Local Detection of Three-Dimensional Systematic Errors in Satellite DSMs: Case Studies of SRTM and ASTER in Lombardy

In this paper we present a method for detecting three-dimensional systematic errors of Digital Surface Models (DSMs) derived from satellite data. The detection process is realized via a three-dimensional comparison with reference altimetric models of better accuracy, by a matching process based on a 3D geospatial transformation without scale factor correction. The matching process of the two altimetric models is based on the estimation of the six parameters of a geospatial transformation between two 3D surfaces, minimizing the Euclidean distances between the surfaces by least squares method; this procedure does not require the a priori availability of homologous points. The method is applied on comparison of GPS surveys over Lombardy Region of Northern Italy, with SRTM (3 arc sec) and ASTER (1 arc sec) DSMs in the same region; tests of statistical significance are performed confirming, in the latter case, the existing 3D systematic error.