1. 1Managed by UT-Battelle for the U.S. Department of Energy Talking Freight Seminar Freight Analysis Framework, version 3 Diane Davidson Center for Transportation Analysis Oak Ridge National Laboratory October 20, 2010

2. 2Managed by UT-Battelle for the U.S. Department of Energy  123 US and 8 foreign flow origination regions(O)  123 US and 8 foreign flow destination regions(D)  43 Commodity Classes (SCTG 2-Digit)(C)  7 Modal Classes (8 in domestic)(M) The full FAF3 flow matrix has almost 500M data cells that need to be estimated, or suppressed as having a zero value. Dimensions of the FAF3 Flow ODCM Commodity Flows Matrix Flow Dimensions Needed for Reporting (User) Purposes Foreign O Domestic O Domestic D Foreign D Import Mode Domestic Mode Export Mode SCTGTrade (Dom. Imp. Exp.) 8123 8787433

3. 3Managed by UT-Battelle for the U.S. Department of Energy ODCM Flows Matrix Annual Updates Spatial Disaggregation of FAF3 Flows for Traffic Assignment Purposes 2007 Origin-Destination-Commodity- Mode (ODCM) Annual Freight Flows Matrix (reported in annual tons and 2007 dollars) On-Line, Web-Based FAF3 Data Products Extraction Tool Long Range (2040) ODCM Forecasts US Highway Network Truck Traffic Assignment FAF3 Highway Network

4. 4Managed by UT-Battelle for the U.S. Department of Energy FAF3 Freight Flow Matrix Construction Process Flow Matrix Construction & Missing Flow Value Inferencing Techniques 2007 U.S. Commodity Flow Survey Data: Domestic Shipper Based, Multi-Modal Commodity Flows (Air, Rail, Highway, Water, Pipeline) Truck-Only Flows associated With: Farm Based, Fisheries, Logging, Construction, Retail, Services, Municipal Solid Waste, and Household & Business Moves Multi-Modal Truck, Rail & Water Flows associated with: Crude Petroleum, Petroleum Products & Natural Gas Flows International (Import & Export) Flows: -Deep Sea Shipping Flows -Air Freight Flows -Transborder - all modes except air & Pipeline -Crude and Natural Gas Imports U.S Shipper Sampled, Multimodal Commodity Flows by Value and Weight Foreign & Domestic Commodity Flows FAF3 Origin – Destination Commodity Mode Freight Flow Matrices Reported in annual tons and 2007 dollars CFS In-Scope Flows CFS Out-Of-Scope Flows

5. 5Managed by UT-Battelle for the U.S. Department of Energy Estimation of Missing CFS Cell Values in FAF3 The ORNL Log-Linear/IPF Routine Uses a Number of Methods for Identifying Sampling versus Structural Zero-Valued Cells.

6. 6Managed by UT-Battelle for the U.S. Department of Energy FAF3 Freight Flow Matrix Construction Process Flow Matrix Construction & Missing Flow Value Inferencing Techniques 2007 U.S. Commodity Flow Survey Data: Domestic Shipper Based, Multi-Modal Commodity Flows (Air, Rail, Highway, Water, Pipeline) Truck-Only Flows associated With: Farm Based, Fisheries, Logging, Construction, Retail, Services, Municipal Solid Waste, and Household & Business Moves Multi-Modal Truck, Rail & Water Flows associated with: Crude Petroleum, Petroleum Products & Natural Gas Flows International (Import & Export) Flows: -Deep Sea Shipping Flows -Air Freight Flows -Transborder all modes except air & Pipeline -Crude and Natural Gas Imports U.S Shipper Sampled, Multimodal Commodity Flows by Value and Weight Foreign & Domestic Commodity Flows FAF3 Origin – Destination Commodity Mode Freight Flow Matrices Reported in annual tons and 2007 dollars CFS In-Scope Flows CFS Out-Of-Scope Flows

7. 7Managed by UT-Battelle for the U.S. Department of Energy Out-of-Scope Commodities U.S. freight shipping establishments in the following industrial sectors were not surveyed as part of the 2007 US Commodity Flow Survey. These out-of- scope (OOS) industries therefore had to be assigned commodity and mode specific O-D flows using other methods. Farm-based agriculture shipment Fishery Cruel Petroleum Natural gas Municipal solid wastes Forestry Construction Retail Services Household and businesses moves, and Imports

8. 8Managed by UT-Battelle for the U.S. Department of Energy Out-of-Scope Commodities: Domestic Truck Flows Data modeling details vary a good deal by commodity class. Input-Output data is used to convert OOS industrial sector inputs and outputs to FAF3 commodity inputs and outputs. O-D flows estimated using spatial interaction models. Estimate national or regional (e.g. state) shipments totals for each industry by FAF3 commodity class. Allocate shipments (by ton and value) down to counties. Estimate O-D flows at the county-to-county level Re-aggregate the O-D estimates from counties back up to FAF3 region-to-region flows.

9. 9Managed by UT-Battelle for the U.S. Department of Energy Imported as well as exported freight flows in FAF3 are constructed from mode specific data sources, each of which must have its flows converted from HS commodity codes to FAF3’s 2-digit SCTG codes, as well as have its flows either spatially aggregated or disaggregated to match FAF3 analysis zones. Out of Scope Flows: Imports & Exports International Waterborne Freight data ( PIERS/USACE/FTD) International Waterborne Freight data ( PIERS/USACE/FTD) US/Canada & US/Mexico TransBorder Freight data (BTS) US/Canada & US/Mexico TransBorder Freight data (BTS) International Air Freight data (BTS/FTD) International Air Freight data (BTS/FTD) Application of commodity and spatial zoning system crosswalks for the purposes of matching data sources to FAF3 commodity classes and geographic analysis zones Application of commodity and spatial zoning system crosswalks for the purposes of matching data sources to FAF3 commodity classes and geographic analysis zones FAF3 Foreign Origin(O)-Destination(D)-Commodity(C) -Mode(M) Flows Matrix (annual tons and 2007 dollars) FAF3 Foreign Origin(O)-Destination(D)-Commodity(C) -Mode(M) Flows Matrix (annual tons and 2007 dollars) Merged Domestic + Foreign FAF3 ODCM Matrix Data Source Specific Flow Modeling & Data Gap Filling Procedures Data Source Specific Flow Modeling & Data Gap Filling Procedures For the first time, FAF3 makes use of PIERS data on the movements of foreign freight within the US. PIERS Imported/Exported Petroleum & Natural Gas (EIA)

10. 10Managed by UT-Battelle for the U.S. Department of Energy FAF3 Methods and Data Source Improvements Significant FAF3 Improvements to the commodity flow matrix over previous versions: A doubling of the number of U.S. shipping establishments sampled as part of the 2007 U.S. CFS (from some 50,000 establishments in 2002, to approximately 100,000 establishments surveyed in 2007; The use of PIERS data to improve estimates of the allocations of waterborne imports and exports to FAF domestic zones of freight origination (for U.S. exports) and destinations (for U.S. imports); Incorporation of additional federal datasets within an enhanced FAF3 log- linear modeling/iterative proportional fitting algorithm; Greater use of U.S. inter-industry input-output (‘use’ and ‘make’) coefficients and additional federal datasets in the development of the FAF3 out-of-scope (to the 2007 CFS) commodity flow estimates; The ability to access FAF3 data products via a user friendly web-based data set construction and download tool.

11. 11Managed by UT-Battelle for the U.S. Department of Energy FAF3 Data Products, including the full FAF3 ‘ODCM’ matrix of 2007 commodity flows can be found at the following FHWA website: http://www.ops.fhwa.dot.gov/freight/freight_analysis/faf/index.htm This site contains the FAF3 Data Extraction Tool. Allows users to customize and download tables directly from the FAF3 database. The site will also contain interactive links to FAF3 Data Documentation and Data Summaries. Users can also download the entire FAF3 2007 regional database in either Microsoft Access 2003 or in CSV format by going directly to the following FAF 3 url: http://cta-gis.ornl.gov/faf/ FAF3 Data Products

12. 12Managed by UT-Battelle for the U.S. Department of Energy The ORNL FAF3 Team Diane Davidson, M.S. Urban and Regional Planning Frank Southworth, Ph.D., Geography Bruce Peterson, M.S., Geography David Vogt, Ph.D., Economics S. M. Chin, Ph.D., Civil Engineering Ho-Ling Hwang, Ph.D., Operational Research and Statistics James Li, Ph.D., Civil Engineering