Effect of the sampling design of ground control points on the geometric correction of remotely sensed imagery

The acquirement of ground control points (GCPs) is a basic and important step in the geometric correction of remotely sensed imagery. In particular, the spatial distribution of GCPs may affect the accuracy and quality of image correction. In this paper, both a simulation experiment and actual-image analyses are carried out to investigate the effect of the sampling design for selecting GCPs on the geometric correction of remotely sensed imagery. Sampling designs compared are simple random sampling, spatial coverage sampling, and universal kriging model-based sampling. The experiments indicate that the sampling design of GCPs strongly affects the accuracy of the geometric correction. The universal kriging model-based sampling design considers the spatial autocovariance of regression residuals and yields the most accurate correction. This method is highly recommended as a new GCPs sampling design method for geometric correction of remotely sensed imagery.

► The distribution of GCPs may influence the accuracy and quality of image correction.
► Simple random sampling, spatial coverage sampling, and universal kriging model-based sampling are adopted for the GCP configuration.
► It has been demonstrated that the spatial pattern of GCPs greatly affects the accuracy of image geometric correction.
► The universal kriging model-based sampling yields the most accurate geometric correction.