8. Geographic Data Modeling

Outline

• Definitions• Data models / modeling• GIS data models

– Topology

Definitions

• Data model– set of constructs for representing objects and

processes in the digital environment• Representation

– Focus on conceptual and scientific issues

Role of a Data Model

Levels of Data Model Abstraction

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.

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

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

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

Generic structure for a grid

Figure 3.1 Generic structure for a grid.

Row

s

Columns

Gridcell

Grid extent

Resolution

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)

Raster data compression

• Run length encoding can be more efficient– One of data compression methodsData 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

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.

Vector Data Model

Raster and Vector representations of the same land use

Vector

Raster

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.

Discrete features can be represented using either vector or raster, but …

Representing discrete features in the raster data model is less accurate.

Figure 3.9 Raster and vector spatial data (Continued)

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

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)

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?

Rubber sheet geometry

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

Vector Topology helps deal with:

overshoots

slivers

dangles

Not sharing border

Topological Polygon Data Layer

Contiguity of Topological Polygons

Geo-relational Polygon Dataset

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

Vector Topology Table

Node # Arcs meeting the Node123……

4,11,2,75,6,7,8……

Graphical display of arcs, nodes, vertices and lines

Figure 8.11 An example street networkGIS Network Data Model

Network data model

Examples of GIS networks

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

A representation of the London Underground network

TIN Surface of Death Valley, California

TIN Surface of Death Valley, California

TIN Surface of Death Valley, California

Example DEM and TIN model for region of varying complexity