Jennifer Symoun:
Today's seminar is being recorded. Today we'll have two presenters: Rolf Schmitt of the Federal Highway Administration Office of Freight Management and Operations and Tianjia Tang of the Federal Highway Administration Office of Highway Policy Information.
Dr. Schmitt has been involved in freight and data issues throughout his 30-year career in federal agencies, including the National Transportation Policy Study Commission in the 1970s, the Bureau of Transportation Statistics in the 1990s, and the Federal Highway Administration in the 1980s and since 2000. He manages the analysis team for the FHWA Office of Freight Management and Operations, and is an emeritus member of the Freight Transportation Data Committee of the Transportation Research Board.
Dr. Tang serves the position of Division Chief for the Travel Monitoring and Surveys Division with FHWA's Office of Highway Policy Information. Prior to his current assignment, Dr. Tang was a transportation specialist with the Office of Freight Management and Operations. Before joining the Federal Highway Administration Headquarters, Dr. Tang worked in FHWA's Resource Center where he provided technical assistance to State DOTs, MPOs and various other organizations in areas of travel demand modeling and transportation conformity. Prior to his Federal tenure, he had over ten years experience in private consulting and State DOT works. Dr. Tang is a registered professional engineer in the State of Georgia.
I'd now like to go over a few logistical details prior to starting the seminar. Today's seminar will last 90 minutes, with 60 minutes allocated for the speakers, and the final 30 minutes for audience Question and Answer. If during the presentations you think of a question, you can type it into the smaller text box underneath the chat area on the lower right side of your screen. Please make sure you are typing in the thin text box and not the large white area. Please also make sure you send your question to “Everyone” and indicate which presenter your question is for. Presenters will be unable to answer your questions during their presentations, but I will start off the question and answer session with the questions typed into the chat box. Once we get through all of the questions that have been typed in, the Operator will give you instructions on how to ask a question over the phone. If you think of a question after the seminar, you can send it to the presenters directly, or I encourage you to use the Freight Planning LISTSERV. The LISTSERV is an email list and is a great forum for the distribution of information and a place where you can post questions to find out what other subscribers have learned in the area of Freight Planning. If you have not already joined the LISTSERV, the web address at which you can register is provided on the slide on your screen.
Finally, I would like to remind you that this session is being recorded. A file containing the audio and the visual portion of this seminar will be posted to the Talking Freight Web site within the next week. We encourage you to direct others in your office that may have not been able to attend this seminar to access the recorded seminar.
The PowerPoint presentations used during the seminar are available for download from the box in the lower right corner of your screen. Please follow the directions above the box to download the presentations. The presentations will also be available online within the next two weeks. I will notify all attendees of the availability of the PowerPoints, the recording, and a transcript of this seminar.
We're now going to go ahead and get started. Today's topic, for those of you who just joined us, is Understanding and How to Use the Freight Analysis Framework. Our first presentation will be given by Rolf Schmitt of the Federal Highway Administration Office of Freight Management and Operations. As a reminder, if you have questions during the presentation please type them into the chat box and they will be answered in the last 30 minutes of the seminar. Rolf, when you're ready you can begin.
Rolf Schmitt:
Thank you. The Freight Analysis Framework, also known as the FAF, is the most comprehensive picture of goods movement in the country. I'm going to introduce you to what the FAF is, what it is not and how it relates to other data sources. Tianjia will explain how to tap it from the comfort of your keyboard.
The FAF was designed to help us understand the pressures being placed on the option system. We need this understanding to guide investments in other policies needed to handle the expected growth and to keep the economy moving.
The needed understanding is built on answers to simple questions made complicated by the sheer size of the American economy. What are we moving? Where? How is it getting there? And when is it moving?
The FAF answers the what, where, and how questions at the national scale for the years ending in 2 and 7, the years of the quinquennial Economic Census. We also forecast the what, where, and how to 2035, a planning horizon for many metropolitan planning organizations. We also provide provisional estimates, and I emphasize provisional, for the most recent year.
Since the FAF deals with annual averages, we must turn to other data sources to answer the question of "when." One such program, also managed by the freight office in the Federal Highway Administration, monitors track activity continuously on interstate highways and at major border crossings to measure freight performance.
We have already mentioned one thing that the FAF does - measure average flows - and what it does not do - identify seasonal or daily variation in those flows. The FAF is a comprehensive picture of freight flows among regions, including the quantity and value of local movement within a region or between regions. The FAF focuses only on the longer distance flows, greater than 50 miles, when turning tonnages on trucks into trucks on specific highways.
The FAF is a good total picture for the nation and its major corridors, but it is not detailed enough to tell you what is moving through the corner of Second and Elm streets.
FAF forecasts are what the expected economy will generate, unconstrained by capacity, and FAF congestion maps are what the future demand will do to the current network, not the planned or possible future network. Forecasts are not sensitive to energy prices or other factors that will affect future mode choice or other transportation characteristics.
The FAF shows states and localities where they fit in the nation and global freight system. This is essential for most places, where the majority of freight is inbound, outbound, or through traffic, and not local.
The FAF must be supplemented by local data and policy-sensitive models to plan local projects and to test the effectiveness of proposed local and national solutions to freight mobility issues.
You will often hear us refer to FAF2. The current version of the FAF is very different in scope and method from the original FAF. You should not compare FAF1 statistics with FAF2. We have created 1997 estimates using FAF2 methods for those of you that want a time series.
We have made several minor corrections to FAF2, so the most current version is FAF 2.2. We anticipate the final version to be 2.3. We will begin to design FAF 3 when the 2007 census data are available.
The FAF consists of two data sets: the O-D database for region-to-region flows, and the network database of long-distance truck volumes on specific highways. The O-D database is enormous: value and weight by 138 regions, 6 modes, 43 commodity types, and 9 years. The years are 1997, 2002, the most recent year, and 2010 through 2035 in 5-year increments. Tianjia Tang will explain how this database is structured after my comments.
The FAF regions are metropolitan areas and balances of states, including the Commodity Flow Survey regions shown here plus additional metropolitan areas that serve as major international gateways such as Laredo, Texas, and Savannah, Georgia.
The network database includes all the major highways over which trucks operate. We convert tons moving by truck into truck payloads and assign payloads to the highway network based on vehicle counts in the Highway Performance Monitoring System. Future FAF trucks are based on forecasted tonnage by truck. Forecasts of other truck volumes for construction and service vehicles and for passenger vehicles are essentially extrapolations of forecasts in the Highway Performance Monitoring System.
This is a snapshot of the FAF truck network. The database and details of estimation methods are on the website. Tianjia will explain how the files are structured and used.
The FAF is more of a data integration process rather than a traditional transportation model. It draws from all of these data sources, as well a few others for specific items such as municipal solid waste. How each data source is used is documented on the FAF web site.
The most important data source is the Commodity Flow Survey, or CFS, conducted every 5 years by the Bureau of the Census with major funding from the Bureau of Transportation Statistics. The CFS is a survey of shippers in manufacturing, mining, wholesale, and selected other industries. The CFS has greater commodity detail than the FAF, but the CFS does not cover all commodity movements because it does not cover all shippers. The FAF turns to other data sources to fill in the missing pieces. As a consequence, FAF flows are bigger than CFS flows.
While the FAF uses data from the Rail Waybill, FAF statistics for rail do not equal statistics from the Waybill. One major difference is that the Waybill may double-count rail shipments that move on more than one carrier, and includes shipments that move by rail and another mode. The FAF counts the shipment by multiple railroads only once, and counts shipments by rail and another mode with intermodal rather than with rail.
The FAF also uses data from the Corps of Engineers, but FAF water flows rarely match the statistics in the Corps' waterborne commerce publications. As in the case of the Rail Waybill, a shipment that goes from deep sea to intraport to inland water carrier is counted 3 times by the Corps and only once in the FAF. The Corps also counts as water crude petroleum flows from offshore wells, which the FAF assigns to pipelines. The Corps counts Puerto Rico as domestic while the FAF counts Puerto Rico with Latin America because it is not covered in the CFS.
One of the biggest sources of confusion among FAF users is the definition of intermodal. The FAF definition is driven by the Commodity Flow Survey, and is not the common definition tied to containerized shipments or the container-on-flatcar and trailer-on-flatcar services of railroads. An intermodal shipment is any shipment, including bulk cargo, that moves on more than one mode, plus mail and small shipments by parcel express carriers for whom the mode cannot be determined by the shipper. One exception is air cargo, virtually all of which moves by truck at one or both ends of the flight. This is left in air cargo so aviation does not disappear completely into the FAF intermodal category. The other exception is intermodal traffic that crosses the borers with Mexico and Canada. Since we know only the mode at the border crossing, we assume the shipment stays on that mode.
Perhaps the most important thing to remember about mode is that mode in the FAF O-D file is the domestic mode. A shipment from Asia to Los Angeles by water and on to Chicago by rail will be a rail shipment in the SEA file. If you are interested in the domestic moves of foreign trade, it is a rail shipment. If you are interested in the importance of intermodalism to foreign trade, it is a water and rail - i.e. intermodal - shipment. This is why intermodal statistics can vary in the FAF.
One of the most common questions I get about the FAF is why the total value of shipments exceeds Gross Domestic Product (GDP). The FAF counts everything that moves in the year: raw materials to factories, manufactured products to stores, and final deliveries to homes and offices. GDP counts the nation's output as what was consumed in the year or left in inventories at year's end. GDP is by definition smaller.
As I said in the beginning, the FAF does not answer anything. It is a good start, but more is needed to make effective use of FAF data. We are about to release a major update to the very old Quick Response Freight Manual, which is full of suggestions on how to use the FAF. Improved methods of freight demand forecasting are under development in a major study through the National Cooperative Freight Research Program. And we are linking the Highway Economic Requirements System and other models to FAF forecasts to provide more policy-sensitive analysis of the consequences of future freight flows, future investment needs, and the like.
On the data side, we are exploring links between the FAF's average conditions and the more dynamic season-to-season and hour-to-hour pictures we get from our Freight Performance Measures program. We are looking at better ways to count trucks, and we are happy to help you find ways to collect local data to provide detail beyond the FAF's geographic resolution.
While we spend endless hours checking FAF results for reasonableness, we depend on FAF users to help us maintain the quality of FAF data. The data files are enormous and the estimation techniques are varied. We need many eyes familiar with the wide variety of commodities and regions to spot unexpected resultes and help us to determine whether the results are insights or errors.
We also depend on users to tell us if the modal definitions, classification systems, file structures, and other aspects of FAF architecture are useful or should be changed in the future. Many studies for the Transportation Research Board call for the creation of an National Freight Data Architecture to link data files and guide data collection programs. Does the FAF architecture meet these needs? What else should be done? A new project under the National Cooperative Freight Research program will take an initial look at these questions.
To reach the FAF and its documentation, you can use that long URL on the screen, or just go to www.dot.gov/freight, click on National Freight Statistics and Maps, and click on Freight Analysis Framework. This will bring up a page that has more FAF than you can imagine.
As you dig into the FAF send questions and feedback to me or to Mike Sprung, who is taking over Tianjia's responsibilities for management of the FAF. Tianjia has moved on to new challenges after implementing our aggressive plans that led to FAF2. As one of his last FAF duties, Tianjia is taking the stage for part two of this seminar. So at this point, I will hand it over to Tianjia.
Jennifer Symoun:
Thank you, Rolf. I do see a few questions that were typed in. We'll get to those at the end. I'm going to slide the phone over to Tianjia here. In just a second I will turn it over to you. Okay, our next presentation is by Tianjia Tang of the FHWA. You can begin.
Tianjia Tang:
Thank you. Until three weeks ago as Rolf said I was responsible for the Freight Analysis Framework here at the Federal Highway Administration. Since then I have taken on new responsibilities in the Office of Highway Policy Information. Two programs in my office covering travel monitory and travel survey are highly relevant to freight modeling. Remember freight and passenger modeling are together. Passengers and trucks traffic are occupying the same highway system. If you need more information on our monitoring and survey programs you can take a look at our website.
Today's topic focuses on the FAF, as Rolf said. From now on if you have any question you can contact these two people listed in Rolf's slide.
The objective of my presentation today is to get you familiarize with all FAF material. We have published tons of data on the web. The second goal is to enhance your understanding of the interconnections among the FAF data. How the data are linked together. The last one, I'll try my best to demonstrate how various products are produced from the FAF 2 data.
I was planning to do a live demo. But fearing a glitch, I decided to not do a live demo. I did capture as many screen shots as I could. This is a pseudolive demo.
We publish our most data via the internet. If you want to obtain the latest information, our website is the best bet. My suggestion to you is to start with USDOT's home page for freight, which is www.dot.gov/freight. Then select the Freight Analysis component. Once you hit enter key, that will take you to the Office of Freight Management and Operations home page. This home page shows the key programs. The first one is Freight Analysis, select that. That will take you to a host of topics under freight analysis. This page is long . You need to scroll down
Now you are at the home page of FAF. Home page for FAF is www.ops.fhwa.dot.gov/freight/freight_analysis/faf. OPS stands for operations. Remember the Office of Freight Management and Operations is under the larger Office of Operations. Today I'm going to come back to this page numerous times. Hopefully you will remember home page web address. If you cannot remember the home page address, go through our DOT home page for freight.
Under our home page here at the top you see Freight Analysis Framework. The first item under it is the product guide. It says FAF 2 product guide. It will show you our plans on what kind of things we are going to develop in the future. The next one is state freight profiles. Third is FAF 2 commodity origin destination data. Then we have the FAF provisional 06. This is a provisional data for 06. The data for 07 will be here after March this year. The next one is highway link and the truck data. The last on here is historical data. If you are planning to do some analysis you may want to download historical data. If you want to see our first generation you can go to that selection.
Under the data profile, if you select state profile it will take you to this page. You can click on any state on the map, or use the drop down menu. This will give you the profile for that state. It will include data for shipments within the state, from the state, to the state, trading partner, commodity types, all of the information in terms of tonnage and dollar value. Keep in mind it does not have congestion data.
Now we're back to the home page again. The second item here is commodity origin, destination. Select this one, it will take you to this part of our home page. It's FAF 2 data. There are three components here. The first one is the FAF 2.2 commodity origin destination database user's guide. I encourage you to download this short users' guide before you start playing around with the data. The second component is data is in Microsoft Access format. If you know how to use Access you can download those things. If you are using something else it will be much wiser for you to download the CSV data, which is the third componets.
Scrolling down on the screen you see other parts of the FAF. The technical documentation. We have just published our 13th or 14th document. The category right behind technical documentation is geographic zone files. This will give you maps showing how the United States and how the world is divided into different zones. Under there, there's another set of files called geographical files. This set of files is for GIS usage with commodity origin destination data.
Let's take a look at the provisional commodity origin destination data. The current provisional commodity origin destination data is for 2006. Buy the end of March of this year we'll post the 2007 data here. The format of the data, the format of the provisional data, is the same as the data for 2002 to 2035.
Back to FAF home page again. Let's look at the highway link and truck data. We have three different groups of files here again. The first one is the GIS file to be used with ESRI's GIS software. If you are using shp file, you can download the top three. You will see the data files. For them to function you need to download the FAF 2 output, which is faf2_2data.dbf. The output file is needed for both GIS packages. The last group of file sis to be used with TransCAD developed by Caliper. Regardless the GIS package, you need to download two of the three data sets here.
The last one here is FAF 2 historical commodity origin documentation. Why we chose 1997 is due to the fact that we had the commodity flow survey in 1997. For FAF2 we use 2002 as our base year because 2002 CFS provided us the foundation for our origin destination database.
Now let's come back to take an in depth examination of all the files.
Again you will see this screen here. Two different data and table formats. As you can see from our website, all of these files are very large. Do not try to open those files online. This is the key. ou will crash your system. You will cause trouble on our end too. What you should do is right click on the files, right click, save the target as, and save to a local storage device. Once you have downloaded to your local drive you can open it up. I have just downloaded the Microsoft Access database. It will show you six tables here. The first one is a BRD underscore kton, it's a transborter file. This data is the trade data between the U.S. and Canada and the U.S. and Mexico measured in thousand tons. The next one is BRD underscore MDOL. It's for million dollars. DOM, that is domestic shipment. You must have true origin and destination within the United States. Domestic origin and destination measured with kiloton units. The sea is our imports and exports data through our seaport. Measured with kilo tons, or million dollars there.
If you double click on the dom underscore kton table, this is the domestic origin, with the measurement unit of kilo tons, you will see this table pop up. The first column is origin. It's the FAF origin. Next one you will see is OST, that's origin state. Next one is destination. You have Dst. That's the destination state. Commodity is defined as the 2 digit SCTG with 42 types of commodities plus one unknown. So a total of 43. Mode includes truck, air, rail, water, intermodal pipeline and unknown. Each column represents data for that year and that commodity for that particular mode. The unit is the domestic 02 kilo tons. If you open a table DOM ,the unit is million dollars.
From this table alone you can do a lot of analysis here. Earlier I mentioned the state profile. All of our state profiles are produced through thes 6 tables. This is one of our state profiles here. As I have said, the state profile right now has the unit of tons, and the dollar value. From the state means from your state to other states. Not from your state to your state. We did it for 02 and 35. You can do any year or commodities you want, you know.
Trading partners, who are your trading partners? Who are you doing business with? All of those things can be done with the FAF 2002 alone.
Okay. Other things related to this database. Let's scroll down the screen. You will see the geographic files for FAF 2 commodity origin destination data. You have just seen the Microsoft access data base. How those things can be used together with the rest of the data. You know, I'm going to show you how the GIS files here can be used in connection with the MS Access database.
Under this heading here you have two sets of files. The first one is for archview or archinfor shp files. The second one is calipers' transcad files. You cannot open these files online. You need the software. So right click, save as. Then go back to your software and open it after you have saved all the files.
Once you opened the GIS file, the first thing you will see on your screen is a map. Let's take a look what is behind this map. Under this map the first column is ID. The third column it says FAF 2 underscore zone underscore code. That is the domestic region plus 17 additional international Gateways. Each of them has a unique code. Then the number. You will see the FAF region's full name. That's the full name for that region. Following this column here is a short abbreviation of the full name there. I want you to pay attention to the short name there. This short name is used throughout our entire database. If you want a correct linking reference, you must use this short abbreviation of the FAF regional name.
What can you do with this thing here? Clearly you can see which part of the world is grouped together for a given FAF region. Lets take a look at how the United States is mapped out. These are the 114 regions for the United States. Another thing here, often folks will wonder which county in the US belongs to which FAF region. With GIS in your hand that's a simple question. The screen shows you which county is grouped into which FAF region.
How about the rest of the world? We know the continent. Now we can also know which country belongs to which FAF region. If you looked into the international trade data, typically it's not continent specific. By overlaying the country on top of FAF region, you can identify country and faf region easily.
Okay. Now we opened the MS Access data file for domestic under kilo tons. Now we're opening this file here. We opened 2002 data. I showed you a little bit earlier. The table is domestic underscore KT. Let's see how this table can work in sync with our map on the screen. Remember I said the origin, destination, they are FAF origin destination in the FAF system. If you take a look at the three columns here on the screen this is where your linkage can be done. Under the map you see the abbreviation names. You have origin and the destinations. You can link the data to the map behind this table here. What this will help us do?, desire lines and a lot of other things.
On the screen, I'm showing you on the screen. This is the projected goods from and to Maryland from other parts of the world. You can do this kind of analysis for other regions that you want. The line thickness is proportional to the tonnage, which is from and to Maryland. Those analysis can easily be done.
Next one. This figure shows you information on your trading partner. This is goods from Texas to other states within the U.S. The darker the color you see on the states, they are receiving more goods from Texas. Clearly you can see California is getting more stuff from Texas than Wyoming.
We have just gone over one of our major databases here. The next one here I'm going to talk about is the FAF 2 highway links and truck data. Remember before we get to here, all we have talked about is tonnage and the dollar value. Data associated with this file here is truck pay load. It's number of trucks, number of passenger vehicles. Now we're talking about AADT, AADTT under this topic here.
If you click on this selection ,it will take you to this here. Three different file types are shown here. Regardless if you are working with archview or trasncad you will always need the FAF output data. You will always need to download this file and to link it to the map. Again, right click, save the file to the hard drive and then open it.
Once you downloaded the GIS file, doesn't matter which package you have, download the output file too, open it. You see this map here. The lines you see represent over half a million miles of highways. Covering all of the United States, some of Canada and Alaska. Let's look at what is behind those lines.
Everything so far you have seen on this line diagram on the screen are highways. They are tagged by state, county, functional, location, and a host of other attributes associated with that highway. But it does not have traffic data on it. The attribute here will help you to sort the roadway system out
Now if you download the output file and save it again. You can open it . This will show you the traffic size from different views. The first one is ID. Then the versions of our network files. The next one is annual average daily traffic for the year of 2002. AADTT means annual average daily truck traffic, You have FAF 02. Commodity carrying trucks for the year of 2002. If you see the extension 35 it means for the year of 2035.
One more thing that I want to mention. Volume capacity ratio. That is what we use to gauge the congestion level. I highlighted this ID column to get your attention. That is where, what we use to link traffic data to the map layer.
See the output data? You have ID. Under the data review for the map, for the highway map you have ID. Those IDs are unique. These Ids enables data to talk to each other. You need to link them together. Once you link those two sets of data together you can do a lot of things here.
Like the map Rolf showed you a little bit earlier. This is a truck flow map here on the screen. Congestion maps.
Next one you can do a state specific analysis map. There are a host of other things you can do with our data and our documentation. What I showed you so far is just small glimpse on what potentially can be done with these done.
One more thing I want to say is read the documentation. Read it, read it, and have a full understanding of what is going on before you jump into the data. It's a very, very complicated process. If you need further assistance just feel free to contact Mike. Mike is ready.. Thank you very much.
J. Symoun:
Thank you, Tianjia. Before we get started on the questions, I wanted to make a note. If there are any FHWA division office people online who were able to log on we have been told that there are DOT network problems. We will try to schedule this seminar again in the near future. In addition, this seminar is being recorded. We do apologize.
Now we will go on to the questions. I'll start with the questions that have been typed in. The first few were for Rolf. I'm going to open it up to Rolf, Tianjia, or Mike, whoever is best to answer. Can you explain further how FAF converts the commodity flows to truck flows between OD pairs. Can the Truck OD flows and trucks per link be obtained separately?
R. Schmitt:
I'll take a shot at that. The Commodity Flow Survey asks for the mode of each shipment that is covered in a sample. We have the basic truck flows in the CFS for the industries that the CFS covers. We use various methods to estimate the missing flows by mode. So the origin destination data shows flows by mode and commodity for every origin destination pair, including moves within a given region. We go through a fairly involved process of slicing and converting those tonnages into truck payloads and then assigning the truck payloads to the network. On the documentation page that Tianjia pointed out, the very last special report, I think it's report S9 on the origin destination documentation page, will explain how we create truck payloads. We have not added those up into a number-of-trucks file, if you will. Other than number of trucks on individual highway segments, we have not calculated a truck O-D matrix. This is partly because we are only dealing with FAF trucks, which is to say trucks that go at least 50 miles between origin and destination. We felt our assignment techniques were not good enough for shorter distances of travel. That's why we have the distinction between FAF trucks, which are fewer than the total trucks in the Highway Performance Monitoring System. Total trucks include service vehicles, construction vehicles, and trucks carrying short haul, less than 50 miles. Did I catch all of that question? I should also add that in our assignment methods we do some disaggregations of our FAF regions to get greater geographic detail. But I should emphasize that, while we're confident in the corridor level estimates that we have, we are not confident in the data if you are comparing parallel routes between two regions. Our estimates fit the best we can to truck counts. If you were trying to use our forecast levels for project planning, or for getting below a broad corridor level, you really need to supplement the FAF with a local understanding of what is moving locally. If you use the Baltimore-Washington example, we could have too many trucks on I-95 and not enough on U.S. 29. That averages out when you look at the entire northeast corridor. It gets you into trouble if you are doing a plan for the Baltimore- Washington areas. This is why we emphasize that FAF is good for corridor level flows and for understanding how your region fits into the broader national and global networks.
T. Tang:
I want to add one more thing. The key we are using in FAF is the truck payload factor developd through the vehicle inventory and use survey supplemented by weigh in motion data . That's the truck pay load factor to convert the tonnage to the number of truck pay load. Remember the vius is a survey result. People tell you how much they are putting on the truck. We complimented the data with wim at a state specific geographic level. We developed these factors for a given commodity and a given truck body type.
J. Symoun:
The next question is what is a definition of OD geography in FAF?
R. Schmitt:
The definition in the FAF comes from the Commodity Flow Survey's 114 regions, which are mainly metropolitan areas. When regions overlap the state lines into big-enough pieces, we split the metropolitan area in two. For Kansas City we have the Kansas City, Kansas portion and the Kansas City, Missouri portions in separate FAF zones. And as was described in the documentation, we include the metropolitan areas, balances of states, we also carved out some international gateways that had enough traffic. Gateways are also metropolitan areas. All of this is described in one of the technical documentation reports that explains how we came up with the international gateways and the foreign trade regions.
J. Symoun:
The next question is, have the future projections in the FAF OD analysis been updated to take into account the most recent year of data?
R. Schmitt:
We created a provisional estimate of the most recent year. We're just trying to finish up the 2007 files now, which updates from the 2002 database. We are not changing the forecast years. We don't want to change the forecast years until we run FAF 3. The forecasts are based on a very involved set of national, regional and international estimates of economic conditions, which we turn into commodity flows for our 2010 to 2035 forecast. I will add that the basic methods we use are to look at how much is spent on different commodities, which is turned into amounts in tonnage given value-to-weight relationships. This is all done in constant dollars to control for inflation. Now, if I had forecast 30 years ago the exact amount of money spent today on prerecorded music, I would be predicting a lot of vinyl and 8-track tapes moving around the country. We do not acco0unt for changing technology and other things. We are forecasting current conditions out into the future. We really don't include technological changes or basic changes in the weight of goods. I should also point out that in the forecasts by mode, the forecasts of future tonnage and value of commodities by mode, all we're really doing is forecasting how much future coal and oil and wheat and other goods are to be moved. In each of the 43 commodity categories, we apply the 2002 mode split to the forecasted 2035 tonnage. If there's a change in the total mode split in 2035, it's driven by commodity mix, not by any of the economic characteristics or capacity characteristics of the individual modes. It's, it's really just projecting forward the amount of stuff we expect to move in the future. And then apply traditional mode splits to each to come up with the future mode split.
J. Symoun:
Okay. The next question is, how are the multiple waybills of the same move (rebilled moves) identified from the waybill sample - to be counted only once in the FAF? Since the Waybill Sample is a "sample", it may not have the other waybill record of the rebilled move. How does FAF address this?
R. Schmitt:
In the FAF, most of the individual movement data comes out of the Commodity Flow Survey, which includes rail. We use the totals in the rail waybill to help controlthe FAF and to help us estimate missing pieces. We don't go down to the individual shipment records of the Rail Waybill. We use the Waybill's aggregate data in helping us to make sure our control totals are roughly in the same ballparks. We don't get into the level of the Rail Waybill that would raise this particular problem.
J. Symoun:
Okay. Is truck tonnage converted to number of trucks by tonnage only or is there a conversion of product to cube usage (i.e. a ton of pillows will use more trucks that a ton of bricks)?
T. Tang:
Yes. That's where the vehicle inventory and use survey comes in. They do indicate truck pay loads by commodity type. That is going to be one of our challenges in creating FAF 3. The one thing we did not have in 2007 was a vehicle inventory survey. We're going to have to find ways to estimate what we used to depend on for that survey through other data sources, or forecasting historic values to the present.
By the way, if you are looking for state specific, those are conversion factors. Feel free to just email Mike. He's more than happy to send you those files. If you want a state specific table, email us.
J. Symoun:
This next one you may have already addressed this. You answered how to get Truck volumes on each link in the network. I'm still confused on whether a truck OD table is available (i.e. the input to the assignment).
T. Tang:
No. We do not create the truck OD.
R. Schmitt:
The answer is no. A conversion is done on the fly. By the way, the platform we adopted to run our network analysis is TransCAD. We used the assignment procedures in TransCAD to flow the network.
J. Symoun:
Okay. What are the factors that are considered in the estimation of 2035 international trade flows (e.g. widening of Panama Canal, economic growth, etc.)?
R. Schmitt:
The future forecasts were driven in large part by the forecasts provided by Global Insight when we had them do special runs. Global Insight's international trade forecasts feed into the FAF. All of the assumptions are what Global Insight uses. They do try to incorporate various demand factors, for individual types of commodities and the origins to try to get a handle on where demands are coming from. Population is a big factor in all of this.
J. Symoun:
How are inland distribution centers accounted for in the transfer of goods from an overseas port to a final destination?
R. Schmitt:
If everything worked properly, the shipment going from Asia to L.A. to the regional distribution center in Riverside that gets repacked and reshipped inland is really two separate flows: an international flow from Asia to L.A. and separately a domestic flow from Riverside to wherever it went in the U.S. If it went straight through and ended up in Chicago, went straight from the dock in L.A. to a train and off into the middle of the U.S., it is an international move from Asia, to L.A. to Chicago. The mode is intermodal because it's a rail move in the SEA file. You can read how we did all of this in the technical documentation. This was probably the hardest and the least precise part of the estimates and missing pieces because the inland move of imports is not well documented. We combined all of the data sets we had available and did our best to balance against many factors and figure out whether materials just went to the coast and were reshipped or if they moved directly inland. This was based on trade data and based on some information we have from individual ports. This is an area that we're hoping to improve in FAF 3 as we look towards 2007 for recalibrating FAF for the 2007 economic census.
J. Symoun:
What level of origin-destination and commodity detail is available for pipeline movements such as petroleum products in the FAF database?
R. Schmitt:
It's the same for all modes. But note we list it as pipelines and unknown together as a mode. The reason is, while we're comfortable with national pipeline estimates, breaking the total down by region, as anyone knows that deals with this, is a very complicated problem. It was so complicated the Commodity Flow Survey gave up on crude by pipeline for a number of reasons. We use estimated techniques. But that's why we combine it with unknown. That's where we are the least confident among the various modal data sets when you slice it by mode; the pipeline mode from region to region is the one we're the least comfortable with. We think we have a pretty good region-to-region estimate, but there could be variations. Since most geographic information about pipelines is at the multistate level, we're really slicing our pipeline data thin to get down to the FAF region-to-region flows, FAF regions being much smaller than pipeline regions.
J. Symoun:
The last question, who should we email for state specific data?
R. Schmitt:
Those questions should be referred to Michael Sprung. First, take a look at the state profiles on our web site. Tianjia pointed them out. If you don't see the information you need there, you can go to the FAF O-D database and sort by state to get all of the flows that go to and from your state by commodity and mode. If there are some things you thinkg would be useful as summary in future editions, that you think everyone would be interested in, by all means email the suggestions to Mike or me.
J. Symoun:
Okay. Let's see if anybody has questions over the phone. If the operator could give instructions.
Operator:
Thank you. If you would like to ask a question, please press star and then 1. You will be prompted to record your name. To withdraw press star and then 2. To ask a question, star 1. One moment please. At this time I show no audio questions.
J. Symoun:
Okay, I think we'll go ahead and close out for the day. I want to thank Rolf and Tianjia for presenting and thank everyone for attending today. The recorded version of this event will be available within the next week on the Talking Freight website.
The next seminar will be held on February 20 and will be a discussion of the recently updated Quick Response Freight Manual. If you haven't done so already, I encourage you to visit the Talking Freight Web Site and sign up for this seminar. The address is up on the slide on your screen. I also encourage you to join the Freight Planning LISTSERV if you have not already done so.
Enjoy the rest of your day!
