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Massive sulphide deposits in the Neoproterozoic Arabian-Nubian Shield are exposed at the surface as Fe-rich crusts termed gossans. Gossans are typically a few tens of metres across but are surrounded by wider clay- and Fe-rich alteration zones. Although Fe-rich gossans have characteristic reflectance spectra and surface: roughness, they are often too small to be directly detected by Landsat TM or SIR-C images, both of which have about 30 m spatial resolution. In this paper, a procedure is described whereby gossans and the surrounding alteration zones can be identified and mapped by Landsat TM and SIR-C data using the Beddaho Alteration Zone and the Tebih Gossan in northern Eritrea as an example. Clay and Fe alteration index maps were generated by density slicing for Landsat TM band-ratios 5/7 and 3/1, respectively. Landsat 5/7-4/5-3/1 TM images characteristically depict small (tens of pixels) gossans in blue and the more extensive alteration zones in pinkish purple. Chh-Lhh-Lhh/Chh SIR-C images succeeded in identifying the gossan due to enhanced back-scattering of the radar shorter wavelength (6 cm) C-band by the rough gossan surfaces. This enhanced back-scattering might also be partially due to the characteristic dielectric property of the Fe-rich minerals forming the gossans. Choosing known gossans from both 5/7-4/5-3/1 Landsat TM and Chh-Lhh-Lhh/Chh SIR-C images as training sites for supervised classification helped to outline areas with reflectance spectra and radar back-scattering properties similar to those of the training sites. These results show significant correlation between supervised classifications based on the two data sets, suggesting a way to use combined visible and near infrared (VNIR) and radar imagery to explore for mineral deposits in arid regions. (C) 2000 Elsevier Science Limited. All rights reserved.