Airborne hyperspectral scanning involves the mapping of a scene’s wavelength intensity, accomplished by measuring upwelling electromagnetic radiation (reflected and/or emitted) in a multitude of contiguous narrow spectral bands. The end product consists of spatially co-registered two-dimensional images, each of them representing a spectral band that is typically just about ten nanometres wide. In this sense, imaging spectroscopy yields a three-dimensional data cube (x, y, λ) in which the first two are the spatial dimensions, whereas the third axis contains a spectral dimension: a digital number (DN) that represents the sampled and quantized at-sensor radiance L for that particular waveband. In post-processing, reflectance (or emissive characteristics) can be calculated from these DNs. Through a combination of all spectral data acquired from a particular spatial location, every individual pixel of the final image holds the complete reflectance or emission spectrum (known as spectral signature) of the material that was sampled at that specific location. Since this spectral signature can be obtained for every pixel in the image, the technique is also called airborne imaging spectroscopy (AIS). AIS has occupied only a small niche in the field of remote sensing during the last decades. Even to this very date, its application in archaeological research is limited and most results are not entirely convincing for practical applications. Next to the common, archaeologically-insufficient ground-sampling distance of 2-3 m, the technical processing of these data does typically not surpass the calculation of band ratios and a principal component analysis. In this contribution, it is the aim to present the analysis of several archaeologically-relevant hyperspectral datasets acquired in different seasons above the Roman town of Carnuntum (Austria). It will be shown how a newly developed MATLAB toolbox was used to extract important archaeological information from these hyperspectral pixels. To this end, a variety of approaches that are not commonly applied in archaeological remote sensing research are tested and validated. Finally, a comparison with simultaneously acquired oblique and vertical photographs will indicate the specific advantages of high-resolution AIS data.