Imaging spectroscopy acquires imagery in often more than hundred narrow contiguous spectral bands. This offers unprecedented spectral data for archaeological research. To make full use of this relatively new data source and extract useful archaeological information from it, a number of problems have to be solved. Major problems relate to the visualization of the huge amount of available data and the data redundancy. This makes data mining approaches necessary as well as efficient data visualization tools. Additional problems relate to data quality. Indeed, the upwelling electromagnetic radiation is recorded in small spectral bands that are only about ten nanometers wide. The signal received by the sensor is thus quite low compared to sensor noise and possible atmospheric perturbations. The often small instantaneous field of view (IFOV) – essential for archaeologically relevant imaging spectrometer datasets – further limits the useful signal stemming from the ground. The combination of both effects makes radiometric smoothing techniques mandatory. The presentation details the functionality of a MATLAB∘ledR-based toolbox called ARCTIS (ARChaeological Toolbox for Imaging Spectroscopy), which addresses the above mentioned problems. It helps the image analyst – not necessarily a specialist in remote sensing or in imaging spectroscopy – to maximize the information extracted from the recorded 3D data cube. It is a tool to display hyperspectral data (multilayer TIFF images or ENVI files) in many different ways and to retrieve as many pieces of information as possible from the imagery. As such it was created to test currently available AIS processing practices as well as validate the value of completely new information extraction techniques. Given the fact that many of its residing processing and visualization tools cannot be found elsewhere and commercial software is often costly and less straightforward to use, the toolbox and its source code will be freely available for all interested parties (via download from http://luftbildarchiv.univie.ac.at) under the Creative Commons Attribution 4.0 International License. Together with some test datasets, this open access will enable interested students and remote sensing professionals to become acquainted with AIS, while other scientists can contribute with new algorithms to further expand and even optimize ARCTIS.