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Program is Subject to Change

Tuesday, June 15
Tue, Jun 15, 9:30 AM - 11:00 AM
TBD
More Data, Geography, and Reduce Burden? Approaches to Improve Measurement of Goods Movements in the United States

Development of Commodity Flow Data on CFS Sub-Area (307983)

*Olivia Brozek, U.S. Census Bureau 

Keywords: transportation, commodity flow, freight, disaggregation, network dataset

The freight transportation community relies heavily on U.S. DOT data and tools. The large number and broad dispersion of jurisdictions in the United States create a need for nationwide products. Furthermore, to fulfill the requirements of the latest Federal funding legislation, state DOTs and local governments need these data and tools to develop state Freight Plans, Critical Urban Freight Corridors, and Critical Rural Freight Corridors.

One of the top requests of U.S. DOT freight data programs is for more geographic detail, and states and local planners often rely on data disaggregated from Commodity Flow Survey (CFS) geographies. Based on an evaluation of variability, it may be possible to generate more granular data than is currently published. However, doing so will involve gaining those details in exchange for less detail in other data dimensions.

A substantial amount of data can be directly estimated because the leading destinations are almost always nearby the origins. As a result, instead of having only data for overall flows within a single large metropolitan area, we would be able to estimate an n x n matrix, with potentially dozens of intraregional flows. Long distance flows are more challenging, as underlying inputs grow increasingly sparse with distance. However, should one not need highly detailed route information, then it may be feasible to mimic the long-distance flows in a way that generates origin-destination volumes.

The U.S. DOT itself would benefit from having better inputs for its Freight Analysis Framework (FAF) highway network routing model, and those benefits would continue downstream. States and local planners will be better able to understand local and pass-through commodity flows, pinpoint congestion and capacity problems, and identify needed improvements.