A Sustainability Perspective on the Distribution Characteristics and Driving Mechanisms of Border Towns: A Case Study of the Inner Mongolia Segment of China’s Northern Border

As a pivotal hub for the northward advancement of the Belt and Road Initiative and a strategic outpost for national security, the spatial patterns of towns in the border regions of northern Inner Mongolia exert a direct impact on the region’s sustainable development and long-term prosperity. This study focuses on 141 border towns situated along the Inner Mongolia stretch of China’s northern border. By leveraging analytical tools including kernel density analysis, standard deviation ellipse method, and nearest neighbor index analysis, it explores the distinctive characteristics of their spatial distribution. Furthermore, this study applies the Geodetector method to quantify the explanatory power of key influencing factors on the spatial differentiation of these border towns. The findings can be summarized as follows: (1) The border towns along the Inner Mongolia stretch of the northern border displayed a distinct heterogeneous distribution gradient characterized by prominent regional agglomeration and formed a three-tier spatial hierarchy. Specifically, the Bayannur–Hetao Plain Town Cluster served as the primary agglomeration core, supplemented by two secondary clusters, namely the Xing’an League–Southern Greater Khingan Range Town Cluster and the Hulunbuir–Border Port Town Cluster. In contrast, the Alxa League constituted a low-density peripheral belt with sparse town distribution. (2) Factor analysis via Geodetector revealed that the spatial distribution pattern of these border towns was primarily driven by the core mechanism of port-led urbanization. This core driver was synergistically reinforced by secondary factors such as mineral resource endowments, jointly shaping a complex spatial layout that partially transcended natural geographical constraints—a stark contrast to coastal ports, where development is dominated by innate natural geographic advantages.