Hyperspectral imaging is one of the most sophisticated data acquisition methods in the field of remote sensing regarding the data processing. Especially when very high spatial and spectral resolution is needed a careful handling of all the data quality influencing parameter has to be ensured. Nevertheless, the following interpretation process determines considerably the previous data processing: classification by using spectral libraries or ground samples require radiometric corrected images as well as multi-temporal data. Other classification methods might be insensitive to earth surface parameters such as spectral albedo and directional reflectance quantities which makes the processing routine slightly easier. New advances in sensor technology allows to now acquire dataset with a ground sampling distance of 25 cm or better within the full spectral range. To cope with the increasing amount and redundancy of data new approaches for data processing have to be developed. The contribution deal with selected aspects of data processing chain for airborne imaging spectroscopy data.


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