Chapter 2 - Data Models Flashcards

1
Q

Map data are abstractions of these

A

Physical surface entities

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2
Q

What are two ways to represent entities on a map?

A

Spatial features or cartographic objects

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3
Q

What three aspects of an entity do maps contain information about?

A

Location, extent and attributes

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4
Q

Is it possible for all entities or their properties be represented on a map?

A

No

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5
Q

Are there multiple ways to abstract reality?

A

Yes

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6
Q

What are two decisions GIS users must make to abstract reality onto a map?

A

Which entities to represent and how to represent them

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7
Q

These are used to represent spatial data

A

Spatial data models

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8
Q

What are three things that spatial data models store data for?

A

Objects, relations of objects, and attributes of objects

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9
Q

Spatial data models use these to position objects

A

Spatial coordinates

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10
Q

Spatial data models assign these to objects

A

Attributes

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11
Q

In spatial data models, these combine spatial data and attribute information for classes of objects

A

Layers

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12
Q

These data describe the location and extent of objects

A

Coordinate data

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13
Q

How many coordinates are used to coordinate a position relative to an origin?

A

At least 2

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14
Q

What are three things that can be represented by coordinate data?

A

Points, lines and shapes

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15
Q

Which two coordinate data systems does GIS use?

A

Cartesian and spherical systems

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16
Q

Cartesian coordinates use these to describe position

A

2-3 orthogonal axes (x, y, z)

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17
Q

These coordinates use two angles to locate a position on a sphere

A

Spherical coordinates

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18
Q

These are non-spatial properties of an entity

A

Attribute data

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19
Q

Where are attribute data stored?

A

In attribute tables

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20
Q

In an attribute table, what does each row correspond to?

A

An object

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21
Q

What is another name for rows in an attribute table?

A

Record

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22
Q

In an attribute table, what does each column correspond to?

A

Individual attribute

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23
Q

What are the four forms of attribute data?

A

Nominal, ordinal, interval, ratio

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24
Q

What are the two common GIS models for conceptualizing spatial data?

A

Raster model and vector model

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25
Q

These are used for point entities

A

Points

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26
Q

Do points have location?

A

Yes

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27
Q

Do points have dimension?

A

No

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28
Q

These are used for linear entities

A

Lines

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29
Q

Do lines have location and length?

A

Yes

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30
Q

Do lines have width?

A

No

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31
Q

How many pairs of coordinates are needed for a line?

A

At least 2

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32
Q

These are the start, end points, and crossing points of lines

A

Nodes

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33
Q

These are points where lines change direction

A

Vertices

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34
Q

These are used for area entities

A

Polygons

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35
Q

How are polygons defined?

A

By line segments that enclose an area

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36
Q

Can polygons enclose other polygons?

A

Yes

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37
Q

Can polygons share edges with other polygons?

A

Yes

38
Q

This is the study of geometric objects that are not changed by warping/stretching

A

Topology

39
Q

What are four examples of topology properties?

A
  1. Line connectivity; 2. Polygon adjacency; 3. Line directionality; 4. Feature containment
40
Q

This was an early model for organizing line data, in which lines were recorded separately with explicit nodes and vertices

A

Spaghetti vector model

41
Q

In the spaghetti vector model, do lines have intersections/connections?

A

No

42
Q

In the spaghetti vector model, do data lack relations among map objects?

A

Yes

43
Q

Which is the spaghetti vector model useful for, data entry or analysis?

A

Data entry

44
Q

This model creates points, lines, and polygons through data structure

A

Topological vector model

45
Q

How are points represented in the topological vector model?

A

Unique ID and coordinate pair

46
Q

How are nodes represented in the topological vector model?

A

Unique ID and coordinate pair

47
Q

How are arcs represented in the topological vector model?

A

Unique ID and end nodes

48
Q

How are polygons represented in the topological vector model?

A

Unique ID and series o

49
Q

Topology can define features between these

A

Layers

50
Q

This provides means for cleaning and verifying data

A

Topology

51
Q

What are the two different types of topology?

A

Non-planar and planar

52
Q

Between non-planar and planar topologies, which is more common?

A

Planar

53
Q

These relationships can exist between layers in vector models

A

Topological relationships

54
Q

In the vector data model, data is stored in these

A

Attribute tables

55
Q

This type of linkage is the norm in the vector data model

A

One-to-one linkage

56
Q

This type of linkage is less common but also used in the vector data model

A

Many-to-one linkage

57
Q

In this type of data linkage, each object has a single table record

A

One-to-one linkage

58
Q

In this type of data linkage, multiple objects link to a single record

A

Many-to-one linkage

59
Q

In the vector data model, tables link features to attributes using these

A

Unique IDs

60
Q

In the raster data model, spatial data describes the surface as this

A

Cell grid

61
Q

In the raster data model, surface features are embodied by these

A

Values attached to cells

62
Q

The raster data model is natural for this type of phenomenon

A

Continuous phenomenon

63
Q

The raster data model is less commonly used for this type of feature

A

Discrete features

64
Q

In the raster data model, cell coordinates define location relative to this corner of the cell

A

Lower left corner

65
Q

What part of the cell do coordinates apply to in the raster data model?

A

Cell center point

66
Q

Raster data is a tradeoff between spatial data and this

A

Data volume

67
Q

In the raster data model, cell dimension affects this

A

Spatial precision

68
Q

In the raster data model, are smaller or larger cells more precise?

A

Smaller cells

69
Q

In the raster data model, positional accuracy is roughly no better than this

A

One-half cell size

70
Q

In the raster data model, decreasing cell size rapidly increases this

A

Cell number

71
Q

In the raster data model, what are the two ways to apply cell values?

A

To entire cell or to cell center

72
Q

Raster layers can have these

A

Attributes

73
Q

In the raster data model, cells are linked to these

A

Records in a table

74
Q

What are the two ways to link cells to table records in the raster data model?

A

One-to-one or many-to-one linkage

75
Q

This type of linkage creates very large tables in the raster data model

A

One-to-one linkage

76
Q

What are three of five factors in choosing between vector and raster models?

A
  1. Predominant data type (discrete vs continuous); 2. Types of anticipated analyses; 3. Available data storage; 4. Main sources of input data; 5. User expertise
77
Q

What are three of five advantages of the raster data model?

A
  1. Particularly apt for continuous data; 2. Data structures are simple; 3. Facilitates easy overlay analysis; 4. More practical for storing/displaying/manipulating images; 5. Much existing digital data is in raster
78
Q

What are four of six advantages of the vector data model?

A
  1. Particularly apt for discrete data; 2. Natural for networks; 3. Data storage more compact; 4. Favored format for maps; 5. Curved lines are smoother; 6. Facilitates storage of topological information
79
Q

What are two common conversion rules in converting between raster and vector models?

A

Any cell and near cell center

80
Q

In raster line to vector line conversion, to what part of the cell is cell value assigned?

A

Coordinates at cell center

81
Q

This data model is used for representing terrain

A

Triangulated irregular network

82
Q

This data model converts sets of x, y, z coordinates to a surface of connected triangles

A

Triangulated irregular network

83
Q

Is the triangulated irregular network data model simpler than raster elevation data?

A

No

84
Q

Is the triangulated irregular network model more efficient when the terrain is highly variable?

A

Yes

85
Q

In the triangulated irregular network model, triangles are defined by these three parts

A

Points, edges and facets

86
Q

In the triangulated irregular network data model, these are used to identify triangle corners

A

Convergent circles

87
Q

What three data models can be used to model elevational data?

A

Vector, raster and triangulated irregular network

88
Q

The combination of raster data model combined with triangulated irregular network model is called this

A

Digital elevation models

89
Q

This data model represents elevation as contour lines

A

Vector data model

90
Q

These two data models are best for analysis of elevational data

A

Raster data model and triangulated irregular network data model

91
Q

These are often used in finished maps to represent elevation

A

Contour lines