1. MODELLING AND STRUCTURING DATA

2. Representing Spatial Elements
RASTER
VECTOR
Real World
Spatial data is essentially data with a location. It contains information about the location and shape of, and relationship among geographic features usually stored as coordinates. Spatial data comes in two types, VECTOR and RASTER. Geographic information systems work with two fundamentally different types of geographic models--the "vector model" and the "raster model."

3. Representing Spatial Elements
Raster
Stores images as rows and columns of numbers with a Digital Value/Number (DN) for each cell.
Units are usually represented as square grid cells that are uniform in size.
Data is classified as “continuous” (such as in an image), or “thematic” (where each cell denotes a feature type.
Numerous data formats (TIFF, GIF, ERDAS.img etc)
A raster image comprises a collection of grid cells rather like a scanned map or picture. Both the vector and raster models for storing geographic data have unique advantages and disadvantages.
Raster models do not provide precise locational information because space is divided into discrete grid cells. The assumption is that a point can be found within a grid cell.

4. Representing Spatial Elements
Vector
Allows user to specify specific spatial locations and assumes that geographic space is continuous, not broken up into discrete grid squares
We store features as sets of X,Y coordinate pairs.
In the vector model, information about points, lines, and polygons is encoded and stored as a collection of x,y coordinates. A single x, y coordinate, can describe the location of a point feature, such as a control tower. Linear features, such as roads and rivers, can be stored as a collection of point coordinates. Two coordinate pairs are enough to show location and orientation in space. Polygonal features, such as an area of operations and lakes, can be stored as a closed loop of coordinates. The vector model is extremely useful for describing discrete features, but less useful for describing continuously varying features such as soil type.
Spatial data is unique to a GIS in that there are two aspects two it. It has a location and an attribute. The location can be either a geographic coordinate, MGRS coordinate, or any other (x,y) coordinate. The attribute can be either adjectival (describing the object) or have a magnitude (a numerical value).

5. Entity Representations
We typically represent objects in space as three distinct spatial elements:
Points - simplest element
Lines (arcs) - set of connected points
Polygons - set of connected lines
We need symbolize spatial features in order to be able to associate attribute information.
We can classify different features into different dimensions. Each classification of dimension is a conceptual classification.
Points - “0” dimensionality. No length or Width.
Each point is Discrete in that it can only occupy a given point in space at any given time.
Lines - “1” dimensional. Length, but No Width.
Must have a beginning and an ending point.
Polygons - “2” dimensional. Length and Width.
By adding Width, we can describe a feature as having an area.
Surfaces - “3” dimensional. Length, Width, and Height.
Surfaces have infinite number of values (e.g. Elevation). We say that this type of data is Continuous.
When thinking of spatial elements, we must consider Spatial Scale. Depending on scale, we may want to represent a river as a line or a polygon.
We use these three spatial elements to represent real world features and attach locational information to them.

6. Attributes
In the raster data model, the cell value (Digital Number) is the attribute. Examples: brightness, landcover code, SST, etc.
For vector data, attribute records are linked to point, line & polygon features. Can store multiple attributes per feature. Vector features are linked to attributes by a unique feature number.

7. Raster vs. Vector Raster Advantages Vector Advantages
The most common data format
Easy to perform mathematical and overlay operations
Satellite information is easily incorporated
Better represents “continuous”- type data
Vector Advantages
In Raster we explicitly store attribute information and imply its location based on the position within the grid cell structure.
In Vector, we explicitly store the entity information and where the entity is located. We rely on a database structure to link to attribute information.
Accurate positional information that is best for storing discrete thematic features (e.g., roads, shorelines, sea-bed features.
Compact data storage requirements
Can associate unlimited numbers of attributes with specific features

8. GIS FUNCTIONALITY
(What do they do?)

9. GIS Functions Data Assembly Data Storage
Spatial Data Analysis and Manipulation
Spatial Data Output

10. GIS Functions Data Assembly Manual Digitizing Manual Digitizing
Scanning
Manual Digitizing
Scanning
RSI
Maps
Intel Database
Data Transfer
Data Transfer
I n p u t: Before geographic data can be used in a GIS, the data must be converted into a suitable digital format. The process of converting data from paper maps into computer files is called digitizing. Modern GIS technology can automate this process fully for large projects using scanning technology; smaller jobs may require some manual digitizing (using a digitizing table). Today many types of geographic data already exist in GIS-compatible formats. NIMA standard digital data exists in useable formats and can usually be loaded directly into a GIS.
Direct Entry
GPS
Keyboard

11. Data Input/Creation
This slide demonstrates heads-up digitizing done in ArcView.

12. GIS Functions Spatial data Attribute data GIS Storage (ARC functions)
1 (Universe polygon)
Spatial data 2 3 3
(ARC functions) 4 5
Storage: For small GIS projects it may be sufficient to store geographic information as simple files. There comes a point, however, when data volumes become large and the number of data users becomes more than a few, that it is best to use a database There are many different designs of DBMSs, but in GIS the relational design has been the most useful. A DBMS is nothing more than computer software for managing a database--an integrated collection of data. In the relational design, data are stored conceptually as a collection of tables. Common fields in different tables are used to link them together. This surprisingly simple design has been so widely used primarily because of its flexibility and very wide deployment in applications both within and without GIS.
COV# ZONE ZIP 1 2
C-19
22060
Attribute data 3
A-4
22061 3
A-4
22061 4
C-22
22060
(INFO or TABLES functions) 5
A-5
22057

13. GIS Functions Spatial Data Manipulation and Analysis
Common Manipulation
Reclassification
Map Projection changes
Common Analysis
Buffering
Overlay
Network
Analysis and M a n i p u l a t i o n: It is likely that data types required for a particular GIS project will need to be transformed or manipulated in some way to make them compatible with your system. For example, geographic information is available at different scales (street centerline files might be available at a scale of 1:100,000; Topographic line maps data such as ITD at 1:50,000). Before this information can be integrated, it must be transformed to the same scale. This could be a temporary transformation for display purposes or a permanent one required for analysis. GIS technology offers many tools for manipulating spatial data and for weeding out unnecessary data.

14. Spatial Analysis
Overlay function creates new “layers” to solve spatial problems
The overlay operation is one the most powerful functions in a GIS. It gives the user the ability to place the cartographic representation of thematic data over one another.
However, this is hardly a new function developed by a GIS, but it has been revolutionized by the use of the computerized GIS.

15. GIS Functions Spatial Data Output Tables Maps Interactive Displays
3-D Perspective View
There are many forms of output for a GIS. The first is usually softcopy, namely what you see on the screen. Most Military service member and commanders prefer to have something hardcopy. So more often than not, will require hard copy outputs. A full functioning GIS can do this. It can plot/print given the equipment, the 2D and 3D perspective views on a 2D map.

16. SOME EXAMPLES
AND APPLICATIONS

17. GIS Applications Site selection Helicopter Landing Zones
Amphibious Assault (Water Depth)
Buffer Zones
Flight Planning
Battlefield Visualisation
Talk to each one relevant to the audience.

18. Helicopter Landing Zones
HLZ sites
This slide shows Helicopter Landing Zones within ArcInfo

19. Amphibious Assault Planning
Often times to map the ocean floor in terms of elevation we use Bathymetric data or DBTB (Digital Bathymetric Data Base). This slide also shows vector data overlaid on top of the data.

20. Spatial Analysis Proximity Analysis (Buffers)
1000 Meter Buffer of Railroads
This slide shows a proximity analysis of railroads around the Tuzla airport in Bosnia. The buffer is 1000 meters and the areas in blue represent all areas within this 1000 meter range.
CAUTION: DO NOT Make assumptions based on visual correspondence only. The user must obtain evidence on a true cause and effect relationship.

21. Flight Planning
This slide shows an example of flight planning within ArcView through the use of Elevation and Cloud cover data.

22. Flight Planning/Flythroughs

23. Battlefield Visualization and/or Situation Awareness

24. Other GIS Applications
Cross country movement
Route planning
Intervisibility study
Facilities management
Airfield assessment
Road network analysis (convoys)
Propagation coverages
Observation post siting analysis
Perspective views

25. CCM Analysis
CCM (Cross Country Movement) Analysis allows the user to model the cost (e.g. time) it would take for a give object to travel from point A to Point B given the difficulty of the terrain.
For example, if a tank had to travel from point A to point B and you new how fast it could travel on certain road types, soil types, and slopes, you could model the travel cost.

26. CCM & Viewshed
This slide shows a CCM analysis along with a viewshed analysis. The viewshed analysis is used to illustrate what a person can or can not see from a certain point. The two areas denoted by the purple and turquoise angles illustrate two separate viewsheds. The region of overlap shows the area that can be see by both observers from their respective positions.

27. Facilities Management
Facilities Management encompasses a wide range of applications. The examples shown above are:
1. Housing Assessments
2. Power Line Maintenance and Tracking
3. Crime around Schools
4. Water lines/pipes Maintenance and Tracking

28. Airfields
This slide shows information on Airfields along with a picture/movie that has been hot-linked to the feature.

29. Network Analysis
The slide shows a Network model, which gives the best route given certain criteria. The green squares denote bridges, which can serve as a limitations within the model. For example, if a bridge was impassible, we could factor that criteria into our model and the route could be recalculated giving us a different solution.

30. Antenna Propagation Coverages

31. Observation Post Siting Analysis

32. Perspective Views
This slide shows a perspective view. A LANDSAT image has been draped over DTED and the buildings have been overlaid over the image and “grown” to represent a 3D view.

33. SUMMARY
Key Concepts
Data representation
Applications