  We perform the renormalization-group-like numerical analysis of
geographically embedded complex networks on the two-dimensional square lattice.
At each step of coarsegraining procedure, the four vertices on each $2 \times
2$ square box are merged to a single vertex, resulting in the coarsegrained
system of the smaller sizes. Repetition of the process leads to the observation
that the coarsegraining procedure does not alter the qualitative
characteristics of the original scale-free network, which opens the possibility
of subtracting a smaller network from the original network without destroying
the important structural properties. The implication of the result is also
suggested in the context of the recent study of the human brain functional
network.
