Today's seminar is being recorded.
Today we have two presenters, Rolf Schmitt and Tianjia Tang.
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 is 90 minutes with 60 minutes for the speakers and 30 minutes for question and answers.
If you thing of a question you can type it into the smaller text box on the lower right of your screen.
Please make sure to type in the thin text box.
Make sure to send the question to everyone and indicate which presenter the question is for.
I will start off the question and answer session with these questions.
Once we get through though the operator will give you instructions on how to ask a question over the phone.
If you ask a question after the seminar you can send it to the presenters or to the list serve.
If you have haven't already joined the web address is provided on the slide on your screen.
I would like to remind you that the session is being recorded.
The file will be posted to the Talking Freight website within the next week.
We encourage you to encourage others to access the roaring.
The -- recording.
The PowerPoint presentation is available for download.
There's direction above the box on how download the presentation.
We'll now go ahead and get started.
Today's topic is Understanding and How to Use the Freight Analysis Framework.
Our first presentation will be given by Rolf Schmitt.
As a reminder, if you have questions please type them into the chat box.
They'll be answered in the last 30 minutes.
With that I will bring up your presentation.
And you can begin.
The freight analysis framework is the most comprehensive picture of goods movement in the country.
I'm going to introduce you to what the faff 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.
It 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 need for understanding is built on answers to simple questions made complicated by the sheer size of the American economy.
What are we moving?
How is it getting there?
And when is it moving?
The faff answers it at the national scale for the years ending in 2 and 7.
Since the FAF deals with annual averages we must turn to other data sources to answer when.
One such program monitors track activity continuously on interstate highways and border crossings to measure freight performance.
We have mentioned one thing that the FAF does, major average flows and what it does not do, identify seasonal variation.
The FAF focuses only on the longer distance flows when turning tonnages on trucks into trucks on specific highways.
The FAF is a good total picture for the nation, but it is not detailed enough to tell you what is moving through the corner of second and elm streets.
FAF congestion maps are what the future demand will do to the current network, not the planned or possible network.
Forecasts are not sensitive to energy prices or other factors.
The FAF shows states and localities where they fit in the nation and global freight system.
This is essential for most places where most of it is out or inbound and not local.
It tests the effectiveness of proposed local and national solutions to freight mobility issues.
You will often hear us refer to FAF two.
You should not compare FAF one statistics with FAF two.
We have created 1997 estimates using FAF two methods for those of you that want a time series.
We have, um, we have made several minor corrections to FAF two.
The most current version is FAF 2.2.
We anticipate the final version to be 2.3.
Then we will begin to design FAF 3 when the 2007 census data are available.
The FAF consists of two data sets.
Region to region flows.
The OD database is enormous.
The years from 1997, 2002.
Tianjia Tang will explain after my comments.
The FAF regions are metropolitan areas and balances of states including this region shown here and other metropolitan areas.
The network database includes all the major highways over which trucks operate.
We convert tons moving by truck into truck pay loads and assign to the highway network based on vehicle counts.
Future FAF trucks are based on forecasted tonnage by truck.
Forecasts of other truck volumes for construction and service vehicles and passenger vehicles are extract lapses of forecasts in the highway performance monitoring system.
This is a snapshot of the network.
The database and details of estimates are on the website.
Tianjia will explain how the files are structured and used.
The FAF is more of a data integration process.
It draws from all of these data sources, as well a few others.
For specific items such as municipal solid waste.
The most important data source is the commodity flow survey, or CFS.
The CFS a survey of shippers and manufacturing, mining and other industries.
The CFS has greater commodity detail, du does not cover all of the shipments.
It does not cover all shippers.
The FAF turns to others to fill in the missing pieces.
FAF flows are bigger than CFS flows.
The FAF uses data from the rail.
One major difference is the many rail shipments are on more than one carrier.
The FAF counts the shipment by multiple railroads only once.
And rail and other 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 water borne commerce.
The corps also counts crude petroleum from offshore wells, which the FAF assigns to pipelines.
One of the biggest sources of confusion among FAF users is the definition of intermodal.
It is driven by the commodity flow survey.
Any shipment, including bulk cargo that moves on more than one mode, plus mail and small shipments when the mode cannot be determined by the shipper.
One exception is air cargo, virilely all of which moves by truck at one or both ends.
This is left in air cargo so aviation does not disappear completely.
The other exception is intermodal traffic that crosses the borer.
Since we know the mode at the border.
We assume the shipment stays on that mode.
The most important thing to remember about mode is that mode in the FAF OD file is the domestic mode.
A shipment from Asia to Los Angeles by water and to Chicago by the rail will be a rail shipment.
If you are interested in the importance of intermodallism to trade, it is an intermodal shipment.
This is why statistics with vary in the FAF.
One of the most common questions I get is why the total value of shipments exceed the 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 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're about to release a major update of the manual which is full of suggestions on how to use the FAF.
We are linking the highway economic requirement system and other planning models to FAF forecasts to provide more policy sensitive analysis of what the future freight flows will do, future investment needs and the like.
On the data side, we are exploring links between the average continues and the more dynamic pictures we get from day-to-day and hour to hour.
We are looking at better ways to count trucks and we are happy to help you find ways to collect local data and provide detail beyond the FAF's geographic resolution.
While we spend endless hours checking results.
We depend on users to help us maintain the quality.
The data files are enormous.
We need many eyes familiar with the wide variety of commodities in regions to spot unexpected resulted and help us to determine if they're insights or errors.
We also depend on users to tell us if the modal definitions, classification systems, file structures and other architecture that we use are useful, or should they be changed in the future?
Thinking ahead towards FAF 3.
Many studies call for the creation of a formal national structure.
Does the architecture meet these needs?
What else should be done?
To reach the FAF and it's documentation you can use that long URL on the screen, or just go to www.DOT.gov/freight 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 S, who is taking over for management of the FAF.
Tianjia has moved on to new challenges after implementing our plans that led to FAF 2.
He is taking the stage for part two of this seminar.
So at this point I will hand it over to Tianjia.
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.
Until three weeks ago as Rolf said I was responsible for the freight analysis framework here at Federal Highway Administration.
Since then I have taken on new responsibilities in the office of highway policy information.
These are highly relevant to the freight modeling.
Remember freight and passenger modeling are together.
Most of the passengers on the trucks that are occupying the same highway system.
If you need more information on the programs you can take a look at our website.
Today's topic focuses on the FAF, as Rolf said.
From now if you have any question questions you can contact these two.
The objective of my presentation today is to get you familiar with all FAF material.
We helped publish 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 the data products, how the various products are produced from the FAF 2 data.
I was planning to do a lot of demo.
But fearing a glitch, I decided to not do a live demo.
I did as many screen shots as I could.
This is a pseudolive demo.
We have published our most recent, most recent publication.
If you want to obtain the latest information, our website is the best bet.
This is not the easiest way.
My suggestion to you is to start with USDOT's home page for freight, which is www.DOT.gov/freight.
Then select the component.
Hit enter, that will take you to the office freight management and operations home page.
This home page it shows the key programs.
The first one is freight analysis, press that.
That will take you to a host of topics of freight analysis.
This is a long page.
You need to scroll down the screen.
Now you are at the home page of FAF.
Home page is www.OPS remember the office of freight management and freight management and operations is under the larger office of operations.
The website is listed here for your use.
Today I'm going to come back to this page numerous times.
Hopefully you will remember our home page.
If you cannot remember this home page, go through our DOT home page for freight.
Under our home page here at the FAF home page, at the top you see freight analysis framework.
The first item is right under it.
It says FAF 2 documentation guide.
It will show you our plans on what kind of things, where things will develop in the future.
The next one is state freight profiles.
Third is FAF 2 commodity [ Indiscernible ].
Then we have the FAF provisional 06.
This is a provisional data for 06.
The data for 07 willer here after March this year.
After March of 08.
There's a highway link and the truck data.
It has historical data.
If you are planning to do some [ Indiscernible ] analysis you may want to download historical data.
If you want to see our first generation you can go to that selection.
So 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 in 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.
[ Speaker Faint/Audio Unclear ].
Now we're back to the home page again.
Now to the second item here.
Commodity origin, destination.
Select this one, it will take you to this part of our home page.
It's FAF 2 data.
You will have 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.
Microsoft [ Indiscernible ] 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 [ Indiscernible ] data.
Scrolling down on the screen you see other parts of the FAF.
The technical documentation.
We have published our 13th or 14th document.
The category right behind technical documentation is [ Indiscernible ].
This will give you a map to show 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.
Let's take a look at the provisional commodity origin destination data.
The provisional commodity origin destination data is from 2006.
But end of March of this year we'll post the 2007 data here.
The format of the data, the provisional data, is the same as the data for 2002 [ Indiscernible ].
Back to this home page again.
Let's look at the highway link to truck data.
We have three different groups of files again.
The first one is the GIS file for the [ Indiscernible ] products.
If you are using ship file, [ Indiscernible ], you can download the top three.
You will see the [ Indiscernible ] data files.
For them to function you need to download the FAF 2 output, which is FAF 2 data dot DBF.
You need to download two of the three data sets here.
The last one here is FAF 2 historical commodity origin documentation.
1997 we had the commodity flow survey.
For 2002 it's our base year.
2002 provided us the foundation for our origin destination database.
Now let's come back to take a look in depth.
Again you will see this screen here.
Two different table format.
As you can see from our website, all of these files are very large.
Do not try to open those online.
That's the key.
You 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.
Save to a local storage device.
Once you have downloaded to your local drive you can open it up.
I have just downloaded Microsoft access database.
It will show you three tables.
The first one is a BRD [ Indiscernible ] it's a transporter file.
This data is the trade data in the U.S. and Canada and the U.S. and Mexico.
The next one is BRD underscorer MDOL.
It's for million dollar.
BOM, that is a domestic shipment.
You must have two destinations within the United States.
Domestic origin measured with kiloton units.
[ Indiscernible ].
The C is our imports and exports data through our seaport.
Measured with kilo tons, or million dollars there.
If you double click, this is the domestic origin, with the measurement unit of kilo tons, you will see this table pop up.
You will see the first column is origin.
It's the FAF origin.
You will have OST, that's origin stake.
You have a deaf nation that is the [ Indiscernible ] for the U.S.
You have DEST.
That's the destination state.
Commodity is [ Indiscernible ] with 42 types of commodities plus one unknown.
So a total of 43.
Mode real truck, pipeline and unknown.
Each column represents data for that year and that commodity for that particular mode.
The unit [ Indiscernible ] is the domestic 02 kilo tons.
If you open a table DOM judge score MDOL the unit is for 02 must be 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 the 06 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.
You can do [ Indiscernible ].
What kind of a commodities you are dealing with, you know.
Trading partners, who are your trading partners?
[ Indiscernible ].
Who is your trading partners?
Who are you doing business with?
All of those things can be done with the FAF 2002 [ Indiscernible ] alone.
For the commodity origin destination database.
Next one, let's take a look at the FAF 2 [ Indiscernible ].
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 canning used in connection with the MF access database.
Under this heading here you can have two sets of a file.
The first one is for [ Indiscernible ] ship files either for [ Indiscernible ].
The second one is [ Indiscernible ].
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 it.
The first thing you will see on your screen is a map.
It's 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 [ Indiscernible ].
That is the domestic region plus 17 [ Indiscernible ] 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 [ Indiscernible ] region.
Following this column here is a short abbreviation of the full name there.
I want you to pay attention to the shore name there -- short name there.
This short name is used throughout all our data base.
If you want a current reference, current link on region 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.
That's take a look at how the United States is mapped out.
This is one of the 14 regions for the United States.
Another thing here, often folks will wonder which [ Indiscernible ] belongs to which FAF region.
With GIF in your hand that's a [ Indiscernible ].
It shows you which county is grouped into which FAF region.
We know we have questions on [ Indiscernible ].
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.
Now UNGIS we opened the MS access data file for domestic under kilo tons.
Now we're opening this file here.
We opened 2002 [ Indiscernible ] data.
I showed you a little bit earlier.
The table is dome stake underscore KT.
Let's see how this table can work this sync with our map on screen.
Remember I said the origin, destination, they are FAF origin deaf nation in the -- destination in the FAF system.
If you take a look at the three columns 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 you to do is, often you will want to do a desire lines.
That's this one here.
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.
It's proportional to the tonnage, which is from or to Maryland.
Those lines can easily be done.
This figure shows you 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 done one of our major databases here.
The next one here I'm going to talk is the FAF 2 highway links and truck data [ Indiscernible ].
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 [ Indiscernible ] under this topic here.
If you click and this selection will take you to this here.
Three different file types here.
[ Indiscernible ].
Regardless if you are working with [ Indiscernible ] you will always need the FAF output data.
You will always need to download that file to link.
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, up open it.
You see this map here.
The sidelines you see -- the lines you see represents over half a million miles of highways.
Covering all of the United States, some of Canada and into Alaska.
Let's look what is behind those lines.
Everything so far you have seen on this line diagram on the screen are highways.
They are [ Indiscernible ] by the state, the county, the functional [ Indiscernible ], the 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.
Urban area or nonurban area [ Indiscernible ] and grouping purposes.
Now if you download the output file and save it again.
You can open it again.
This will show you the traffic size from different [ Indiscernible ].
The first one is ID.
Then the versions of our network files.
The next one is [ Indiscernible ].
Annual average daily traffic for the year of 2002.
Then the fourth column, you have more more extra T with it.
[ Indiscernible ].
You have FAF 02.
[ Indiscernible ].
Commodity carrying trucks for the year of 2002.
Then the [ Indiscernible ] is nonFAF 02.
If you see the extension [ Indiscernible ] 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 to the map.
The output data.
You have ID.
Under the data review for the map, for the highway map you have ID.
Those IDs are unique.
Shows how they 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.
Next one you can do a state specific analysis map.
Those are a host of other things you can do with our data and our documentation.
One more thing I want to say is read the documentation.
Read it, read it, and have a full understanding of what going on.
It's a very, very complicated process.
If you need further assistance just feel free.
Mike is already helping you folks out.
Thank you very much.
Thank you, Tianjia.
Before we get started on the questions, I wanted to make note.
If there's any FHWA division office people online who went able to log on there's network problems.
This is being recorded.
We will 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 Rolfing Tianjia, or Mike.
Just whoever is best to answer.
Can you explain how FAF converts to truck flows between the OD flows?
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 methods to estimate for the missing pieces, we estimate those by mode as well.
So the origin destination data shows it by mode and commodity for every origin destination pair, including moves within a given region.
Um, we go through a fairly involved process of slicing and converting those tonnages to truck pay loads and then assigning the truck pay loads to the network.
On the documentation page that Tianjia pointed out, at the very last special report, I think it's report S9, on the origin destination documentation page it will explain how we create truck pay loads.
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 done a truck OD matrix.
Partly because we're 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 smaller than the total trucks, which come from the highway performance monitoring system.
Which includes 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 mention, or I should emphasize that we're very, wile we're confident in the quarter level estimates that we have, if you are comparing parallel routes between two regions, our stimes fits a best we can the truck counts.
They don't, I, if you were trying to use especially our forecast levels for a project planning, or for getting below a broad corridor level you really need to supplement that with a local understanding of what is moving locally.
We can be high.
If you use the Baltimore, Washington example.
We could have too many trucks on i95 and not enough on 29.
That averages out when you look at a huge, or you are looking at the entire northeast corridor.
It gets you into trouble if you are doing a plan for the Baltimore, or Washington areas.
Which is why we emphasize FAF is for corridor level flows and understanding how your region fits into the broader national and global networks.
I want to add one more thing.
The key FAF we are using is the [ Indiscernible ].
That's the truck pay load center, to convert the tonnage to the number of truck pay load.
The number of trucks should be [ Indiscernible ].
The [ Indiscernible ] data, also FHWA has [ Indiscernible ].
Remember that's a survey result.
People tell you how much they are putting on the trucks.
We complimented the [ Indiscernible ] data with a state specific geographic level.
We came up with for a given commodity and a given distance.
Even truck body type.
Looking to see if there's anything else.
We'll move to the neck question.
The definition in the FAF, this comes from the commodity flow surveys, 114 regions which are metropolitan areas.
When they overlap the state lines we split the metropolitan area in two.
Kansas City we have the Kansas City Kansas portion and the Kansas City, Missouri portions separately as FAF zones.
And as was described in the documentation, we include the metropolitan areas, balance of state, we also carved out some international Gateways and had enough Gateway traffic that 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.
The next question is, the future projects been updated to take into account the most recent year of data?
We create a provisional estimate of the most recent year.
We're just trying to finish up the 2007 files now.
Which updates from the 2002 base.
We are not changing the forecast years.
We don't want to change the forecast years until we run FAF 3.
They're based on a very involved set of national, regional and international estimates of economic conditions.
Which we be turn into commodity flows for our 2010 to 2035 forecast.
I will add, the basic methods we use are to look at how much is spent on different commodities.
That is turned into the amount of tonnage given value to weight relationships.
This is all done in constant dollars.
It should take inflation, control for inflation.
Now if I had forecast 30 years ago the amount of money spent today on prerecorded music and forecasted it exactly I would be predicting a lot of vinyl and tapes moving around the country.
All of that has gone electronic since.
It's sunlight to changing technology and other things.
We are forecasting the conditions out into the future.
We really don't include technological changes, basic changes in the weight of goods.
I should also point out in the forecast by mode, we do forecast the future tonnage and value of commodities by mode.
All we're really doing is forecasting how much future coal and oil and wheat goods.
In each of those 43 commodities 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.
The neck question, how are the multiple weigh bills of the same move identified from the weigh bill sample, to be counted only once in the FAF.
It may not have the other weigh bill record of the rebuild move.
How does FAF address this?
The FAF is, really most of the individual movement data comes out of the commodity flow survey, which includes rail.
We use the totals in the CFS to, um, you know, to help control.
To help us estimate missing pieces.
We don't go down to the individual shipment records of the railway bill.
We use the aggregate data in helping us to estimate.
Madge sure our control totals are in -- make sure our control totals are roughly in the same ballparks.
We don't get into the level of the railway bill that would raise this particular problem.
Is truck tonnage converted to number of trucks by tonnage only?
Or a conversion by product [ Indiscernible ] usage?
That's where the vehicle inventory and [ Indiscernible ] 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 [ Indiscernible ] 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 [ Indiscernible ] 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.
There's a document called [ Indiscernible ].
They are only covered national average.
We have like over 2000 pages for those tables here.
If you want a state specific table, email us.
Um, this next one you may have addressed this.
You answered how to get truck volumes on each.
I'm still confused if a truck OD is available.
We do not create the truck OD.
The answer is no.
[ Indiscernible ].
A conversion is done on the slide.
By the way, the platform we adopted to run our highway analysis is transcat.
We used the assignment procedures in transcat to flow the network.
What are the factors considered in the estimate of 2035 trade flows?
The future forecasts were driven in large part by the forecasts inflated dy global insight when we had them do special runs.
They're a large international trade forecasts.
They feed into the FAF.
It's all of the assumptions that global incites 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 the you know, where the demands are coming from.
Population is a big factor in all of this.
How are in-distribution centers accounted for?
If the shipment, let's say if everything worked properly, if the shipment is going from Asia to L.A. to the regional center in riverside and gets repacked and reshipped inland that is really two separate flows.
An international flow from Asia to L.A.
And then 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 9 U.S.
That is an international move from Asia, to L.A., to Chicago.
The mode is the inland mode.
Because it's in the sea file.
Now admittedly 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.
Did our best to balance against all of those, to figure out, whether materials just went to the coast and were reshipped.
Or if they moved directly all the way.
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.
What level is available for pipeline movements such as petroleum products in the FAF?
It's the same for all modes.
But note we list it as pipe lines and unknown together as a a mode.
The reason is, as a national totals we're comfortable with the pipeline estimates.
When we start breaking it down by region, as anyone knows that deals with this, is a very complicated world.
It was so complicated the commodity flow survey gave up for a number of reasons.
We use estimated techniques.
Used a lot of data from [ Indiscernible ].
But that's why we combine it with unknown.
That's where we are the least, of 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 it's a pretty good estimate.
We know it could be, um, there could be variations.
Since most gee graphic information about pipelines, is at the multistate level.
We're really splicing our pipelines thin to get down to the FAF region to region flows.
FAF regions being much smaller.
The last question, who should we email for state specific data?
That's referring to Michael.
And um, first take a look at the state profiles.
Tianjia pointed them out.
If you don't see the information there, of course, that summary data you can, if you go into the FAF OD database and sort by state you can get all of the flows that go to and from your state by commodity and mode.
If there are some things you thing would be useful summary data that you would like to see in future editions, that you think that everyone would be interested in, by all means email the suggestions to Mike or me.
Let's see if anybody has questions over the phone.
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Okay, I think we'll go ahead and close out for the day.
Um, I wanted to thank Rolf and Tianjia and thank you for you attending.
The recording will be available in the next two weeks.
If you want the follow-up information you can send me an email and let me know, my email is in the chat box at the top.
The next seminar is February 20.
It's a discussion of the updated quick response freight manual.
I encourage you to visit the site and sign up.
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With that, we'll close out.
Thank you, everybody.
Enjoy the rest of your day.