
Title: Must be clear, concise, and preferably at the top of the map with bold letters.
Contents: the body of the map must be printed in clear background.
Legend: Symbols must be informative and clear
Scale: Scale of the map is essential, especially in reference maps (measurement of distance).
North arrow: Direction of the map is important for many studies (e.g. tourist, wind direction, etc.)
In addition to the above, other information can be added such
as source of map (name of organization, name of person, date, city), frame, and
logo. For interactive maps (multi-media maps) additional information may
include table, graph, photo (picture), and video clip (Plate 20, 31, Figure
12.5, page 200)
The major reason for making a map is to study spatial pattern, therefore, labeling should be minimized or provided on a separate table outside the map. Base information (information that is not the major theme) such as roads, rivers has to be added based on its relevance to the theme being mapped and should not detract from communicating the major theme (Figure 2.12 and 2.13 page 34 and 35).
What is
meant by typography in map design?
Typography is the process that deals with font, style, and size of letters use for map elements (title, legend, labels, source). Generally speaking, the following guidelines can be use (Figure 2.19, page 37):
1. Use single font for entire display
2. Select legible fonts (clear- e.g. serif)
3. Use combination of upper and lower lettering (Good lettering, BAD LETTERING)
4. Use size to distinguish major elements (use bold letters for important elements e.g. hierarchical feature; City-Town-Village).
Software such as ArcView can be used for labeling, however, some interactive (manual) editing may be needed to locate a label properly. New developed software (expert systems) can be used to locate labels automatically (e.g. following a road).
Chapter 3:
page 40-59 : Statistics and graphical foundation
Statistics such as a sum, mean and graphs such as bar or line may give a quick exploration about the nature of data. Statistical methods for analyzing non-spatial data include:
1. Analyzing distribution of individual variables
2. Analyzing the relationship between two or more variables
Tables can be sorted to give an indication about minimum, maximum and outliers values (outliers are unusual values).
Grouped-frequency table can be constructed by dividing the data range (maximum-minimum) into equal intervals and then count the number of observations that fall in each interval (see Table 3.2, page 43).
Graphs are used mainly to simplify exploration of data. There are different types of graphs such as point and dispersion graph (Figure 3.1, page 44). The most common type of graph is histogram (Figure 3.2, page 45).
Measurement
of central tendency
Measurement of central tendency is used to indicate a value around which the data are most likely concentrated. (mod, median, mean) (page 46 - 47). While the measures of dispersion are the range and standard deviation.
Grouped frequency tables (Table 3.3 , page 47) and scatter plot (Figure 3.5, page 47) are used to analyze the relationship between two or more variables. The most widely uses approach for summarizing the relationship between numeric values is the correlation coefficient (r). The value of r range between -1 and +1. A positive r indicates positive relationship (e.g. 0.82) and vice versa (e.g. -0.7). Bivariate regression establish a relationship between two variables (best-fit-line) e.g. the equation Y = a + bx : where Y is dependent variable, a intercept, b slope and x is independent variable.
Numerical summaries in which location is an integral part include centroid (center of gravity or mean center) and spatial autocorrelation. Spatial autocorrelation is the tendency for like things to occur near one another in geographic space (gravity model, Tobler law), e.g. expensive homes likely will located near other expensive homes. The measure used to study spatial autocorrelation are Moran coefficient (MC) and the Geary ratio (see page 55).
Exercise:
Given the coordinates (x, y): (5,10), (10,20), (15,30), (20,35), (25,50)
Calculate the mean center (page 55), standard deviation (page 46) for each (x and y) and plot a rough scatter plot showing the relationship between the variables (x and y) (page 47). Is there any correlation between the two variables (positive , negative, none)?
