Product bilateral trade features can be organized and expressed in the Cartesian coordinate system by taking imports and exports as X and Y, which is similar to spatial visualization. Hence, geospatial expression and analysis methodologies can be applied in bilateral trade studies. In this paper, we propose a new digital trade feature map (DTFM) method for the visualization of bilateral trade features from a spatial perspective. The implementation process of DTFM can be summarized as feature extraction, visualization, and analysis. China–US bilateral trade data were used in several case studies. As the case studies show, the DTFM has the advantages of clear expression, easy operationalization and is highly extensible. Moreover, this method can provide a broader perspective for the understanding of trade features, i.e., in comprehensively considering the features of a specific product type and its neighbors. Furthermore, we propose an extensible DTFM application framework into which different trade features, different grid generation modes, and numerous spatial analysis models can be readily integrated.

The new wave of modern rail transit and the proposal of the Belt and Road Initiative (BRI) have complicated the business patterns of the rolling stock manufacturing industry (RSMI) and the export of rolling stock products, especially in the case of countries participating in the BRI. Based on the analysis of trade patterns—which focuses on the evolution of trade links, community structures, and intraregional export competitiveness—this study aims to explore the changes in the RSMI within the BRI region from 2003 to 2017. Sequential clustering was applied to the creation of a three-phase timeline. The network models of the cumulative trade of the rolling stock products and trades of two typical categories of products were constructed in each phase for the evolution analysis. Social network analysis methods, such as the analysis of network indices and community detection, were also applied. The results show that from 2003 to 2017, the connectivity of the rolling stock trade in this region significantly increased. China was the largest exporter, with increasing trade influence and technological strength. Ukraine and Russia were less competitive and highly mutually dependent. Czechia and Austria’s competitiveness remained prominent, but compared with China they lacked expansive vitality. South Korea was also an active and competitive country with strong technological prowess. These countries accounted for the majority of the exports, and were always at the center of their own separate communities, over which they maintained a sphere of influence. The grouping of countries far from any such spheres of influence changed frequently.