| The Farm Services Agency of the United States Department of Agriculture, along with other public and private agencies, records thousands of small scene 35 mm aerial images annually. With georeferencing, these images could be a valuable source of land management information, especially for natural resources. This research began as a funded project to evaluate the efficacy of software developed by Michigan State University's Center for Remote Sensing to rectify the 35 mm images. Evaluation of those rectifications was hampered by the absence of a good measure of image error. Two digital images were selected and georeferenced using global linear transformations of first-, second-, and third-order and local or piecewise linear transformation. These georeferenced images were used for error analysis. Independent check points were tested in each image and error surfaces were generated from those measurements for visualization and analysis of error. In addition, the areas of representative fields were measured for each transformation to test the effect of error on secondary products. It was found, first, that the images contained systematic error, and that any pattern of control points for a global transformation was forced to accommodate that error. It was also found that, even though the images did contain this systematic error, discontinuous transformations with from ten to twenty control points could produce corrected images with root mean squared error less than 15 meters in flat terrain. It was further found, that, with a continuous transformation and as few as three control points, large areas of the corrected image have absolute positional error less than 20 meters. |