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In the context of global change, alteration of landscapes and loss of biodiversity, the monitoring of habitats, vegetation types and their changes have become extraordinary important. In this paper, first results from a study that analyses the differentiability of NATURA2000 habitats and HNV grassland with imaging radar data are presented. Therefore, Kennaugh elements derived from TerraSAR-X and Radarsat-2 dual pol (VV/VH) time series data are used, both separately and in combination, to model the distribution of these classes with the Maximum-Entropy principle. The preliminary results show that the multi-frequency approach enables - compared to single frequency analyses - a finer differentiation between scatterers in the size of 3–6 cm (e.g. 7120, 7230 and HNV grassland).

A rapid visualisation of change in urban crisis areas is an important condition for planning and coordination of help. For automated change detection, a large number of algorithms has been proposed and developed. This paper describes the results of a colour and texture based change detection approach that was applied to satellite and aircraft images of the earthquake region in Haiti. In our integrated methodology, we calculate firstly new colour texture images which are based on the feature ‘energy’. This is performed for every channel in the visible colour spectrum at two different times after a radiometric harmonisation. Combined with a principal component analysis for each texture image and a subsequent histogram optimisation, we subtract the texture elements to visualise the occurred change. As result, it is not only possible to automatically delineate areas of change but also to distinguish between different types of change.

This paper discusses the fusion of multi-spectral and panchromatic remote sensing images. A multi-wavelet transform based fusion method is presented after analyzing the basic principles of remote sensing imaging systems and the rational for image fusion. The simulation results show that the multi-wavelet transform based fusion method is superior to the ordinary wavelet transform based fusion method. The fused image provides more spatial and spectral information.

In a geographic information system (GIS) an object is generally defined by two aspects, positional and thematic values. It is possible to have error indicators to describe the positional accuracy and to describe thematic accuracy. However, ther is not a well developed theory to derive a combined uncertainty indicator for a GIS object. the authors present a strategy for such a combined error model, the "S-BAND" uncertainty model. This model is based on a combined uncertainty indicator with both positional and thematic aspects. >