Multisensor data fusion for spaceborne and airborne reduction of mine suspected areas

The problem of mined area reduction is addressed in this paper. Pieces of information collected using airborne multispectral scanners and airborne full polarimetric SAR, together with context information, all integrated in a geographical information system, are classified and combined in order to find indicators of mine presence and mine absence and provide image analysts with adequate tools to interpret mined scenes during the area reduction process. The paper contains a broad description of the whole problem and of the developed method and focuses on classification and data fusion tools based on the belief function framework and fuzzy sets theory.