The infrared sensor system FASA (Fire Airborne Spectral Analyser) operated in a DLR research aircraft is a unique combination of an imager and a Fourier Transform Spectrometer used to detect, analyse and classify fires and volcanoes. In such cases, the scenes in the FTS field of view are generally inhomogeneous and not known a priori, and the data fusion approach of image and spectral data is supposed to overcome the difficulty hereby involved. The analysis of an artificial coal fire has provided us fundamental insights in how to model such fires and potential strategies for data evaluation. First and promising results will be presented. Moreover, the importance of aerosol contributions is examined and the feasibility to retrieve smoke particle parameters in the infrared is demonstrated.