  In this paper we present an empirical study of the worldwide maritime
transportation network (WMN) in which the nodes are ports and links are
container liners connecting the ports. Using the different representation of
network topology namely the space $L$ and $P$, we study the statistical
properties of WMN including degree distribution, degree correlations, weight
distribution, strength distribution, average shortest path length, line length
distribution and centrality measures. We find that WMN is a small-world network
with power law behavior. Important nodes are identified based on different
centrality measures. Through analyzing weighted cluster coefficient and
weighted average nearest neighbors degree, we reveal the hierarchy structure
and "rich-club" phenomenon in the network.
