What are some common sources of error or distortion when georeferencing an image?

1 Human error

One of the most common sources of error when georeferencing an image is human error. This can include choosing inappropriate or inaccurate control points, entering wrong coordinates, misreading scales or units, or applying incorrect transformation methods. To avoid human error, you should follow some best practices, such as using consistent and clear naming conventions, checking your data sources and metadata, selecting well-distributed and identifiable control points, and verifying your results with other data sets or visual inspection.

2 Image quality

Another source of error when georeferencing an image is the quality of the image itself. Poor image quality can result from low resolution, blurriness, noise, distortion, or degradation. These factors can make it difficult to identify and match control points, or to see the details and features of the image. To improve image quality, you can try to obtain a higher-resolution or newer version of the image, use image enhancement tools, or apply filters or masks to reduce noise or distortion.

3 Projection and datum

A third source of error when georeferencing an image is the projection and datum of the image and the target coordinate system. A projection is a method of representing the curved surface of the earth on a flat map, and a datum is a reference frame for defining the location and shape of the earth. Different projections and datums can introduce distortion, scale, or offset errors when georeferencing an image. To avoid these errors, you should use the same projection and datum for both the image and the target coordinate system, or apply a suitable transformation to convert between them.

4 Spatial extent and resolution

A fourth source of error when georeferencing an image is the spatial extent and resolution of the image and the target coordinate system. Spatial extent is the area covered by the image, and resolution is the level of detail or pixel size of the image. If the spatial extent or resolution of the image and the target coordinate system are too different, it can cause mismatch, overlap, or gaps when georeferencing an image. To minimize these errors, you should use an image and a target coordinate system that have similar spatial extent and resolution, or resample or clip the image to match the target coordinate system.

5 Temporal variation

A fifth source of error when georeferencing an image is the temporal variation of the image and the target coordinate system. Temporal variation is the change of spatial features or phenomena over time, such as land use, vegetation, urbanization, or erosion. If the image and the target coordinate system are from different time periods, it can cause inconsistency, discrepancy, or displacement when georeferencing an image. To reduce these errors, you should use an image and a target coordinate system that are from the same or close time period, or account for the temporal variation by using historical data or models.

6 Geometric transformation

A sixth source of error when georeferencing an image is the geometric transformation that is applied to the image to align it with the target coordinate system. A geometric transformation is a mathematical function that adjusts the position, orientation, shape, and size of the image based on the control points. There are different types of geometric transformations, such as affine, polynomial, or spline, that have different levels of complexity and accuracy. Choosing an inappropriate or inaccurate geometric transformation can cause distortion, error, or loss of information when georeferencing an image. To avoid these errors, you should choose a geometric transformation that suits the type and number of control points, the projection and datum, and the spatial extent and resolution of the image and the target coordinate system.