Abstract To estimate impacts, support cost–benefit analyses, and enable project prioritization, it is necessary to identify the area of influence of a transportation infrastructure project. For freight related projects, like ports, state-of-the-practice methods to estimate such areas ignore complex interactions among multimodal supply chains and can be improved by examining the multimodal trips made to and from the facility. While travel demand models estimate multimodal trips, they may not contain robust depictions of water and rail, and do not provide direct observation. Project-specific data including local traffic counts and surveys can be expensive and subjective. This work develops a systematic, objective methodology to identify multimodal “freight-shed” (or “catchment” areas) for a facility from vehicle tracking data and demonstrates application with a case study involving diverse freight port terminals. Observed truck Global Positioning System and maritime Automatic Identification System data are subjected to robust pre-processing algorithms to handle noise, cluster stops, assign data points to the network (map-matching), and address spatial and temporal conflation. The method is applied to 43 port terminals on the Arkansas River to estimate vehicle miles and hours travelled, origin, destination, and pass-through zones, and areas of modal overlap within the catchment areas. Case studies show that the state-of-the-practice 100-mile diameter influence areas include between 15 and 34% of the multimodal freight-shed areas mined from vehicle tracking data, demonstrating that adoption of an arbitrary radial area for different ports would lead to inaccurate estimates of project benefits.