Geometric correction procedures (image-to-map rectification, image-to-image rectification) are used to rectify remotely sensed data to a standard map projection whereby it may be used in conjunction with other spatial information in a GIS to solve problems. The rectification process normally involves selecting ground control point (GCP) image pixel coordinates (row and column) with their map coordinate counterparts (e.g. meters northing and easting in a UTM map projection). Rectification requires that polynomial equations (that translate from image coordinates to map coordinates) be fit to the GCP data using least squares criteria. Depending on the distortion in the imagery, the number of GCPs used, and the degree of topographic reliefdisplacement in the area, higher -order polynomial equations may be required to geometrically correct the data. To determine how well the six coefficients derived from the least-squares registration of the initial GCPs account for geometric distortion in the inpit image, for each GCP, the root-mean-square error (RMSE) is computed.
Understand how root mean squared error (RMSE) at tie points represents local spatial accuracy and enables calculation of total RMSE that informs about the average spatial accuracy of the entire image
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