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Combining super-resolution techniques can increase the accuracy with which the shape of objects may be characterised from imagery. This is illustrated with two approaches to combining the contouring and pixel swapping methods of super-resolution mapping for binary classification applications. In both approaches, the output of the pixel swapping method is softened to allow a contour of equal class membership to be fitted to it to represent the inter-class boundary. The accuracy of super-resolution mapping with the individual and combined techniques is explored, including an assessment of the effect of variation in the number of neighbors and zoom factor on pixel swapping based analyses. When combined, the error with which objects of varying shape were represented was typically greatly reduced relative to that observed from the application of the methods individually. For example, the root mean square error in mapping the boundary of an aeroplane represented in relatively fine spatial resolution imagery decreased from 14.41 m with contouring and 4.35 m with pixel swapping to 3.07 m when the approaches were combined.