  Morphologically classifying radio sources in continuum images with the SKA
has the potential to address some of the key questions in cosmology and galaxy
evolution. In particular, we may use different classes of radio sources as
independent tracers of the dark-matter density field, and thus overcome cosmic
variance in measuring large-scale structure, while on the galaxy evolution side
we could measure the mechanical feedback from FRII and FRI jets. This work
makes use of a \texttt{MeqTrees}-based simulations framework to forecast the
ability of the SKA to recover true source morphologies at high redshifts. A
suite of high resolution images containing realistic continuum source
distributions with different morphologies (FRI, FRII, starburst galaxies) is
fed through an SKA Phase 1 simulator, then analysed to determine the
sensitivity limits at which the morphologies can still be distinguished. We
also explore how changing the antenna distribution affects these results.
