  As both simulations and observations reach the resolution of the star-forming
molecular clouds, it becomes important to clarify if these two techniques are
discussing the same objects in galaxies. We compare clouds formed in a high
resolution galaxy simulation identified as continuous structures within a
contour, in the simulator's position-position-position (PPP) co-ordinate space
and the observer's position-position-velocity space (PPV). Results indicate
that the properties of the cloud populations are similar in both methods and up
to 70% of clouds have a single counterpart in the opposite data structure.
Comparing individual clouds in a one-to-one match reveals a scatter in
properties mostly within a factor of two. However, the small variations in
mass, radius and velocity dispersion produce significant differences in derived
quantities such as the virial parameter. This makes it difficult to determine
if a structure is truely gravitationally bound. The three cloud types
originally found in the simulation in Fujimoto et al. (2014) are identified in
both data sets, with around 80% of the clouds retaining their type between
identification methods. We also compared our results when using a peak
decomposition method to identify clouds in both PPP and PPV space. The number
of clouds increased with this technique, but the overall cloud properties
remained similar. However, the more crowded environment lowered the ability to
match clouds between techniques to 40%. The three cloud types also became
harder to separate, especially in the PPV data set. The method used for cloud
identification therefore plays a critical role in determining cloud properties,
but both PPP and PPV can potentially identify the same structures.
