Lecture 3 (From Geographic Features to GIS Data: Representing Geography) Flashcards

1
Q

The Value of Maps

A

1) Represent the world

2) Communicate the geographic information to each other

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

Sensing the World

A
  • Personal experience limited in time and space (one human lifetime/ a small fraction of the earth’s surface)
  • All additional knowledge comes from books, media, movies, maps, images, and other information sources (From indirect or “remote” sensing)
  • DIGITAL REPRESENTATION HAS MANY USES BECAUSE OF ITS SIMPLICITY AND LOW COST.
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Representations

A
  • Needed to CONVEY information
  • Fit information into a STANDARD form or model
    Almost always SIMPLIFY THE TRUTH that is being represented
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

Simplification and Standardization

A

They help us assemble far more knowledge about the Earth than it is possible on our own.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

The importance of representation in GIS

A
  • Spatial interpolation in places where no observations were made ( SOIL CHARACTERISTICS and RAINFALL)
  • TOBLER’s FIRST LAW OF GEOGRAPHY - “Everything is related to everything else, but near things are more related than those far away.”

EX. UN/FAO Soil Map of the U.S. and Average Annual Precipitation, 1971-2000 in Oregon

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

Key Issues of GIS Representation

A

Accuracy of Representation
- Details can be irrelevant, or too expensive and voluminous to record.
- What to represent? / What to leave out?
- How to represent the infinitely complex world?
NONE IS PERFECT AND IDEAL FOR ALL APPLICATIONS
- What is missing in a representation?

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

“How to lie with maps”

A

Mark Monmonier, 1991 and 1996 “If a picture is worth a thousand words, a map can be worth a million –but beware. All maps distort reality …In short, the author warns, all maps must tell white
lies.” (Distinguished Professor of Geography at the Maxwell School of Syracuse University)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

Approximations of the Earth’s Shape

A

a) Sphere O
b) Ellipsoid
c) Geoid
- Note that the shape of the ellipsoid and geoid are highly exaggerated for illustrative purposes.
GEODESY - the science of earth measurement.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

Map Projection Process

A

Terrestrial Surface -> Geoid -> Ellipsoid -> Nominal or generating globe -> 2D Map

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

The Fundamental Problem

A
  • The geographic world is infinitely complex, but computer systems are finite.
  • The more closely we look at the world the more detail it reveals.
  • REPRESENTATION is all about the CHOICES to capture information about the world.
    We must somehow limit the amount of detail in the digital representations.
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

The Fundamental Problem

A
  • Common strategies for limiting detail (Throw away or ignore information that applies only to a small area - Spatial resolution - the degree of detail/ Ex. 10km, anything less that 10km across is virtually invisible/ Large or small scales).
  • Observe many properties remain constant over large areas.
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

Scales

A

Small, Medium, Large - In this way, we classify the world into fewer groups and also make our database to be much simpler.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

Geographic Attributes

A
  • Geographic information links a place, time, and ATTRIBUTE (DESCRIPTIVE PROPERTY). “The temperature at noon local time on 1/23/2011, at 34N, 120 W was 43 Fahrenheit”
  • Geographic attributes describe all kinds of properties (PHYSICAL, ENVIRONMENTAL, SOCIAL, ECONOMIC)
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

Types of Attributes

A

Nominal -> land cover class, name (EX. State name)
Ordinal -> a ranking
Interval -> temperature
Ratio -> Income, weight (EX. Income Map)
Cyclic -> Wind/ slope direction (Ex. Wind direction and Wind Rose Map)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

Discrete Objects and Continuous Fields

A
  • The most fundamental distinction in geographic representation
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

Discrete Objects

A
  • Countable
  • Dimensionality (Points, Lines, and Areas)
  • Objects with well-defined boundaries
    Persistent through time, perhaps mobile
    Examples: Biological Organisms - animals, trees, peaks/ Human- made objects - road, buildings, dam
17
Q

Discrete Objects

A
  • Points (Zero-dimension)
  • Lines (One-dimension)
  • Polygon (Area/ Two-dimension)
  • Three-dimensional object (Including the altitude)
18
Q

Continuous Fields

A
  • The world as a continuous surface
  • Represent the real world as a finite number of variables, each one defined at every possible position.
  • Properties vary continuously over space (A single value at every point on the Earth’s surface/ Value is a function of location/ Property can be of any attribute type)

EX. Soil Moisture, Geodemographic Structure of Nottingham, UK, Weather Satellite Image (Hurricane)

Difficult Cases - Lakes and other natural phenomena (often conceived as objects, but difficult to define or count precisely), Weather forecasting (forecasts originate in models of fields, but are presented in terms of discrete objects - highs, lows, fronts) Ex. Hurricane Isaac

19
Q

Representation

A
Spatial Representation (the map side)
Attributive representation (the table side)
20
Q

Representation with Layers

A

Vector - Transportation, Land Use, Census Tracts, Structures

Raster - Postal Codes, Raster Imagery

21
Q

Spatial Representation - The Map Side

A

Raster Data

Vector Data

22
Q

Raster Data

A
  • More commonly used to represent CONTINUOUS FIELDS than discrete objects (It does not mean to exclude discreet objects)
  • Divide the world into SQUARE CELLS
  • Assigning attribute value to each cell
  • Represent discrete objects as collections of one or more cells
23
Q

Vector Data

A
  • Represent DISCRETE OBJECTS than continuous fields
  • Used to represent points, lines, and areas/ polygons
  • All features are represented in coordinates
24
Q

Raster v Vector

A
  • Volume of data (Raster - depends on cell size, Vector - depends on density of vertices)
  • Source of data (Raster - remote sensing, elevation data, Vector - Administrative data (social, environment)).
  • Software - Some GIS better suited to raster, some to vector.
    Resolution (Raster - Fixed, Vector - Variable).
25
Q

Attribute Representation - The Table Side

A

Discrete Objects v. ATTRIBUTE FIELDS
- Objects and FIELDS
Attribute Fields = Variables

26
Q

Attribute Database

A

Data Base Components

  • Records (row)
  • Attribute fields/ values (column)
  • Keys - query fields (key column)

Three Classic Models

  • Hierarchical
  • Networked
  • Relational/ Tabular
27
Q

Some concepts in representation

A
  • Generalization
  • Specification
  • Weeding
28
Q

Generalization

A

Reducing the level of detail in geographic data

  • By simplifying, weeding, abstracting
  • To reduce the volume of data WITHOUT ADVERSELY AFFECTING ITS USE
  • To “see the wood for the trees” (to understand the bigger picture without being caught up in small details).
29
Q

Specification

A

How real world on the ground is selected for inclusion on the map

  • Refinement/ replacement of a complex pattern of objects by a selection that PRESERVES THE PATTERN’S GENERAL FORM
  • Enhancement, through the alteration of the physical sizes and shapes of symbols
30
Q

Weeding

A

The process of removing points in a polygon or polyline while preserving important aspects of shape
- E.g. the Douglas-Poiker line simplification algorithm

31
Q

Census Data

A
  • Determine the population and household counts for estimation of federal fund and transportation management
  • TIGER (Topologically Integrated Geographic Encoding and Referencing) - U.S. Bureau of the Census and U.S. Geological Survey - Street lines (road network) - Major products - Demographic data (income, population, housing, etc.)
32
Q

Geographic unit in TIGER

A

State, County, CENSUS TRACT, Block Group, Block

33
Q

Coding in Census Data

A

FIPS (Federal Information Processing System) - 15 digits

  • State - two digits ( 41 Oregon)
  • County - three digits (41607 Washington County)
  • Census Tract - six digits (41067000400)
  • Block Group and Block - four digits (410670004001023)