Complement of incomplete spatial information via RBF network

Incomplete information" and its complement are encountered frequently in geo-information processing. It is of great significance to interpolate the lost data via the known historic datasets and improve the quality and accomplishment of information integration. The RBF network possesses the advantages of Kohonen and regression networks. A test was performed to prove the effectiveness of RBF to complement the incomplete spatial information.