Chapter 2 - Data Models Flashcards
Map data are abstractions of these
Physical surface entities
What are two ways to represent entities on a map?
Spatial features or cartographic objects
What three aspects of an entity do maps contain information about?
Location, extent and attributes
Is it possible for all entities or their properties be represented on a map?
No
Are there multiple ways to abstract reality?
Yes
What are two decisions GIS users must make to abstract reality onto a map?
Which entities to represent and how to represent them
These are used to represent spatial data
Spatial data models
What are three things that spatial data models store data for?
Objects, relations of objects, and attributes of objects
Spatial data models use these to position objects
Spatial coordinates
Spatial data models assign these to objects
Attributes
In spatial data models, these combine spatial data and attribute information for classes of objects
Layers
These data describe the location and extent of objects
Coordinate data
How many coordinates are used to coordinate a position relative to an origin?
At least 2
What are three things that can be represented by coordinate data?
Points, lines and shapes
Which two coordinate data systems does GIS use?
Cartesian and spherical systems
Cartesian coordinates use these to describe position
2-3 orthogonal axes (x, y, z)
These coordinates use two angles to locate a position on a sphere
Spherical coordinates
These are non-spatial properties of an entity
Attribute data
Where are attribute data stored?
In attribute tables
In an attribute table, what does each row correspond to?
An object
What is another name for rows in an attribute table?
Record
In an attribute table, what does each column correspond to?
Individual attribute
What are the four forms of attribute data?
Nominal, ordinal, interval, ratio
What are the two common GIS models for conceptualizing spatial data?
Raster model and vector model
These are used for point entities
Points
Do points have location?
Yes
Do points have dimension?
No
These are used for linear entities
Lines
Do lines have location and length?
Yes
Do lines have width?
No
How many pairs of coordinates are needed for a line?
At least 2
These are the start, end points, and crossing points of lines
Nodes
These are points where lines change direction
Vertices
These are used for area entities
Polygons
How are polygons defined?
By line segments that enclose an area
Can polygons enclose other polygons?
Yes
Can polygons share edges with other polygons?
Yes
This is the study of geometric objects that are not changed by warping/stretching
Topology
What are four examples of topology properties?
- Line connectivity; 2. Polygon adjacency; 3. Line directionality; 4. Feature containment
This was an early model for organizing line data, in which lines were recorded separately with explicit nodes and vertices
Spaghetti vector model
In the spaghetti vector model, do lines have intersections/connections?
No
In the spaghetti vector model, do data lack relations among map objects?
Yes
Which is the spaghetti vector model useful for, data entry or analysis?
Data entry
This model creates points, lines, and polygons through data structure
Topological vector model
How are points represented in the topological vector model?
Unique ID and coordinate pair
How are nodes represented in the topological vector model?
Unique ID and coordinate pair
How are arcs represented in the topological vector model?
Unique ID and end nodes
How are polygons represented in the topological vector model?
Unique ID and series o
Topology can define features between these
Layers
This provides means for cleaning and verifying data
Topology
What are the two different types of topology?
Non-planar and planar
Between non-planar and planar topologies, which is more common?
Planar
These relationships can exist between layers in vector models
Topological relationships
In the vector data model, data is stored in these
Attribute tables
This type of linkage is the norm in the vector data model
One-to-one linkage
This type of linkage is less common but also used in the vector data model
Many-to-one linkage
In this type of data linkage, each object has a single table record
One-to-one linkage
In this type of data linkage, multiple objects link to a single record
Many-to-one linkage
In the vector data model, tables link features to attributes using these
Unique IDs
In the raster data model, spatial data describes the surface as this
Cell grid
In the raster data model, surface features are embodied by these
Values attached to cells
The raster data model is natural for this type of phenomenon
Continuous phenomenon
The raster data model is less commonly used for this type of feature
Discrete features
In the raster data model, cell coordinates define location relative to this corner of the cell
Lower left corner
What part of the cell do coordinates apply to in the raster data model?
Cell center point
Raster data is a tradeoff between spatial data and this
Data volume
In the raster data model, cell dimension affects this
Spatial precision
In the raster data model, are smaller or larger cells more precise?
Smaller cells
In the raster data model, positional accuracy is roughly no better than this
One-half cell size
In the raster data model, decreasing cell size rapidly increases this
Cell number
In the raster data model, what are the two ways to apply cell values?
To entire cell or to cell center
Raster layers can have these
Attributes
In the raster data model, cells are linked to these
Records in a table
What are the two ways to link cells to table records in the raster data model?
One-to-one or many-to-one linkage
This type of linkage creates very large tables in the raster data model
One-to-one linkage
What are three of five factors in choosing between vector and raster models?
- Predominant data type (discrete vs continuous); 2. Types of anticipated analyses; 3. Available data storage; 4. Main sources of input data; 5. User expertise
What are three of five advantages of the raster data model?
- 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
What are four of six advantages of the vector data model?
- 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
What are two common conversion rules in converting between raster and vector models?
Any cell and near cell center
In raster line to vector line conversion, to what part of the cell is cell value assigned?
Coordinates at cell center
This data model is used for representing terrain
Triangulated irregular network
This data model converts sets of x, y, z coordinates to a surface of connected triangles
Triangulated irregular network
Is the triangulated irregular network data model simpler than raster elevation data?
No
Is the triangulated irregular network model more efficient when the terrain is highly variable?
Yes
In the triangulated irregular network model, triangles are defined by these three parts
Points, edges and facets
In the triangulated irregular network data model, these are used to identify triangle corners
Convergent circles
What three data models can be used to model elevational data?
Vector, raster and triangulated irregular network
The combination of raster data model combined with triangulated irregular network model is called this
Digital elevation models
This data model represents elevation as contour lines
Vector data model
These two data models are best for analysis of elevational data
Raster data model and triangulated irregular network data model
These are often used in finished maps to represent elevation
Contour lines
