Motivated by the empirical analysis of the air transportation system, we
define a network model that includes geographical attributes along with
topological and weight (traffic) properties. The introduction of geographical
attributes is made by constraining the network in real space. Interestingly,
the inclusion of geometrical features induces non-trivial correlations between
the weights, the connectivity pattern and the actual spatial distances of
vertices. The model also recovers the emergence of anomalous fluctuations in
the betweenness-degree correlation function as first observed by Guimer\`a and
Amaral [Eur. Phys. J. B {\bf 38}, 381 (2004)]. The presented results suggest
that the interplay between weight dynamics and spatial constraints is a key
ingredient in order to understand the formation of real-world weighted
networks
