Playing with Spaghetti: Vector and Raster Data Models in Depth

1
Playing with SpaghettiVector and Raster Data
Models in Depth

• Talbot J. Brooks
• ASU Dept. of Geography

2
Tonights topics

• Recap of discussion so far
• Big picture overview Raster vs. Vector
• The details Vector data models
• The details Raster data models
• Cardinality an exercise

3
Review you tell me

• What is the difference between vector and raster
  data?
• Basic vector data types
• Examples of raster data
• Computer file structures
• Flat
• Hierarchical
• Network
• Relational

4
RASTER AND VECTOR FORMATS
RASTER Grid-based, Simplify reality VECTOR
Analog map, Cartography
5
DATA MODEL OF RASTER AND VECTOR
REAL WORLD
1 2 3 4 5 6
7 8 9 10
1 2 3 4 5 6 7 8 9 10
GRID RASTER
VECTOR
6
RASTER DATA MODEL

• derive from formulation that real world - it has
  spatial elements and objects fills those elements
• real world is represented with uniform cells
• list of cells is a rectangle
• cell comprises of triangles, hexagon and higher
  complexities
• a cell reports its own true characteristics
• per units cell does not represent an object
• an object is represented by a group of cells

7
Lake
River
Pond
Reality - Hydrography
Lake
River
Pond
Reality overlaid with a grid
1
1
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
0
0
0
0
0
0
0
0 No Water Feature 1 Water Body 2 River
1
1
1
2
0
0
0
0
0
0
0
0
2
2
1
1
0
0
0
0
0
0
0
0
2
2
0
0
0
0
0
0
0
0
0
0
2
0
0
0
0
0
0
0
0
0
0
0
Resulting raster
Creating a Raster
8
VECTOR DATA MODEL

• derived from the formulation of spatial concepts
  that emphasize on real world objects
• geometry primitives of vector data model are
  point, line and polygon
• objects can be built from these primitives
• object location determined by represented
  location point
• uniqueness of vector data model lies in its
  management and storage of data geometry
  primitives
• spaghetti model
• topology model

9
VECTOR CHARACTERISTICS
POINT X LINE POLYGON
10
RASTER TO VECTOR
RIVER CHANGED FROM RASTER TO VECTOR FORMAT
RIVER THAT HAS BEEN
VECTORISED ORIGINAL RIVER
11
PRO AND CONS OF RASTER MODEL

• pro
• raster data is more affordable
• simple data structure
• very efficient overlay operation
• cons
• topology relationship difficult to implement
• raster data requires large storage
• not all world phenomena related directly with
  raster representation
• raster data mainly is obtained from satellite
  images and scanning

12
PRO AND CONS OF VECTOR MODEL

• pro
• more efficient data storage
• topological encoding more efferent
• suitable for most usage and compatible with data
• good graphic presentation
• cons
• overlay operation not efficient
• complex data structure

13
A look behind the scenes Vector GIS data models

• Spaghetti model
• Topological vector model
• Cardinality (this is gonna hurt!)
• Break

14
The Spaghetti Model

• The spaghetti model is the most simple vector
  data model
• The model is a direct representation of a
  graphical image
• NO explicit topological information

15
Spaghetti Model

• Description direct line for line translation of
  the paper map (often viewed as raw digital data)
• Pros easy to implement, good for fast drawing
• Cons storage and searches are sequential,
  storage of attribute data

16
Spaghetti model
17
Topology

• Branch of mathematics dealing with geometric
  properties
• Geometry of objects remain invariant under
  transformations
• Neighborhood relationships remain the same
• Topology is the distinguishing basis for more
  complicated vector models

18
Topological Vector Model

• Topological data models are provided with
  information that can help us in obtaining
  solutions to common operations in advanced GIS
  analytical techniques.
• This is done by explicitly recording adjacency
  information into the data structure, eliminating
  the need to determine it for multiple operations.
• Each line segment, the basic logical entity in
  topological data structures, begins and ends when
  it either contacts or intersects another line, or
  when there is a change in direction of the line.

19
Topological Vector Model

• Each line has two sets of numbers, a pair of
  coordinates and an associated node number.
• Each line segment has its identification number
  that is used as a pointer to indicate which set
  of nodes represent its beginning and ending.

20
Topological Vector Model

• Polygons also have identification codes that
  relate back to the link numbers. Each link in
  the polygon now is capable of looking left and
  right at the polygon numbers to see which two
  polygons are also stored explicitly, so that even
  this tedious step is eliminated.
• The Topological data model more closely
  approximates how we as map readers identify the
  spatial relationships contained in an analog map
  document.

21
Topological Vector Model
22
How do we preserve topology ina computer
database?

• What are we storing?
• Points, lines, polygons
• What do we need to preserve?
• Neighborhood relationships between these objects
• Terminology
• point, link, node, polygon

23
Terminology

• Point x, y coordinate identifying a geographic
  location
• Link (line, arc) an ordered set of points with a
  node at the beginning and end of it
• Node the beginning and end of link (often
  defined where 3 or more lines connect)
• Polygon two or more links connected at the
  nodes, contains a point inside to identify the
  polygons attributes

24
Nevada
Utah
California
Arizona
25
Identify the polygons
26
Create the polygon attribute table (PAT)
27
Identify the nodes
28
Node table
29
Identify the links (arcs, lines)
30
Simplify this
31
Create the topology!
32
Nodes First
33
Nodes First
34
Polygons
35
Polygons
36
Identify the points
37
Link List
38
Point Coordinates
39
Putting it all together
40
Putting it all together
41
Putting it all together
42
Putting it all together
43
Putting it all together
44
Cardinality

• Cardinality is the relationship between spatial
  objects, attributes, or spatial objects and
  attributes.
• This relationship may be defined as
• 11
• 1many
• manymany

45
Cardinality

• We can use cardinality to establish relationships
  and rules among objects and attributes
• This becomes the basis for modeling how data is
  arranged within a GIS - especially one that uses
  vector data.

46
Cardinality contd

• Entity-entity relationships are described by
  cardinality which may be
• One to one. A FOREST can have only one MANAGER
  and a MANAGER can have only one FOREST
• Many to one. Many FACILITIES may be contained
  within one FOREST
• Many to Many. The relationship water_supply may
  have many entries and may be connected to many
  entries FACILITIES, FOREST, etc

47
Cardinality contd

• The same concept applies to space
• A bathroom is located within a house (11)
• Many homes are within a town (many1)
• Many people are within many homes (manymany)

48
Diagram Characteristics

• Boxes represent entities
• Ovals represent attributes
• Diamonds represent relationships
• Note how cardinality is depicted
• Key attributes are underlined
• Multi-valued attributes are in double ovals

49
Entity-Relationship (ER) Diagrams A Conceptual
Model
50
Exercise work in pairs 10 minutes

• Create a simple ER diagram for your neighborhood
• Pick a feature that matches each geometry type
  (point, line). For example
• For points, you might pick fire hydrants and lamp
  posts
• For lines, you might pick streets and water mains
• For polygons, pick parcels or zip codes