Abstract. This study addresses the modelling of synthetic aperture radar (SAR) image texture for sea ice scenes in the Labrador marginal ice zone (MIZ). The image texture of distributed scatterers contains a substantial component relating to the imaging system as well as information about the scene itself. Theory shows that the image autocorrelation function (ACF) may be analysed to separate system contributions from scene contributions under certain conditions. The main theses of the study are: (i) SAR intensity images of sea ice are spatially nonGaussian; and (ii) the predominant types and forms of MIZ sea ice may be discriminated based upon ACF model parameters. Experimental results indicate that the model provides an excellent fit to the measured ACFs. The image texture was found to be a strong function of the form of the sea ice as well as its type. For a given type, the various forms could be discriminated through a single SAR channel. For full discrimination of all types and forms observed, a two-channel combination was necessary: XHV CHH or XHV CHV.