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Using Geospatial Info and Tools in Multi-Modal Analysis: The 2007 Commodity Flow Survey Steve Lewis USDOT, Research & Innovative Technology Administration.

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Presentation on theme: "Using Geospatial Info and Tools in Multi-Modal Analysis: The 2007 Commodity Flow Survey Steve Lewis USDOT, Research & Innovative Technology Administration."— Presentation transcript:

1 Using Geospatial Info and Tools in Multi-Modal Analysis: The 2007 Commodity Flow Survey Steve Lewis USDOT, Research & Innovative Technology Administration Bureau of Transportation Statistics Geospatial Concepts for Executives April 11, 2007

2 2 Background: What is the CFS? Freight survey of U.S. businesses (shippers) Performed by RITA/BTS in partnership with the Census Bureau Previous surveys in 1993, 1997, and 2002 as part of the U.S. Economic Census Provides data on actual shipments by mode of transportation

3 3 Background: The Need Part of major performance push to: Improve overall efficiency of estimating distances in the RITA/BTS 2007 Commodity Flow Survey Improve the methods used in generating the shipment mileages Improve the quality of mileage information reported in the survey

4 4 Shippers generally do not know distance shipments travel Survey asks for origin and destination ZIP codes Mileages are calculated for each shipment by mode (highway, rail, water, air, parcel and pipeline) Modal-mileages are critical for ton-miles Why CFS Mileage Calculation?

5 5 The Mileage Calculation Problem Large proportion of shipments are multi- modal Few national level, multi-modal GIS networks available Few (if any) commercial routing routines with mode-change logic  In a multimodal trip, when/where does the mode change take place

6 6 The Solution: A Geospatial Approach Develop a geospatial-based tool GeoMiler based on current GIS technology and robust network data Develop core multi-modal routing models for domestic and export shipments for all modes Integrate map visualization tool to help Analysts better estimate mileages for problematic records

7 7 GeoMiler: Logical System Flow Pre-Processor (Geographic info correction) Pre-Processor (Geographic info correction) Post-Processor Modification, flag, and QA Post-Processor Modification, flag, and QA Mileage Solver (Multi-modal & Export) Mileage Solver (Multi-modal & Export) OUTPUT DATA Census Bureau OUTPUT DATA Census Bureau Map Interface (Path verification & presentation) Map Interface (Path verification & presentation) Data Processor Route solver Mapping Interface INPUT DATA Census Bureau INPUT DATA Census Bureau

8 8 The Mileage Calculation Process Required Data Input Valid Origin ZIP Code Valid Destination ZIP Code; if an export, valid Country Name (valid City Name for Canada and Mexico) Mode or Mode Sequence Commodity Type, particularly hazmat Commodity Weight

9 9 Input from Survey Form

10 10 Building GeoMiler: GIS Basis Fully integrated GIS based tool Seamless functionality with fully mechanized geographic info correction Multimodal pathfinder and distance solver ArcGIS 9.1 and Network Analyst  Route and OD solvers for estimations  ArcMap for visualization of routes

11 11 Building GeoMiler: GIS Networks Roads – TeleAtlas DynaMap Transportation Rail – FRA Rail Network Water – USACE Navigable Waterway Network Air – Based on BTS Office of Airline Information and Official Airline Guide Pipelines – Great Circle Distance

12 12 Modeling Multimodal Transfer Highway network Rail network TRUE ORIGIN TRUE DESTINATION Truck-Rail transfer facility Modal spatial joins

13 13 Spotsylvania, VA - Chicago: Multimodal Truck->Rail

14 14 Shenadoah, WV – Wendell, MA: Multimodal Rail->Water->Rail->Truck

15 15 Ashland, MA - Frederick, MD: Multimodal Truck-> Air (Dulles)->Truck

16 16 GeoMiler: Beyond the CFS?? Offers possible solutions for other geospatial needs Capability for other uses and applications beyond CFS distance calculation BTS interested in partnering with other federal agencies with comparable geospatial needs and challenges

17 17 Steve Lewis (202) Questions or Comments?


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