1. 8. Geographic Data Modeling

2. Outline Definitions Data models / modeling GIS data models – Topology

3. Definitions Data model – set of constructs for representing objects and processes in the digital environment Representation – Focus on conceptual and scientific issues

4. Role of a Data Model

5. Levels of Data Model Abstraction

6. How is a GIS map organized? A GIS map consists of one or more data layers. Each layers contains a collection of features that represent real-world objects.

7. GIS Data Models & Applications CAD Graphical Image Raster/Grid Network Geo-relational TIN Object Engineering design Simple mapping Image processing and analysis Spatial analysis / modeling Network analysis Geoprocessing geometric features Surface /terrain analysis / modeling Features with behavior

8. Raster and Vector Models Raster – implementation of field conceptual model – Array of cells used to represent objects – Useful as background maps and for spatial analysis Vector – implementation of discrete object conceptual model – Point, line and polygon representations – Widely used in cartography, and network analysis

9. Raster Spatial features modeled with grids, or pixels Grid cells identified by row and column number Grid cells are usually square in shape The dimension of each cell defines the resolution Each cell store only one attribute, in the form of a “z” value – cell value

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

11. Cell Values: One Value per Cell Each pixel or cell is assumed to have only one value – This is often inaccurate -the boundary of two soil types may run across the middle of a pixel – In such cases the pixel is given the value of the largest fraction of the cell (this is called dominant rule)

14. Raster data compression Run length encoding can be more efficient – One of data compression methods Data entered as pairs, first run length, then value Example: this array would be entered as: 3 0 5 2 8 5 9 1 5 3 There are 10 items to enter, instead of 30

15. Vector Model Points are defined by a single x,y coordinate pair Lines are defined by two or more x,y coordinate pairs Polygons are defined by lines that close to form the polygon boundaries In the vector data model, every feature is assigned a unique numerical identifier, which is stored with the feature record in an attribute table.

16. Vector Data Model

17. Raster and Vector representations of the same land use Vector Raster

18. Which data model should you use? Both the vector and raster data models are useful for representing geographic data, but one may be more appropriate than the other when it comes to representing a particular type of geographic data or answering different kinds of questions. In general, use the vector data model when you want to represent features that have discrete boundaries. For example, a building is well represented as a polygon feature with x,y coordinates recorded for its corners. The raster data model is very useful for representing continuous geographic data; that is, phenomena such as elevation, precipitation, and temperature, which don't have well-defined boundaries and which usually change gradually across a given area.

19. Discrete features can be represented using either vector or raster, but … Representing discrete features in the raster data model is less accurate.

20. Figure 3.9 Raster and vector spatial data (Continued)

21. Figure 3.10 Effect of changing resolution in the raster (left) and vector worlds (right)

22. Vector GIS: Topology Topology (from the Greek τόπος, “place”, and λόγος, “study”) is a major area of mathematics concerned with properties that are preserved under continuous deformations of objects, such as deformations that involve stretching, but no tearing or gluing. It emerged through the development of concepts from geometry and set theory, such as space, dimension, and transformation. Also called rubber sheet geometry. Science and mathematics of geometric relationships – Simple features + topological rules – Connectivity – Adjacency – Intersection (shared nodes/edges) Topology uses – Data validation – Spatial analysis (e.g. network tracing, polygon adjacency)

23. Topology Defines Spatial Relationships Relationships based on location are called spatial relationships. Four basic types of spatial relationships: distance, containment, intersection, and adjacency. Getting answers to questions that are based on spatial relationships is the reason people use a GIS. Examples of questions that can be answered using feature spatial relationships are: - How many houses are less than 1 mile from the airport? - Which parcels are contained by the contamination plume? - Which bridges intersect the fault line? - Which land uses are adjacent to the proposed subdivision?

24. Rubber sheet geometry

25. Points within a given distance of the red point Points contained by the polygon Lines that intersect the red line Polygons adjacent to the red polygons

26. Vector Topology helps deal with: overshoots slivers dangles Not sharing border

27. Topological Polygon Data Layer

28. Contiguity of Topological Polygons

29. Geo-relational Polygon Dataset

30. Vector Topology Table in ArcGIS Graphical display of arcs, nodes, vertices and lines Topology table for the ARCs making up the polygons A table of the polygon topology

31. Vector Topology Table Node # Arcs meeting the Node 1 2 3 …… 4,1 1,2,7 5,6,7,8 …… Graphical display of arcs, nodes, vertices and lines

32. Figure 8.11 An example street network GIS Network Data Model

33. Network data model

34. Examples of GIS networks

35. Link, turn and stop impedances affecting the journey of a delivery van

36. A representation of the London Underground network

37. TIN Surface of Death Valley, California

43. Example DEM and TIN model for region of varying complexity