Cooperative Algorithms and Techniques of Image Analysis and Gis

During the past data fusion has become an important issue in remote sensing image analysis. Image analysts benefit very much from fusion products, e.g. merged optical and radar imagery, which provide a more complete view of the imaged scene. Enhancement of the local texture of multispectral imagery by fusion with panchromatic images is another example which leads to an improvement of classification accuracy and visual interpretability. In photogrammetry sensor and data fusion and recently the more general task of information fusion gain more and more attention. Improvements with regard to the algorithmic complexity and the quality of 3D reconstructed objects are demonstrated, for example, in combining airborne laser data and aerial images for building reconstruction. From the GIS field existing maps or object data bases which carry information about objects in various forms are contributed which also have to be taken into account within information fusion. And all three disciplines are dealing with modeling and the development of strategies and algorithms to solve a variety of problems in so far heterogeneous fields and applications. In this paper we intend to give an overview about information fusion in the interrelated fields of photogrammetry, remote sensing and GIS. In particular, we summarise papers and other activities of members of ISPRS ICWG IV/III.2 with the idea to structure these efforts giving state of the art.