Suitability Assessment and Route Network Planning for Low-Altitude Transportation in Urban Agglomerations Using Multi-Source Data

As low-altitude transportation becomes essential to global integrated transport systems, developing extensive and well-structured networks in urban agglomerations is crucial for fostering regional synergy and enhancing three-dimensional transport. Focusing on the Beijing–Tianjin–Hebei urban agglomeration, this study integrates multi-source data within a three-stage research framework: (1) node suitability assessment, (2) route optimization, and (3) network structure evaluation. It systematically evaluates the suitability of county-level general aviation airports and township-level vertiports. Building on the suitability analysis, a hierarchical route network is constructed using a modified gravity model augmented by spatial correction mechanisms. Finally, spatial syntax analysis, supplemented with equity and robustness assessments, is applied to evaluate network accessibility, topological efficiency, and resilience. The key findings are as follows: (1) The suitability classification identifies 43 Class A, 86 Class B, and 71 Class C general aviation airports, revealing a spatial pattern characterized by higher density in the east, lower density in the west, and a multi-nodal clustering structure. Township-level vertiports markedly increase terminal-node coverage. (2) The optimized hierarchical network includes 114 primary, 180 secondary, and 366 tertiary routes, bridging previous regional connectivity gaps. (3) High values of network integration, choice, spatial intelligibility, and equity-adjusted accessibility indicate robust performance, fairness in service distribution, and resilience under potential disruptions. This study offers a methodological paradigm for the systematic development of low-altitude transport networks and provides valuable references for evidence-based planning of urban agglomeration air mobility systems and the strategic development of regional low-altitude economies.