When precise ground coordinates for control points are not available, existing vector layers such as roads, buildings, or trees can be used to support the georeferencing process. These layers provide identifiable features that are present both in the raster image and the vector data.
For instance, an image can be georeferenced by aligning road intersections from the image with those in a road vector layer. These intersections are then marked as control points to establish spatial reference.
Identifying common points in an image and a vector layer.
To carry out the georeferencing process, a new map must first be created. Then, the vector layer named routes2.shp and the raster image image2.png—located in the folder 06_georeference\no_coordinates—must be added to the map.
After adding these layers, select the raster image and activate the georeferencing tool. The coordinate system for the image must then be defined by following the appropriate steps outlined previously.
To better visualize the data, right-click on the routes2.shp layer and select “Zoom To Layer”. Then, choose the image in the “Contents” panel and go to the “Georeference” tab. In the “Prepare” group, click on “Fit To Display” to overlay the vector layer onto the raster image.
To begin placing control points, navigate to the “Adjust” group within the “Georeference” tab and select “Add Control Points”. The mouse pointer will display the message “From point (source)”, indicating the user should mark a point on the raster image first. For example, a traffic circle may be selected as a source point.
Next, click on the corresponding location in the vector layer, marking the “To point (target)”. This process should be repeated for each control point until the two layers are properly aligned. The image is adjusted automatically after each pair of control points is established.
Entering control points for georeferencing using a vector layer.
The number of control points alone does not determine the accuracy of georeferencing. Instead, it is more important to ensure an even spatial distribution across the entire image. This helps achieve a more uniform and accurate transformation.
Using too many control points may lead to complex transformations that increase potential residual errors. Common transformation methods include polynomial, spline, and projective adjustments, which refine the coordinate mapping for each pixel in the raster image.
Distribution of control points.
The accuracy of the georeferencing process can be assessed by reviewing the “Control Point Table”, accessible from the “Georeference” tab under the “Review” group. This table displays residual errors that indicate how precisely the control points match between the image and the vector layer.
Lower residual errors reflect higher georeferencing quality. In rural cadastral applications, an error of up to three meters may be acceptable. For urban cadastral work, stricter standards may apply, often requiring errors no greater than 25 centimeters. These thresholds depend on the specific requirements of the project or applicable regulations.
Control points table in georeferencing.
It is generally discouraged to use imagery from “Google Earth” for technical georeferencing tasks. These images often include topographic distortions and may lack the precision needed for spatial accuracy. Furthermore, the resolution may not always be sufficient for detailed work. These images are best used as visual references rather than as primary data sources.
There is no fixed number of control points required for effective georeferencing. Some situations may require only a few, while others might necessitate dozens. The key factor is precision in selecting points that are well-distributed and accurately placed.
The number of required points also depends on the quality of the raster image. If the image is well-scanned and free from physical distortions, fewer points may be needed. However, if the image contains wrinkles or deformations, additional points will help correct for these imperfections through transformation adjustments.
Ultimately, the quality and condition of the source data significantly influence the georeferencing process and determine the number and placement of control points necessary to achieve accurate spatial alignment.