Introduction: The decarbonization of urban transportation is a central pillar of sustainable city development. While hydrogen offers a promising pathway, its integration into urban and regional infrastructure faces significant spatial and safety challenges.

Methods: To address this, we developed a novel geospatial optimization model that designs hydrogen supply chain networks (HSCNs) for clean transportation. The model's key novelty is its grid-based optimization framework, which integrates real pipeline and station data to simultaneously optimize hub locations for both proximity to refueling stations and access to the main pipeline network. Applied to Germany's Hydrogen Core Network (HCN), the model was formulated with distance-minimizing objective functions and solved using a clustering algorithm.

Results and discussion: When applied to Germany's operational stations, the model achieved a 23.4% reduction (2,719.6 km) in total distribution distance within optimized grids, while also capping the longest single delivery route. Furthermore, it introduces a station density threshold to determine the need for decentralized sub-storage facilities. This work provides a scalable decision-support framework for planners and policymakers, facilitating the strategic deployment of hydrogen infrastructure and accelerating its adoption for sustainable urban mobility.