Transport network backbone extraction: A comparison of techniques

Network backbone extraction techniques reduce the size of networks while trying to preserve their key topological and spatial features. Various backbone extraction algorithms have been proposed in different scientific fields. Although of clear interest to transport geographers, backbone extraction techniques have been adopted unevenly and in an ad hoc fashion in transport geography research. In this paper we therefore present a conceptual and experimental comparison of backbone extraction techniques in a transport-geographical context, and explore the new insights each technique can offer to enhance our understanding of the Southeast Asian intercity air transport network (SAAN). We review six frequently-used methods, i.e. global weight thresholding method (GWTM), k-core decomposition method (KCDM), minimum spanning tree method (MSTM), primary linkage analysis method (PLAM), multiple linkage analysis method (MLAM), and the disparity filter algorithm method (DFAM), and elaborate their analytical essence by applying them to extract the backbone of the SAAN. The abstracted networks are compared in terms of their geographical and topological structures using the initial network as a benchmark. This comparison is then used to point out the different techniques' potential in light of different transport geography research applications.