This document discusses geo-referencing raster data. It defines geo-referencing as aligning raster data to real-world coordinates so it can be viewed and analyzed with other geographic data. There are two main types of geo-referencing: absolute, which aligns raster to maps or coordinates, and relative, which aligns raster to other geo-referenced raster. The document outlines the geo-referencing process, including selecting ground control points, performing transformations, and interpreting error metrics to evaluate accuracy.

1. Introduction to Geo-
Referencing
Prof. Dr. Sajid Rashid Ahmad
sajidpu@yahoo.com
Atiqa Ijaz Khan _ Demonstrator
atiqa_ss09@yahoo.com

2. Basics of Raster Data
• Raster data is commonly obtained by scanning maps or collecting aerial
photographs and satellite images.
• Scanned map datasets don't normally contain spatial reference information (either
embedded in the file or as a separate file).
• With aerial photography and satellite imagery, sometimes the location information
delivered with them is inadequate, and the data does not align properly with other data
you have.
• Thus, to use some raster datasets in conjunction with your other spatial data, you
may need to align or georeference them to a map coordinate system.
• A map coordinate system is defined using a map projection (a method by which the
curved surface of the earth is portrayed on a flat surface).
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Upper Left:
Topographic Sheet of India
and Pakistan
Upper Right: Satellite
Image
Lower Right:
Aerial Photography

4. Geo-Referencing
• “Georeferencing is the process of aligning the raster dataset, with the help of
real world coordinates, to its actual position on the earth (globe)” (ESRI).
• Georeferencing is refers to the process of assigning map coordinates to image
data.
• Georeferencing means to define its existence in the physical space.
• “Rectification is also known as Geo-Referencing” (Swan, 1988).
• “The alignment of an image to a map so that the image is planimetric , just like the
map” (Jensen, 2004).
• “The process by which the geometry of an image is made planimetric” (Jensen,
1986)
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Geo-Referenced Map of Pakistan

6. Why Geo-Referencing?
• When data from different source is to be combined in GIS analysis, it is required
to align them properly with the help of geo-referencing.
• As the raster is made up of pixels, it does not store any information regarding
location, so we cant use it into real world location until it is geo-referenced.
• To calculate the exact area or extent of a raster dataset.
• Satellite images inherent some un-systematic errors making its location shifted to
the original xy-location.
• Georeferencing is the process of aligning the geographic dataset, to a known
coordinate system so it can be viewed, queried, and analysed with other
geographic data.
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7. Types of Geo-Referencing
• Geo-Referencing is divided into two further types, like:
• Absolute Geo-Referencing
• Relative Geo-Referencing
• Absolute Geo-Referencing(Image to Map Rectification):
• The raster image is geo-referenced using:
• Google Earth
• Topo-Sheets
• Ground Control Points (GCPs)
• Relative Geo-Referencing (Image to Image Registration):
• The raster image is geo-referenced using another already referenced image.
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8. Image to Image Rectification
• It is a process in which geometry of an image is made planimetric.
• It is used in order to accurately measure the area, direction and distances.
• This process mainly involves: Selecting GCPs from image to map with its counter-
part available on the map.
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9. Image to Image Registration
• It is a process in which two images of like geometry and same geographical
location are positioned in a way that it coincides with each other.
• It involves translational and rotational alignment.
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10. Aligning Raster using Control Points
• Control Points (CPs):
• Could be defined as a point on the surface of the earth of known location (i.e.
fixed within an established co-ordinate system) which is used to geo-reference
image data sources, such as remotely sensed images or scanned maps.
• It will help in shifting the raster datasets from its original location to spatially
corrected location.
• One control point from a raster dataset associates with one and only CP from the
target map that is a geo-referenced raster or vector data.
• The connection between these points is said to be a ‘Link’.
• Complexity of the image defines how many number of links are to be create.
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CPs Control
Points

12. • It is not necessary, the large number of links always produces better registration.
• Typically, try to link one corner point and few at the interior to have best results.
• Generally, greater the overlap between the raster and target data, the more the
data is accurately registered.
• It is not a good practice to establish control point only at one edge of an image.
• It should be well distributed overall the image.
• The quality of image registration is only up-to the limit to which is it registered.
• To get the good results, one must geo-referenced the image to the highest
possible resolution available.
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13. Raster Transformation
• Geo-referencing involves transformation of raster so to establish a strong control.
• It involves different techniques:
• Shift (Zero Order)
• Affine (1st Order)
• 2nd Order
• 3rd Order
• Spline
• Adjust
• Project Transformation
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14. Zero Order (Shift)
• A zero-order polynomial is used to shift your data.
• This is commonly used when your data is already georeferenced, but a small shift
will better line up your data.
• Only one link is required to perform a zero-order polynomial shift.
• It may be a good idea to create a few links, then choose the one that looks the
most accurate.
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15. 1st Order (Affine)
• The first-order polynomial transformation is commonly used to georeference an
image.
• Use a first-order or affine transformation to shift, scale, and rotate a raster
dataset.
• This generally results in straight lines on the raster dataset mapped as straight
lines in the warped raster dataset.
• Thus, squares and rectangles on the raster dataset are commonly changed into
parallelograms of arbitrary scaling and angle orientation.
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17. Polynomial Order
• With a minimum of three links, the mathematical equation used with a first-
order transformation can exactly map each raster point to the target
location.
• Any more than three links introduces errors, or residuals, that are distributed
throughout all the links.
• However, you should add more than three links, because if one link is positionally
wrong, it has a much greater impact on the transformation.
• Thus, even though the mathematical transformation error may increase as you
create more links, the overall accuracy of the transformation will increase as well
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The number of the non correlated control points required for this method must
be:
• 1 for a zero-order shift,
• 3 for a first order affine,
• 6 for a second order, and
• 10 for a third order.
The lower order polynomials tend to give a random type error, while the higher
order polynomials tend to give an extrapolation error.

19. High Order Transformation
• The higher the transformation order, the more complex the distortion that can be
corrected.
• However, transformations higher than third order are rarely needed.
• Higher-order transformations require more links and, thus, will involve
progressively more processing time.
• In general, if your raster dataset needs to be stretched, scaled, and rotated, use a
first-order transformation.
• If, however, the raster dataset must be bent or curved, use a second- or third-
order transformation.
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21. Spline
• The spline transformation is a true rubber sheeting method and optimizes for
local accuracy but not global accuracy.
• Spline transforms the source control points exactly to target control points.
• The pixels that are a distance from the control points are not guaranteed to be
accurate.
• This transformation is useful when the control points are important, and it is
required that they be registered precisely.
• Adding more control points can increase overall accuracy of the spline
transformation.
• Spline requires a minimum of 10 control points.
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22. Interpreting the Root Mean Square
• When the general formula is derived and applied to the control point, a measure
of the error — the residual error — is returned.
• Residual Error: The error is the difference between where the from point ended
up as opposed to the actual location that was specified—the to point position.
• The total error is computed by taking the root mean square (RMS) sum of all the
residuals to compute the RMS error.
• This value describes how consistent the transformation is between the different
control points (links).
• When the error is particularly large, you can remove and add control points to
adjust the error.
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23. RMS Error
• Although the RMS error is a good assessment of the transformation's accuracy,
don't confuse a low RMS error with an accurate registration.
• As the larger the number of control points, the more accurately polynomial
transforms, and give low RMS value.
• Typically, the adjust and spline transformations give an RMS of nearly zero or
zero; however, this does not mean that the image will be perfectly georeferenced.
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24. Residual
• All residuals closer to zero are considered more accurate.
• The other types of residual are:
• Forward:
• The forward residual shows you the error in the same units as the data frame spatial
reference.
• Inverse:
• The inverse residual shows you the error in the pixels units.
• Forward-Inverse:
• The forward-inverse residual is a measure of how close your accuracy is, measured in
pixels.
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