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Fundamentals of GIS > Chapter 2 - Data Models > Flashcards

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
These are used for point entities
Points
26
Do points have location?
Yes
27
Do points have dimension?
No
28
These are used for linear entities
Lines
29
Do lines have location and length?
Yes
30
Do lines have width?
No
31
How many pairs of coordinates are needed for a line?
At least 2
32
These are the start, end points, and crossing points of lines
Nodes
33
These are points where lines change direction
Vertices
34
These are used for area entities
Polygons
35
How are polygons defined?
By line segments that enclose an area
36
Can polygons enclose other polygons?
Yes
37
Can polygons share edges with other polygons?
Yes
38
This is the study of geometric objects that are not changed by warping/stretching
Topology
39
What are four examples of topology properties?
1. Line connectivity; 2. Polygon adjacency; 3. Line directionality; 4. Feature containment
40
This was an early model for organizing line data, in which lines were recorded separately with explicit nodes and vertices
Spaghetti vector model
41
In the spaghetti vector model, do lines have intersections/connections?
No
42
In the spaghetti vector model, do data lack relations among map objects?
Yes
43
Which is the spaghetti vector model useful for, data entry or analysis?
Data entry
44
This model creates points, lines, and polygons through data structure
Topological vector model
45
How are points represented in the topological vector model?
Unique ID and coordinate pair
46
How are nodes represented in the topological vector model?
Unique ID and coordinate pair
47
How are arcs represented in the topological vector model?
Unique ID and end nodes
48
How are polygons represented in the topological vector model?
Unique ID and series o
49
Topology can define features between these
Layers
50
This provides means for cleaning and verifying data
Topology
51
What are the two different types of topology?
Non-planar and planar
52
Between non-planar and planar topologies, which is more common?
Planar
53
These relationships can exist between layers in vector models
Topological relationships
54
In the vector data model, data is stored in these
Attribute tables
55
This type of linkage is the norm in the vector data model
One-to-one linkage
56
This type of linkage is less common but also used in the vector data model
Many-to-one linkage
57
In this type of data linkage, each object has a single table record
One-to-one linkage
58
In this type of data linkage, multiple objects link to a single record
Many-to-one linkage
59
In the vector data model, tables link features to attributes using these
Unique IDs
60
In the raster data model, spatial data describes the surface as this
Cell grid
61
In the raster data model, surface features are embodied by these
Values attached to cells
62
The raster data model is natural for this type of phenomenon
Continuous phenomenon
63
The raster data model is less commonly used for this type of feature
Discrete features
64
In the raster data model, cell coordinates define location relative to this corner of the cell
Lower left corner
65
What part of the cell do coordinates apply to in the raster data model?
Cell center point
66
Raster data is a tradeoff between spatial data and this
Data volume
67
In the raster data model, cell dimension affects this
Spatial precision
68
In the raster data model, are smaller or larger cells more precise?
Smaller cells
69
In the raster data model, positional accuracy is roughly no better than this
One-half cell size
70
In the raster data model, decreasing cell size rapidly increases this
Cell number
71
In the raster data model, what are the two ways to apply cell values?
To entire cell or to cell center
72
Raster layers can have these
Attributes
73
In the raster data model, cells are linked to these
Records in a table
74
What are the two ways to link cells to table records in the raster data model?
One-to-one or many-to-one linkage
75
This type of linkage creates very large tables in the raster data model
One-to-one linkage
76
What are three of five factors in choosing between vector and raster models?
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
What are three of five advantages of the raster data model?
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
What are four of six advantages of the vector data model?
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
What are two common conversion rules in converting between raster and vector models?
Any cell and near cell center
80
In raster line to vector line conversion, to what part of the cell is cell value assigned?
Coordinates at cell center
81
This data model is used for representing terrain
Triangulated irregular network
82
This data model converts sets of x, y, z coordinates to a surface of connected triangles
Triangulated irregular network
83
Is the triangulated irregular network data model simpler than raster elevation data?
No
84
Is the triangulated irregular network model more efficient when the terrain is highly variable?
Yes
85
In the triangulated irregular network model, triangles are defined by these three parts
Points, edges and facets
86
In the triangulated irregular network data model, these are used to identify triangle corners
Convergent circles
87
What three data models can be used to model elevational data?
Vector, raster and triangulated irregular network
88
The combination of raster data model combined with triangulated irregular network model is called this
Digital elevation models
89
This data model represents elevation as contour lines
Vector data model
90
These two data models are best for analysis of elevational data
Raster data model and triangulated irregular network data model
91
These are often used in finished maps to represent elevation
Contour lines

Fundamentals of GIS (13 decks)

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