Geography 120 Maps and Mapping

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Geog 120 Lecture Outline: Week 6:

III. Map Abstraction and Infrastructure

Introduction

- map (or cartographic) abstraction: "the process of transforming the actual human and physical environment into a map

- infrastructure: "Something on which another thing is reared or built or by which it is supported or fixed in place"

- map infrastructure: some basic elements upon which all maps are constructed


I. The Map Abstraction Process

- model: a generalized and simplified representation of some object or phenomena


- example: Centre History Map


1. selection: given the infinite detail in the physical and human environment, what is selected to be mapped?


2. classification: given what we have selected to map, how do we group and categorize these objects or phenomena?


3. generalization: the systematic process of removing and/or enhancing detail from the objects and phenomena to be mapped


4. symbolization

- symbol: A thing representing something else because of relationship, association, convention, or resemblance.

- map symbolization: the systematic process of creating graphic marks which represent the objects and phenomena to be mapped


- look at each of these in more detail


1. Selection:

- given the infinite detail in the physical and human environment, what is selected to be mapped?


1a. Selection of "Where" and "When" and "What" to map

Where?: spatial: the area shown

- examples

- World Political Boundaries


When?: temporal: what time is the map?

- a function of the time the map was created, and the time of the information

- examples

- Land Ownership


What: selecting what to map

- what is selected, and what is eliminated, are a function of

- the purpose of the map

- examples

- Buffalo's Ancestry


- the decisions of the map maker: individual or institutional decisions

- examples


- Census Data


- the available data

- examples

- Mortality Atlas


- in essence, the map maker sets thresholds: cut-off points

- an arbitrary but logical decision about what to map

- examples


1b. Selecting a Scale

- map scale: "the extent of size reduction from the environment to the map; the ratio of map distance to ground distance"

- USGS Common Scale Maps


- the selection of map scale by the map maker is driven by map purpose

- examples


Understanding Map Scale

- Examples

Xerox Map Viewer

MapObjects example




- map use requires not only understanding the technical details of map scale, but understanding the general issue of scale

- some technical details...

- most maps have some kind of way of communicating their scale

- two general (and related) types of map scales


Linear Scales

- three types of linear map scale indicators: ratio, verbal, and graphic


- Ratio Scales

- ratio scales represent the ratio between the map and reality

- expressed as a "representative fraction" or RF

ex) 1:60,000 (or 1/60,000)

- means that 1 unit on the map = 60,000 of the same units on the ground

- ratio scales are the origin of the "large" scale vs "small" scale distinction

ex) 1:2400 is "larger" scale than 1:100,000

- large scale maps are maps with a scale of 1:24,000 or larger

- examples

- USGS Common Scale Maps


- small scale maps are maps with a scale of 1:500,000 or smaller

- examples


- Verbal Scales (or Word Statements)

ex) "one inch equals one mile"

- equivalent to 1:63,360

- problem with verbal scales

- examples


- Graphic Scales

- they graphically show a distance and relate (usually with text) how much that distance is equivalent to on the ground

- two advantages

- variable graphic scales

- Mercator Projection


Areal Scale

- why used

- examples


1c. Selecting a Perspective

- what is the selected vantage point (perspective) of the map?

- vantage point: the position that the map maker takes with respect to the earth's surface

- horizontal viewing angle (viewing azimuth): the orientation of the map

- examples

- vertical viewing angle: view from the side or above looking down

- examples


- perspective: how we see (rather than from where)

1. stereographic perspective: how we actually see

- description

- examples

2. central perspective: what a person blind in one eye sees; like a photo

- description

- examples

3. parallel perspective: "gods eye view"

- horizontal parallel vantage: from the side

- examples


- vertical parallel vantage: from above: most maps assume this

- examples

- faked stereographic perspective on parallel perspective map



- oblique parallel vantage: somewhere between from above and from the side

- examples

- hybrid: plan-psuedo perspective


- in addition to vantage point and perspective

- a vitally important related issue is map projection

- in essence: flattening out the spherical earth

- projecting the spherical earth onto a flat surface ALWAYS results in some distortion

- Mercator Area Distortion

- more on this next week...


2. Classification:

- given what we have selected to map, how do we group and categorize these objects or phenomena?

- we classify qualitative data so we can map it

- example

- we classify quantitative data

- example

- keep in mind: "classification reflects the point of view taken by those gathering data and making maps more than it does inherent phenomenal traits. There are no classes in reality; classes are the product of human cognition."

- aspects of a good classification scheme

1. every element falls into one class: classes are mutually exclusive

2. every element falls into a distinct class: few or no elements in an "other" class; the classification scheme is exhaustive

3. the classification scheme serves a useful function


2a. Number of Classes

- how much do we aggregate our data together?

- examples


- the level of aggregation (and number of classes) also effects map symbolization

- examples


- quantitative data classification

- look at the example of the "choropleth map" (more on these maps later)

- data associated with particular areas

- usually classified: number of classes and set class limits

- examples: ESRI

- different number of classes = different patterns


2b. Class Limits

- decisions about how to split up geographic data

- sometimes the class limits are easy to determine

- qualitative (nominal) geographic data

- example


- with quantitative (ordinal, interval, ratio) data it is a bit more complicated

- examples: ESRI

- equal (or constant) interval class limit schemes

ex) data range from 0 to 100

- five equal interval classes: 0 to 20, 21 - 40, 41 - 60, etc.

- advantage:

- disadvantage:


- variable interval class limit schemes

- example

- quantiles: put an equal number of counties in each category

- different class limit schemes = different patterns


3. Generalization

- the systematic process of removing and/or enhancing detail from the objects and phenomena to be mapped

- Monmonier: "A map that did not generalize would be useless"


Generalization procedures which apply to Points, Lines, and Areas

3a. Selection

- we select a few features and don't select most

- purposeful elimination: examples

- accidental or method-produced elimination

3b. Simplification

- the systematic process of removing detail and angularity from the objects and phenomena to be mapped

- examples

Xerox Map Viewer

ESRI


3c. Smoothing

- related to simplification, but result may entail moving some points and adding others

- distinguished from simplification

- examples

- consequences: examples

- simplification and smoothing together are a form of shape abstraction


3d. Displacement

- moving features on the map apart so that they do not interfere

- examples


3e. Enhancement and Exaggeration

- the systematic enhancement of objects and phenomena to be mapped

- examples


3f. Point, Line, and Area Conversion (change in dimensionality)

- generalizing from one feature form into another

- usually the consequence of changing scale

- examples


- aggregation

- eliminate detail by grouping features together: examples


3g. Measurement Level Reduction

- data may exist at interval or ratio level, but map as ordinal

- examples


3h. Compacted Variables

- maps that show data concocted from several different variables

- examples


5. Map Symbolization

- probably the most fundamental step in the map abstraction process

- symbol: A thing representing something else because of relationship, association, convention, or resemblance.

- map symbolization: the systematic process of creating graphic marks which represent the objects and phenomena to be mapped


5a. The Visual Variables

- a framework that logically relates data to graphic marks on the map

Spatial Dimensions of the Geographic Data

- recall: geographic data has a spatial dimension

- points, lines, areas

- recall that this is somewhat arbitrary: map maker's decision

- map symbols can be points, lines, and areas


Level of Measurement of the Geographic Data

- recall: geographic data has a level of measurement (or level of quantification)

- nominal: distinctions of kind or quality with no implied order

- ordinal: basic distinctions of order but with no measurable difference between the ordered positions

- interval/ratio: distinctions of order with measurable difference between the ordered positions


The Visual Variables and Map Symbolization

- matching the data to graphic marks in some logical manner: symbolization HANDOUT) MacEachren Visual Variables

- describe and illustrate a few of the visual variables


1. Size

- changes in size imply an ordinal or numerical difference

- examples


2. Color Value

- value is the variation in lightness or darkness of a color and implies ordinal difference; usually light means less and dark means more

- examples


3. Color Hue

- usually what people associate with the word "color," hue implies nominal, qualitative differences

- examples


- Most mistakes are made when color hue is used to imply ordinal differences


4. Orientation

- highly noticeable variable for depicting nominal and ordinal differences

- examples


5. Shape

- changes in shape imply a nominal (qualitative) difference

- examples


6. Texture

- texture can imply both nominal and ordinal differences

- examples


- as a map user: use the Visual Variables to decode maps

- as a map user: use the Visual Variables to critique maps

- examples


5b. Map Symbols for Data at Points, along Lines, and in Areas

- the data we can map can be

1) point data: located at a specific location

2) line data: located along a string of specific locations

3) area data: data which is collected into some kind of area


- for data at points and lines we can distinguish between

- pictorial symbols: look like what they represent

- examples


- abstract symbols: don't look like what they represent

- examples


- data in areas is more complicated...

- recall the idea of a census

- U.S. Census data is an important example of this kind of data

- how do cartographers determine how to map such data?


- what kind of phenomena is being mapped?

- this is NOT the same as your data


- two dimensions in "Phenomena Space"

Discrete versus continuous

- discrete: occurs at isolated locations; areas of no occurrence between occurrences

- examples


- continuous: occurs at all places in varying amounts

- examples


Abrupt versus smooth variation in space

- abrupt variation: distinctive and substantial breaks possible

- examples


- smooth variation: continuous variation over space with no breaks

- examples


- given an understanding of the nature of the phenomena, the next step is to match this to an appropriate map symbolization method...

- Symbolization space graphic: has the same dimensions

- representing discrete phenomena with smooth variation

- use the technique of dot mapping: examples


- representing discrete phenomena with abrupt variation

- use the technique of graduated symbol mapping: examples

- Monmonier: use this to represent whole (underived) numbers


- representing continuous phenomena with smooth variation

- use the techniques of isarithmic mapping

- examples


- representing continuous phenomena with abrupt variation

- use the technique of choropleth mapping: examples

- Monmonier: use this to represent derived numbers (per square mile)


Summary

- the Map Abstraction Process: "the process of transforming the actual human and physical environment into a map

- four primary (and interrelated) activities

1. selection

2. classification

3. generalization

4. symbolization


- next: map infrastructure




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