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36 Guidebook for Understanding Urban Goods Movement Exhibit 4-7. Example of integrated data sources for evaluating urban freight networks. Source: Wilbur Smith Associates. datasets from a variety of cell phone and other GPS devices from vendors who supply GPS services to the trucking industry. Information gained from network data can be used to identify current truck routes as well as potential alternatives that may serve additional destinations or facilitate a faster trip. Network data can also include critical information regarding routes that are inaccessible to trucks because of weight limits, vertical clearance, truck prohibitions, or other reasons. Freight Flow Data Commodity flows are typically used in freight planning to provide insights about the economic and trade environment of a region. Commodity flow attributes help tie goods movement to eco- nomic development by providing information about urban consumption dependencies such as raw material or service input markets (imports), and markets for finished manufacturing prod- ucts (exports). As such, commodity flow information also is used to generate trip estimates in some traffic modeling applications. Commodity data at the urban level can provide insight about interdependencies between goods and services such as retail trade and food services. Commodity flow data also can help identify those industries in a regional economy that are highly dependent on transportation (e.g., those industries producing high-volume movements and/or high-value products). When combined with other economic and demographic informa-

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Using Freight Data for Planning 37 Exhibit 4-8. Freight flow data. Source: Wilbur Smith Associates. tion, freight flow data can help depict how an urban area is connected through trade to other regions of the nation or the world. Freight flow data is origin-destination information about commodity shipments (see Exhibit 4-8). The typical commodity flow record will contain an origin-destination, type of commodity, weight and/or value of the commodity shipment, and mode of shipment. There are secondary sources of freight flow data from both public and commercial sources. Exam- ples include Commodity Flow Survey (BTS); Freight Analysis Framework, Version 3 (FHWA); Railroad Waybill (Surface Transportation Board [STB]); and TRANSEARCH (IHS Global Insight). The Commodity Flow Survey (CFS) is conducted as an element of the Economic Census conducted by the U.S. Census Bureau every 5 years. The CFS is produced by surveying business establishments in mining, manufacturing, wholesale trade, and selected retail industries. The CFS provides estimates of tons shipped and dollar values for all major modes and covers the entire United States. However, the CFS has a number of well-researched weaknesses. For example, not all commodities are covered by the CFS--the survey does not survey establishments classified as government, farms, forestry, fisheries, construction, or transportation. The CFS does not capture the first leg of imports. Although the CFS plays an important role in providing data on domestic freight movements, gaps in shipment and industry coverage, and a lack of geographic and com- modity detail, limit the direct usefulness of the CFS data, especially at the urban level. The Freight Analysis Framework (FAF) dataset produced by FHWA, now in its third genera- tion, uses the CFS as a starting point, and then uses statistical modeling methodologies to remedy most of the deficiencies associated with the CFS. The FAF-3 database includes measurements of freight flows by weight and value between 131 unique geography zones. The United States is divided into 123 domestic zones while areas outside the United States are represented in 8 distinct foreign zones. The database yields freight flow origin and destination (O/D) pairs, identifying