1. Spatial Data Entry via Digitizing
May 5, 2016

2. Digitizing Process of collecting digital coordinates
Common data entry method
Process by which coordinates from a map, image, or other sources are converted into a digital format in a GIS
Nearly all geographic information produced before 1960 was recorded in hardcopy form.

3. Digital spatial data Data in computer compatible format
Text files
List of coordinates
Digital images
Coordinate and attribute data in electronic file format
Common source of digital information

4. Digitizing Methods Manual digitization
Human guided coordinate capture from a map or image source
On-screen digitizing (heads-up digitizing)
Hardcopy map digitizing
On-screen digitizing: digitizing on a computer screen using digital image as a back drop.

5. Characteristics of Manual Digitizing
Data accuracy may be affected due to
Equipment characteristics
Errors in original scanned document
Abilities and attitude of person digitizing
Map scale
Small errors in map production may cause significant positional errors
may negatively affect the positional quality of spatial data
Greater for smaller scale maps
Map scale impacts the spatial accuracy of digitized data.

6. Larger Error at Smaller Map Scale
Surface Error caused by a one millimeter Map Error
Map Scale
Error (m)
Error (ft)
1:24,000 24 79
1:50,000 50
164
1:62,500
62.5
205
1:100,000
100
328
1:250,000
250
820
1:1,000,000
1,000
3,281
Table 4-1 of Text book
Effect of 1 mm on different scales

7. Digitizing Process Display image on screen Trace locations of feature
Point
Features that are viewed as points
Line
linear features
Starting point is called ‘starting node’
Vertices: intermediate nodes
Ending node
Polygon

9. Digitizing Errors
Positional errors are inevitable in manual digitization
Undershoots and overshoots
Common error of digitization
Undershoots: nodes that do not quite reach the line or another node
Cause unconnected networks and unclosed polygons
Overshoots: lines that cross over existing nodes or lines
May cause difficulties in network analyses

11. Node and Line Snapping
To reduce undershoots and overshoots while digitizing
Snapping: process of automatically setting nearby points to have the same coordinates.
Relies on a snap tolerance or snap distance
Prevent a new node from being placed within the snap distance of an already existing node – new node is joined or snapped to the existing node ensuring connection between digitized lines

13. Snapping Distance/Tolerance
Careful selection may reduce digitizing errors
Too short or too large – Problem
Should be smaller than the desired positional accuracy
Should not be below the capabilities of the system used for digitizing

14. Reshape: Line Smoothing and Thinning
Software may provide tools to
Smooth
Densify
Thin
Spline Function
To smoothly interpolate curves between digitized points

15. Coordinate Transformation
To bring spatial data into an Erath-based map coordinate system so that each data layer aligns with every other data layer
Also referred to as “Registration” – because it registers the layers to a map coordinate system
Control points are needed

16. Control Points A set of control points is used for transformation
Used to estimate the coefficients for transformation equation
Criteria for selecting a control point
A sufficient number of control points should be selected
Minimum number depends on the mathematical form of the transformation
Additional points above minimum numbers are recommended to improve the quality and accuracy of the statistically-fit transformation
Should be from a source that provides the highest feasible coordinate accuracy
Control point accuracy should be at least as good as the desired overall positional accuracy required for the data
Should be as evenly distributed as possible throughout the data area

17. Control Point Sources
????

18. Image Transformation: Georeferencing
Georeferencing is the process of defining how raster data is situated in map coordinates
Aligning the raster with control points

19. Types of Transformation
Polynomial
Spline
Adjust transformation

20. Polynomial Transformation
Uses a polynomial that is built upon control points and a least square fitting (LSF) algorithm
It is optimized for global accuracy but does not guarantee local accuracy
Yields two formulas:
one for computing the output x-coordinate for an input (x, y) location and
one for computing the y-coordinate for an input (x,y) location
Number of control points required for this method must be 3 for a first order, 6 for a second order, and 10 for a third order
source: ESRI-ARCGIS

21. 1st Order Polynomial – Affine Transformation
Employs linear equations to calculate map coordinates
Provides translation, rotation and scaling
6 unknowns and hence needs 6 equations

22. Affine Transformation
C and F are translation changes between coordinate systems – shifts in the origins from one system to the next
Other parameters incorporate the change in scales and rotation angle
500, = A (103.0) + B (-100.1) + C
5,003,683.5= D (103.0) + E (-100.1) + F
This generally results in straight lines on the raster dataset mapped as straight lines in the warped raster dataset.

23. Affine Transformation
3 GCPs - can exactly map each raster point to the target location
Any more than three links introduces errors, or residuals
However, add more than three GCPs because if one link is positionally wrong, it has a much greater impact on the transformation
Even though the transformation error may increase as with more GCPs -the overall accuracy of the transformation will increase as well

24. Second- or Third-order transformation
In addition to translation, scaling, rotation - raster dataset may be bent or curved

25. Root Mean Square Error
A measure of the error—the residual error
Difference between where the from point ended up as opposed to the actual location
When the error is particularly large, try to remove and add control points to adjust the error
RMS of near zero or zero does not mean that the image is perfectly georeferenced
Typically, the adjust and spline transformations give an RMS of near zero or zero; however, this does not mean that the image will be perfectly georeferenced