Week 5 Symbolizing Map Data

1
Week 5 Symbolizing Map Data

• The map as an appreciation of earth environments
• Representing earth environments requires data
• Satellite map and aerial photographs show
  realistic scenes, but require substantial
  training to properly interpret the landscape.
• Acquired data, such as census data or any other
  surveyed or collected datasets will require
  systematic methods of representing the data and
  the use of symbols.
• Thus, we need to have an understanding of how
  data are managed and organized on a map and how
  such data are symbolized to represent the real
  world.
• Cartographers often refer to these efforts as
  data portrayal and symbolization.

2
Week 5 Symbolizing Map Data

• Data portrayal and symbolization
• Numeric and non-numeric map data come in all
  kinds of formats, all kinds of densities, all
  kinds of data collection methods, and all kinds
  of time frames.
• How we portray them depends on a combination of
  these varying factors.
• But geometrically speaking, they come in as point
  data (zero dimension), line data (one dimension),
  area data (two dimensions) volume (three
  dimensions) and volume through time (four
  dimensions).
• Therefore, we can portray them as point symbols,
  line symbols, area symbols or shades, 3-D
  formats, and 3-D formats over time (animation).
• Data may be classified as qualitative and
  quantitative.
• Symbols may be realistic or abstract (mimetic or
  arbitrary).

3

• Qualitative and quantitative data maps
• Qualitative data refer to nominal (named)
  geographic information, e.g. a valley, a mountain
  range, a river, a church in a reference map,
  sedimentary rocks on a geologic map, commercial
  retail area on a land use map, clayey soils on a
  soil map
• There is no numeric quantity associated to the
  map data
• Quantitative data refer to the amount of things
  that are being mapped, e.g. the number of people
  on a population map, temperature records on a
  weather map, elevations on a topographic map, the
  amount of traffic on a flow-line map
• Numeric data usually indicate how much of
  something is distributed spatially on the map

4
Quantitative and qualitative data maps.
Qualitative
Quantitative
5
Qualitative
Point data maps
Quantitative
6
Qualitative
Line data maps
Quantitative
7
Qualitative no one area should look darker than
another, because these are just classifications
of lands, and not comparisons of quantities.
Area data maps
Quantitative
Darker shades normally indicate higher quantities.
8
Manually prepared 3-D block diagram
3-D formats
Computer-generated 3-D terrain model
9
Time series maps are particularly useful in
detecting change over time
10
Week 5 Symbolizing Map Data

• Symbols play an important role in helping the map
  reader understand the map
• But other processes, such as data collection,
  mapping methods, and how to classify data also
  play very important roles in helping the map
  reader.
• Well examine the nature of symbols, data
  collection and mapping methods, and the process
  of map generalization.

11
Symbols may be realistic or pictorial or abstract
Realistic point feature
Abstract point feature
Abstract line feature
Realistic line feature
Realistic areal feature
Abstract areal feature
12
Some cartographers use different terms to
illustrate this type of symbolization by
referring to a pictoral continuum from being
Mimetic or mimicking to Arbitrary
13
But when a map is all put together and finally
published, the map reader will only have the
symbols to interpret the map and try to get a
sense of what is the main map message by
visualizing the geographic patterns from the map.
14
Week 5 Symbolizing Map Data

• Generalizing map data
• It is apparent that map data must be generalized
  to some degree before they can be symbolized and
  represented on a map.
• Given all of the variations of map data formats
  that weve discussed as well as the abstraction
  of the symbols, the map reader must exercise some
  common sense in interpreting a map.
• Because much geographic information has been
  generalized and when it is finally represented on
  a map as map symbols, a great deal of alteration
  of the original data has already taken place.
• Consider the following series of maps

15

• How useful is this map? How do we interpret this
  map?
• Looking at the map legend, we can derive several
  conclusions
• That the map was purposely classified into four
  classes, two of which are above the national
  average of 79.6 persons per sq. mile and the
  other two below. (continued on next slide)

16

• That the dark blue represents the most dense
  states
• That the range of the dark blue is from 300 to
  9,316 persons/sq. mile
• That this range is very large, compared to all
  other ranges
• That the information is lost if we wish to
  compare the density say, between NY and Rhode
  Island, or between Massachusetts and Delaware
  even though all 4 states are within the same
  class of 300-9316.
• For all that matters, one of these states may be
  as dense as 9,316 since the data indicated that
  as the highest in the range while another state
  can be as low as 300 or close to the low end of
  300.

7. There is no way to know which state is
high and which state is low. 8. There is also no
way to know how low the lowest state is is it at
300 or can it be at 350?
17
9. That the population density of Wisconsin can
possibly be the same as that of California since
they have the same color on the map. 10. That,
according to the map, Alaska can be as high as
6.9 and Minnesota can be as low as 7.0, putting
these two states practically having little to no
difference in terms of population density. Is
this true? According to the map, it is true but
in reality, maybe not! 11. That there is no
variation in population density within each
state! 12. That if one needs information on
variations in population density in each state,
the mapping method must include data at the
county level, as on the map in the next slide
18
On this map, population density data were
collected at the county level. 1. There is a lot
more variation in population density on this map
and the map now really reflects the concentration
of urban centers.
19

• That the black color represents the most dense
  counties, in the range of 3,000 to 66,940.
• That this range is also very large (22 times
  between high and low)
• That the spatial resolution is much better than
  the previous state level map. Geographic
  patterns can thus emerge.
• That there is still no variation in population
  density information within each county.
• The question then becomes whether we need data
  variation within one county?
• Examine at the next set of maps.

(They are actually enlargements of the same map).
20
Consider the geographic background that relates
to population density in San Bernardino County in
California which extends into the Mojave Desert
and Miami-Dade County in Florida which extends
into the Everglades. Are there many people
living in Mojave Desert or Everglades?
21
Week 5 Symbolizing Map Data

• Generalizing map data
• The way that a cartographer generalizes map data
  and the very method that we use for mapping would
  indeed change the perception of the map patterns.
• Not only should a cartographer be faithfully
  seeking the best ways to map geographic data, but
  the map reader should also be cognizant of what
  goes on in the mapping process in order to get
  the correct insight of the precise geographic
  pattern.
• Thus, we must also study the accuracy of maps.
• Consider the following scenarios.

22
Different data sampling techniques will result in
different number of data points collected.
23
(a) Mapping by townships
(b) Mapping by townships with uninhabited areas
added.
(c) Mapping by subdivisions of townships. When
the mapping area unit is smaller, the mapping of
the true phenomenon is more accurate, as in
this case of Cape Cod where heavy concentration
of homes are along either coasts and the middle
strip of land is devoted to commercial
establishments along a state highway.
24
Week 5 Symbolizing Map Data

• How to lie with maps and distort the truth
• Because of the different ways of mapping
  geographic data and the outcomes of the maps can
  change, there is also ambiguity in the
  interpretation of maps.
• In fact, the author of your textbook has also
  written another book titled How to lie with
  maps.