Probabilistic and Evidential Approaches for Multisource Data Analysis

Two methods for combining the information contents from multiple sources of remote-sensing image data and spatial data in general are described. One is a probabilistic scheme that employs a global membership function (similar to a joint posterior probability) that is derived from all available data sources. The other is an evidential calculus based upon Dempster´s orthogonal sum combination rule. A feature of both methods is that uncertainty regarding data analysis can be incorporated into the process. Both schemes are evaluated in terms of their general applicability and certain equivalences are noted. Moreover, both are shown to perform well on mixed multispectral data.