Abstract
Applications such as landscape planning, environmental monitoring, and flight and driving simulators have a high demand for realistic landscape models. Quantity, precision and the type of models ask for methods which automate the model generation by evaluation of remote sensing data. The presented modelling system AIDA tackles the demand for efficient representation and high realism by integrating a priori knowledge about the appearance of the objects in the scene to drive object specific constraints for 3D reconstruction. This requires an image interpretation to assign a meaning to the objects in the scene. For explicit representation of the declarative and procedural knowledge a problem independent formalism based on semantic nets and rules is used. It provides both a data driven and model driven control strategy.

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