Quality control must take place at every step in the processing, so that errors can be addressed before further time and effort is invested. With the availability of GIS software and robust computer processing, evaluating the quality of the postprocessed data sets has become relatively straightforward. One method for assessing the relative calibration is to create TIN models of the flight lines with their overlap, and visually compare the overlap from a vertical view or in profile view; mismatches indicate possible data problems. Also, this method will visually display any shifts or scaling errors. In some cases, creating contours from lidar data will aid in distinguishing mismatches or noise points – points that are either too high (spikes) or too low (wells) – from the true bare earth surface.
Some projects require a statistical analysis of the bare earth terrain model, and development of an absolute accuracy assessment. In this case, ground control points are surveyed, and the x, y, z values of the points are compared to interpolated x, y, z points from the lidar digital surface model (DSM). Depending on the accuracy established for the project, a report defining the accuracy of the lidar against the ground survey may be expressed.