A self-organizing method for map reconstruction

A variety of problems in geographical and satellite-based remote sensing signal processing, and in the area of "zero-error" pattern recognition dealing with processing the information contained in the distances between the points in the geographical or feature space. In this paper we consider one such problem, namely, that of reconstructing the points in the geographical or feature space, when we are only given the approximate distances between the points themselves. In particular, we are interested in the problem of reconstructing a map when the given data is the set of intercity road travel distances. Reported solution approaches primarily involve multi-dimensional scaling techniques. However, we propose a self-organizing method. The new method is tested and compared with the classical multi-dimensional scaling and ALSCAL on different data sets obtained from various countries.