  The definition of complexity through Statistical Complexity Measures (SCM)
has recently seen major improvements. Mostly, effort is concentrated in
measures on time series. We propose a SCM definition for spatial dynamical
systems. Our definition is in line with the trend to combine entropy with
measures of structure (such as disequilibrium). We study the behaviour of our
definition against the vectorial noise model of Collective Motion. From a
global perspective, we show how our SCM is minimal at both the microscale and
macroscale, while it reaches a maximum at the ranges that define the mesoscale
in this model. From a local perspective, the SCM is minimum both in highly
ordered and chaotic areas, while it reaches a maximum at the edges between such
areas. These characteristics suggest this is a good candidate for detecting the
mesoscale of arbitrary dynamical systems as well as regions where the
complexity is maximal in such systems.
