1. GIS Data Models

2. Geographic information
Characteristics of Geographic Information
Location!
volume
Dimensionality
Point
Line
Area
Continuity
Feature
field
Volume: A three-dimensional representation of a set of areas that encloses part of a surface. In a GIS, usually only the top surface is represented. For example, a lake is a volume features, but in a GIS only the top boundary of the volume is typically represented.
Dimensionality: The property of geographic features by which they are capable of being broken down into elements made up of points, lines, and areas. This corresponds to features being zero-, one-, or two-dimensional. A drill hole is a point, a stream is a line, and a forest is an area.
Continuity: The geographic property of features or measurements that gives measurements at all locations in space. Topography and air pressure are examples.

3. Building complex features
Simple geographic features can be used to build more complex ones.
Areas are made up of lines which are made up of points represented by their coordinates.
Areas = {Lines} = {Points}

4. Properties of Features
size
distribution
pattern
contiguity
neighborhood
shape
scale
orientation.

5. Basic properties of geographic features

6. GIS Analysis
Much of GIS analysis and description consists of investigating the properties of geographic features and determining the relationships between them.

7. GIS Capability A GIS package should be able to move between
map projections,
coordinate systems,
datums, and
ellipsoids.

8. Draw a map of your favorite place in Texas.

10. GIS Data Models

11. Maps as Numbers
GIS requires that both data and maps be represented as numbers.
The GIS places data into the computer’s memory in a physical data structure (i.e. files and directories).
Files can be written in binary or as ASCII text.
Binary is faster to read and smaller, ASCII can be read by humans and edited but uses more space.

12. The Data Model
A logical data model is how data are organized for use by the GIS.
GISs have traditionally used either raster or vector for maps.

13. Two approaches to handling spatial data with GIS:
Raster model
Vector model
Points,
lines,
polygons

14. Features and Maps
A GIS map is a scaled-down digital representation of point, line, area, and volume features.
While most GIS systems can handle raster and vector, only one is used for the internal organization of spatial data.

15. Rasters and vectors can be flat files … if they are simple
Vector-based line
Raster-based line
Flat File

16. A raster data model uses a grid.
One grid cell is one unit or holds one attribute.
Every cell has a value, even if it is “missing.”
A cell can hold a number or an index value standing for an attribute.
A cell has a resolution, given as the cell size in ground units.

17. Raster GIS Raster Data Model Rows and Columns of Cells (Array)
Area of Cell equals Spatial Resolution
Value for each cell records type of object or condition
Cells do not correspond to spatial entities in real world
A road is a group of cells, not a single entity
Cells are considered Homogeneous Units

18. Two approaches to handling spatial data with GIS:
Raster model
Vector model
Points,
lines,
polygons

19. Generic structure for a grid
Grid extent
Grid
cell s w o R
Resolution
Columns
Figure 3.1
Generic structure for a grid.

21. Definitions
Raster - A format for storing, processing, and displaying graphic data in which graphic images are stored as values for uniform grid cells or pixels.
Pixels - Abbreviation for picture element, the smallest indivisible element that makes up an image. In raster processing, data is represented spatially on a matrix of grid cells, called pixels, which are assigned values for image characteristics or attributes.

23. More Definitions
Resolution - A measure of the accuracy or detail of a graphic display, expressed as dots per inch, pixels per line, lines per millimeter, etc.
Spatial Resolution - The accuracy associated with the capture of ground information as reproduced in a digital format or graphic display. For example, 10-foot pixels vs. 100-foot pixels.

25. Definitions
Minimum Mapping Unit - The smallest element we can uniquely represent in our data.

26. Sources of Raster Data Satellite data Scanned aerial photography
LANDSAT
SPOT
Scanned aerial photography
Digital Orthophotography
Scanned maps and documents

27. From where do we get Raster Data?
SCANNED Aerial photographs
photographs are NOT raster images but SCANNED images ARE
SCANNED maps
Satellite images

30. From where are the data in a raster cell taken?

31. Why does it matter where the cell data come from?
It’s hard to tell just by looking at the image!

32. The mixed pixel problem

33. Grids and missing data Figure 3.8
GIS data layer as a grid with a large section of “missing data,” in this
case, the zeros in the ocean off of New York and New Jersey.

34. Why use Raster? Overlay Analysis/Overlay Operations
Arithmetic Operations
Addition
Subtraction
Division
Multiplication
Logical (Boolean) Operations
Where conditions occur or do not occur together
AND, OR, NOT, GT, LT, etc.

36. Raster GIS Applications
Integrate images to georeferenced data
i.e., parcel deed image linked to parcel centroid
Document Imaging
Natural Resource applications where:
Positional accuracy relaxed
Imagery-oriented

37. Raster Applications Utility Corridor Siting Environmental Mapping
Natural Communities Mapping
Forest resource planning
Spatial data variability decisions
Forest inventory
Wildlife habitat analysis

38. More Raster Applications
Wetlands Vegetation Inventory & Analysis
Agricultural analysis
Planetary analysis (including lunar)
Vector Updating
Digital Terrain Modeling
Flood Control & Emergency Preparedness
Communication System Engineering

39. Any Technology has Pro’s & Con’s

40. Raster Limitations Aesthetics Data storage requirements
Overlay operations performed on every cell
Sparse data sets require as much processing as dense ones

41. RASTER -- summary
A grid or raster maps directly onto a programming computer memory structure called an array.
Grids are poor at representing points, lines and areas, but good at surfaces.
Grids are good only at very localized topology, and weak otherwise.
Grids are a natural for scanned or remotely sensed data.
Grids suffer from the mixed pixel problem.
Grids must often include redundant or missing data.
Grid compression techniques used in GIS are run-length encoding and quad trees.

42. GIS Data Models

43. Rasters are faster, but...
Points and lines in raster format have to move to a cell center.
Lines can become fat. Areas may need separately coded edges.
Each cell can be owned by only one feature.
As data, all cells must be able to hold any cell value.
It is very difficult to precisely position features in space.

44. Vector GIS Data Model Precisely position features in space
Points, Nodes, vertex, single X,Y coordinate pair
Lines, Arcs, series of X,Y coordinate pairs
Area, Polygons, area as a closed loop of X,Y coordinate pairs

45. Areas are lines are points are coordinates

46. The Vector Model
A vector data model uses points stored by their real (earth) coordinates and so requires a precise coordinate system.
Geographic Coordinate System
Latitude/Longitude
Cartesian Coordinate Systems
X,Y Coordinate system
State Plane
UTM (Universal Transverse Mercator)
Lines and areas are built from sequences of points in order.
Lines have a direction to the ordering of the points.
Polygons can be built from points or lines.
Vectors can store information about topology.

47. Raster/Vector Comparison

48. VECTOR
At first, GISs used vector data and cartographic spaghetti structures.
Collection of coordinate strings with no structure
Cartesian coordinates stored in data structure
No spatial relationships stored
Inefficient data storage technique
Vector data evolved the arc/node model in the 1960s.
In the arc/node model, an area consist of lines and a line consists of points.
Points, lines, and areas can each be stored in their own files, with links between them.

49. Arc/node map data structure with files13
1 x y 11
2 x y e l 12 i
3 x y F 10 2
4 x y s 7 t
5 x y n i
POLYGON “A” 5 o
6 x y P 9
7 x y 4 6
8 x y 1
9 x y 2
10 x y 3
11 x y 8
12 x y 1
13 x y
File of Arcs by Polygon A
: 1,2
, Area, Attributes 1
1,2,3,4,5,6,7 2
1,8,9,10,11,12,13,7
Arcs File
Figure 3.4
Arc/Node Map Data Structure with Files.

50. The topological vector model uses the line (arc) as a basic unit
The topological vector model uses the line (arc) as a basic unit. Areas (polygons) are built up from arcs.
The endpoint of a line (arc) is called a node. Arc junctions are only at nodes.
Stored with the arc is the topology (i.e. the connecting arcs and left and right polygons).

51. Vectors TIN must be used to represent volumes.
Vector can represent point, line, and area features very accurately.
Vectors work well with pen and light-plotting devices and tablet digitizers.
Vectors are not good at continuous coverages or plotters that fill areas.

53. Topological Model
Topology: mathematical method to define spatial relationships
Arc-node data model
Arc: a series of points that start and end at a node
Node: an intersection point where two or more arcs meet

54. Topological Data Spatial Operations
Contiguity: spatial relationship of adjacency
i.e., stand of coniferous trees adjacent to deciduous trees
Connectivity: interconnected pathways or networks
i.e., street and trail networks, stream networks

55. Basic arc topology n2 3 2 A 1 B n1 Topological Arcs File Arc From ToPL PR
n1x
n1y
n2x
n2y 1 n1 n2 A B x y x y
Figure 3.5
A topological structure for the arcs.

56. TOPOLOGY Topological data structures dominate GIS software.
Topology allows automated error detection and elimination.
Rarely are maps topologically clean when digitized or imported.
A GIS has to be able to build topology from unconnected arcs.
Nodes that are close together are snapped.
Slivers due to double digitizing and overlay are eliminated.

57. Slivers
Sliver

58. Unsnapped node

59. Topology Matters
The tolerances controlling snapping, elimination, and merging must be considered carefully, because they can move features.
Complete topology makes map overlay feasible.
Topology allows many GIS operations to be done without accessing the point files.

60. Vectors and 3D
Volumes (surfaces) are structured with the Triangulated Irregular Network model, including edge or triangle topology.
TINs use an optimal Delaunay triangulation of a set of irregularly distributed points.
TINs are popular in CAD and surveying packages.

61. TIN: Triangulated Irregular Network
Way to handle field data with the vector data structure.
Common in some GISs and most AM/FM packages.
More efficient than a grid.

62. Sources of Vector Data RASTER-VECTOR conversions from scanned images
Pre-existing digital data from disks or internet
DIGITIZING

64. Vector to raster to vector conversion

66. Comparison: Raster and Vector

68. FORMATS
Most GIS systems can import different data formats, or use utility programs to convert them.
Data formats can be industry standard, commonly accepted or standard.

69. Vector Data Formats
Vector formats are either page definition languages or preserve ground coordinates.
Page languages are HPGL, PostScript, and Autocad DXF.
True vector GIS data formats are DLG and TIGER, which has topology.

70. Raster Data Formats Most raster formats are digital image formats.
Most GISs accept TIF, GIF, JPEG or encapsulated PostScript, which are not georeferenced.
DEMs are true raster data formats.

71. EXCHANGE Most GISs use many formats and one data structure.
If a GIS supports many data structures, changing structures becomes the user’s responsibility.
Changing vector to raster is easy; raster to vector is hard.
Data also are often exchanged or transferred between different GIS packages and computer systems.
The history of GIS data exchange is chaotic and has been wasteful.

72. Vector to raster exchange errors

73. Transfer Standards

74. GIS Data Exchange
Data exchange by translation (export and import) can lead to significant errors in attributes and in geometry.
In the United States, the SDTS was evolved to facilitate data transfer.
SDTS became a federal standard (FIPS 173) in 1992.
SDTS contains a terminology, a set of references, a list of features, a transfer mechanism, and an accuracy standard.
Both DLG and TIGER data are available in SDTS format.
Other standards efforts are DIGEST, DX-90, the Tri-Service Spatial Data Standards, and many other international standards.
Efficient data exchange is important for the future of GIS.

75. Attribute data Attribute data are stored logically in flat files.
A flat file is a matrix of numbers and values stored in rows and columns, like a spreadsheet.
Both logical and physical data models have evolved over time.
DBMSs use many different methods to store and manage flat files in physical files.