A method for characterizing scene content from aerial images is presented. The method is demonstrated for a building complex scene for which a three-dimensional data base and corresponding aerial images were available. Intuitively, the complexity of the building scene as viewed in a projected image is proportional to the number of vertices visible in the view. The greater the number of vertices, the greater the complexity of the scene. To automate this approach, one must automatically locate vertices from aerial images of the scene and determine relations among the vertices. Objective measures of scene content should not only basically agree with the intuitive measures, but also possess certain desirable mathematical properties. Two such measures, structural entropy and structural content, which were previously developed, are applied to the building scene, and experimental results which illustrate the variation of these measures with range, azimuth, and elevation are provided. One application of the scene content measures is the prediction of overall scene content characteristics performance support for map matching systems. To illustrate this application, an error analysis is presented of the mean square error in the transformational computation between a three-dimensional scene and the corresponding two-dimensional projected images, given a number of corresponding vertices. The analysis illustrates that the best possible performance depends heavily upon the vertex location accuracy.