1. Introduction to Cartographic Modeling
RNR 419/519
Introduction to Cartographic Modeling

2. Analysis vs. Synthesis
Analysis – the separating of an entity its constituent elements or the manipulation and assessment of data to better understand or represent its form and function. RNR 473/573 – Fall
Synthesis – the combining of constituent elements into single and unified entity, typically done through a model. RNR 419/519 - Spring

3. Definitions
An analysis method is spatial if the results depend on the locations of the objects being analyzed
Move the objects and the results change
Results are not invariant under relocation
Spatial concepts (location, distance, adjacency) appear explicitly
Spatial analysis requires both attributes and locations of objects
a GIS has been designed to store both

4. Spatial Modeling
A model is used to integrate data to create information.
A model is a simplification (logical or physical) of a process or system.
Elements (thematic layers) represent inputs into the model that are integrated, usually mathematically, to create the output, the new information.
In Cartographic Modeling the output is typically a new thematic layer

5. Spatial Processes: General Principles
Integration of data through the GIS:
* Linking data through common location–the thematic
layer cake
* Linking processes across disciplines–spatially
explicit processes–e.g. social-economic and
biophysical processes interact at common locations
* Place-based modeling – representation of a location

6. GIS Database
A GIS database consists of a set of thematic layers representing different entity types.
Data may include:
Vector Data
Raster Data
Images
CAD Draws
Associated Tables
Graphics and Text

7. Rasters and Vectors
How to represent phenomena conceived as fields or discrete objects? Two basic data structures.
Raster
Divide the world into square cells, rectangle matrix
Register the corners to the Earth
Represent discrete objects as collections of one or more cells
Represent fields by assigning attribute values to cells
More commonly used to represent fields than discrete objects

8. Rasters
Most rasters are uniform tessellation of square cells, but raster
elements do not need to be square, nor must a raster be uniform.

9. Continuous Information
Each cell has a value that represents the average elevation for the cell.

10. Discrete Types
Legend
Mixed conifer
Douglas fir
Oak savannah
Grassland
Raster representation. Each color represents a different value of a nominal- scale field denoting land cover class.

11. Characteristics of Rasters
Pixel size
The size of the cell or picture element, defining the level of spatial detail
All variation within pixels is lost
Assignment scheme
The value of a cell may be an average over the cell, or a total within the cell, or the commonest value in the cell
It may also be the value found at the cell’s central point

12. Effect of a raster representation using:
the largest share rule
(B) the central point rule

13. Vector Data Used to represent points, lines, and areas
All are represented using coordinates
One per point
Areas as polygons
Straight lines between points, connecting back to the start
Point locations recorded as coordinates
Lines as polylines
Straight lines between points

14. Vector Data Point Number X,Y Coordinates 1 2,4 2 3,2 3 5,3 4 6,2
Points
Point Number X,Y Coordinates ,4 ,2 ,3 ,2
Line Number X,Y Coordinates
,5 3,6 6,5 7,6
,1 3,3 6,1 7,3
Polygon Number X,Y Coordinates
1 1,5 3,6 4,4 2,2 1,5
2 6,6 8,7 8,3 7,3 6,6 1 3 2 4
Lines 1 2
Polygons 2 1

15. An area (red line)
and
its approximation by a polygon (dashed blue line)

16. Raster vs. Vector
Smallest addressable unit in Raster is a cell and in Vector is a point.
Raster can represent both objects and fields, Vector has difficulty representing fields.
Vector can represent the true dimensions of a object, Raster will always distort an object.
Vector makes better graphics.
Easier to write algorithms and integrate data in raster

17. Raster vs Vector
Volume of data - raster becomes more voluminous as cell size decreases
Vector handles tabular data more effeciently
Source of data- remote sensing, elevation data come in raster form
Vector used for problems where parcels and lines are issues (AM/FM, Property Mgt)
Raster is better for fields and integrating data – used in modeling

18. Types of Attributes Level of Measurement
Nominal – Name (land cover class)
Ordinal – rank (a ranking of habitat)
Interval – no true zero (Celsius temperature)
Differences make sense
Ratio – true zero (Kelvin temperature)
Ratios make sense
Cyclic – (wind direction)