Fig. 3
From: Multi-modal and multi-layer robustness analysis of the European rail and air networks
Distribution of mean node dependency degree \({\bar{w}_i}\) for the European rail network in geographical (left) and histogram (right) plots. Mean node dependency degree is an absolute value representing how many nodes are on average becoming disconnected from the network’s largest connected component when a given node is removed. Light nodes have \({\bar{w}_i}\) close to unity, indicating that the failure of these nodes does not lead to the isolation of additional nodes. Blue nodes have a mean dependency degree below unity, meaning that they are likely to be disconnected from the network’s largest connected component following the removal of another node (referred to as dependent nodes). Conversely, red nodes are those that likely disconnect other nodes from the network’s largest connected component (referred to as connecting nodes). The histogram reports the percent distribution and the cumulative distribution. Almost 60% of network nodes have a \({\bar{w}_i}\) lower than unity, and the 90th percentile equals 1.8. (Map is created using Matplotlib and Basemap https://matplotlib.org/basemap/stable/).
