*Apologies for cross-postings
FHWA is establishing a new pooled fund program in support of the next
generation National Household Travel Survey (NHTS). The NextGen NHTS will
integrate passive data with household travel surveys to provide both
long-distance and local travel behavior data on an annual basis. We invite
you to come and learn more about this new pooled fund effort while at TRB:
What: NextGen NHTS Pooled Fund Program Open House
When: Monday 1/8, 1-2 pm
Where: Convention Center Conference Room 302
This pooled fund is designed to bring together agencies considering their
next household travel survey program in order to learn from each other's
experiences to date and design the NextGen NHTS. Pooled fund participants
will identify design elements and benefit from research into critical
questions about the evolution to a hybrid travel behavior data source,
including guidance for evaluating passive data opportunities and
benchmarking results.
Whether you just completed a household travel survey or are actively
researching your 2020 survey program, this pooled fund program will equip
your agency with the research and results needed to meet local and long
distance travel behavior needs on an annual basis. We hope to see you at
TRB!
For more information or to RSVP, contact:
Wenjing Pu, PhD, PE
DOT | FHWA | Office of Highway Policy Information
(202) 366-5024
wenjingpu(a)dot.gov <mailto:wenjing.pu(a)dot.gov>
I'm a demographer in private practice. I used CTPP data when I did a
demographic study for the city of Hartford, CT. I'm familiar with UTPP/CTPP
going back decades, so it's not like I had to discover that the data
existed. But it was very useful for city officials to understand more about
people who work in Hartford, as well as about those who live there.
<https://www.avast.com/sig-email?utm_medium=email&utm_source=link&utm_campai…>
Virus-free.
www.avast.com
<https://www.avast.com/sig-email?utm_medium=email&utm_source=link&utm_campai…>
<#DAB4FAD8-2DD7-40BB-A1B8-4E2AA1F9FDF2>
On Thu, Dec 28, 2017 at 2:55 PM, Benjamin Gruswitz <bgruswitz(a)dvrpc.org>
wrote:
> Some discussion came up at our recent conference in Kansas City about
> earlier days of the program when public sector employees would get data
> request from folks in various private sector industries. The CTPP Board
> Training & Outreach subcommittee wanted to generate an anecdotal list from
> listserv members of who they know using the data--beyond more traditional
> public sector transportation planners and their consultants. This could be
> some non-traditional research area at a university, some more obscure
> public agency use case, or a private sector application. Knowing not only
> who is using it but what they're using it for is always a plus.
>
> Feel free to reply to the listserv or me directly.
>
> Thanks in advance!
> Ben
>
> *Ben Gruswitz, AICP *|* Senior Planner*
>
> Office of Long-Range Planning
> Delaware Valley Regional Planning Commission
> 190 N Independence Mall West, 8th Floor
> Philadelphia, PA 19106-1520
> 215.238.2882 <http:/#> | bgruswitz(a)dvrpc.org <http:/#>
>
> www.dvrpc.org
>
>
> _______________________________________________
> ctpp-news mailing list
> ctpp-news(a)chrispy.net
> https://www.chrispy.net/mailman/listinfo/ctpp-news
>
>
--
Patricia C. (Patty) Becker
APB Associates/Southeast Michigan Census Council (SEMCC)
28300 Franklin Rd, Southfield, MI 48034
office: 248-354-6520
home:248-355-2428
pbecker(a)umich.edu
Some discussion came up at our recent conference in Kansas City about
earlier days of the program when public sector employees would get data
request from folks in various private sector industries. The CTPP Board
Training & Outreach subcommittee wanted to generate an anecdotal list from
listserv members of who they know using the data--beyond more traditional
public sector transportation planners and their consultants. This could be
some non-traditional research area at a university, some more obscure
public agency use case, or a private sector application. Knowing not only
who is using it but what they're using it for is always a plus.
Feel free to reply to the listserv or me directly.
Thanks in advance!
Ben
*Ben Gruswitz, AICP *|* Senior Planner*
Office of Long-Range Planning
Delaware Valley Regional Planning Commission
190 N Independence Mall West, 8th Floor
Philadelphia, PA 19106-1520
215.238.2882 <http:/#> | bgruswitz(a)dvrpc.org <http:/#>
www.dvrpc.org
Apologies for cross posting.
The link to the activities of the NHTS task force (ABJ45T) at TRB 2018 can
be found here: http://rpubs.com/matungawalla/ABJ45T_2018AM
Treats include:
1) Want to know about the 2017 NHTS? - Find out at Session 336
2) Want to know how to visualize NHTS data? - See it at the Task Force
Meeting
3) All you wanted to know about large passive data but were too afraid to
ask :-) - Ask away at Session 403
4) How does Freight interact with Household Travel? - Session 738 might
have some answers.
Happy Holidays,
Krishnan
--
Krishnan Viswanathan
Chair, ABJ45T
NONCONFIDENTIAL // EXTERNAL
Hi,
I'm trying to get 2000 CTPP data at the block group level from the BTS/transtats website for all states plus DC. I cannot find block group level data for D.C., Nebraska, Rhode Island, South Carolina, Texas, and West Virginia. Doe anyone know if these these data are just not available? Or if this is a website glitch? I have not found any information yet that would indicate that the block group level CTPP 2000 data is not available for these 5 states (plus D.C.). Any help will be greatly appreciated.
Thanks,
McKenzie
The series of posts from last week remind me that the idea of estimating “household demographics” based only on observed vehicle types has been around since the 1990s, as planners have tried to figure out whether the actual observed distribution of vehicle types seen on toll lanes are noticeably different from the observed distribution seen on non-tolled roads that offer a viable (but probably slower and/or less reliable) alternative to the toll lanes, and if so what this might mean (statistically speaking) in regards to differences in the likely distribution of household income for toll-road users and non-users. I am not an expert on such matters, so will avoid offering any personal opinions about the “likely statistical accuracy” of such an observation-based analysis, beyond noting that the term “Lexus lane” is often used, and often gets people into some rather contentious point-counterpoint debates about who actually “directly benefits” from the availability of faster and/or more reliable tolled facilities.
Ken Cervenka
From: ctpp-news [mailto:ctpp-news-bounces(a)chrispy.net] On Behalf Of Pete Swensson
Sent: Friday, December 01, 2017 8:27 PM
To: ctpp-news(a)chrispy.net
Subject: Re: [CTPP] The Washington Post: Scientists can now figure out detailed, accurate neighborhood demographics using Google Street View photos
Just an anecdotal observation: Vehicle make and model preferences vary a lot by geography for reasons other than income or demographics. Lots more pick-ups in some parts of the country than others. Subarus ALL have 4-wheel drive, and they are consequently a very popular make in my county. Japanese makes of cars (e.g., Honda) have long been more popular on the West Coast (regardless of ethnicity) than in the Midwest, where there is stronger brand loyalty to American makes manufactured in the Midwest (in theory – many are now made in Mexico).
Even if one accepts the underlying premise of correlating vehicle types to demographics and voting patterns, I think Ed’s suggestion of processing vehicle registration files instead of Google photos is right on target. Much easier. And it wouldn’t surprise me if users of Big Data for political analysis are already doing this.
Pete Swensson
1201 Terrace Lane SW
Olympia, WA 98502
(360) 352-7909 home
(360) 628-6621 cell
pete(a)swensson.us<mailto:pete(a)swensson.us>
From: ctpp-news [mailto:ctpp-news-bounces(a)chrispy.net] On Behalf Of Steve Wilson
Sent: Friday, December 01, 2017 9:04 AM
To: ctpp-news(a)chrispy.net<mailto:ctpp-news(a)chrispy.net>
Subject: Re: [CTPP] The Washington Post: Scientists can now figure out detailed, accurate neighborhood demographics using Google Street View photos
Streetview + ACS can also be used to develop a model estimating likelihood of encountering man on porch yelling “hey you kids – get off my lawn”. :)
From: Polzin, Steven [mailto:polzin(a)cutr.usf.edu]
Sent: Friday, December 01, 2017 10:58 AM
To: ctpp-news(a)chrispy.net<mailto:ctpp-news(a)chrispy.net>
Subject: Re: [CTPP] The Washington Post: Scientists can now figure out detailed, accurate neighborhood demographics using Google Street View photos
Be careful who you let parked in front of your house. It might change your income.
From: ctpp-news [mailto:ctpp-news-bounces(a)chrispy.net] On Behalf Of Scott Ramming
Sent: Friday, December 01, 2017 11:55 AM
To: ctpp-news(a)chrispy.net<mailto:ctpp-news(a)chrispy.net>
Subject: Re: [CTPP] The Washington Post: Scientists can now figure out detailed, accurate neighborhood demographics using Google Street View photos
As I understand it, their models aren’t based on auto ownership levels, but the type and age of the autos parked in view.
There’s a big difference in neighborhoods where you find concentrations of say 2018 Range Rovers versus 1964 Ford Mavericks.
Plus one to Thomas’s point about high density areas where people either don’t own vehicles or park the vehicles they do in garages. The same lack of sample would also apply to where HOAs dictate that all vehicles must be parked in personal garages with the door lowered. Perhaps lack of variation in the paint color scheme could be used as an explanatory variable for such neighborhoods.
Scott Ramming, PhD PE | Senior Travel Modeler | Transportation Planning & Operations
Direct: 303-480-6711 | Fax: 303-480-6790 | Email: sramming(a)drcog.org<mailto:sramming(a)drcog.org>
[2016DRCOG-Logo-Side-PMS.png]<https://drcog.org/>
1290 Broadway • Suite 100 • Denver, Colorado 80203-5606
main: 303-455-1000 • email: drcog(a)drcog.org<mailto:drcog(a)drcog.org> • web: www.drcog.org<http://www.drcog.org/>
[AWARD-email-signiture-V02]<https://drcog.org/annualawards>
[facebook]<http://www.facebook.com/Denver.Regional.Council.of.Governments> [twitter] <https://twitter.com/DRCOGorg> [linkedin] <http://www.linkedin.com/company/denver-regional-council-of-governments?trk=…>
From: ctpp-news [mailto:ctpp-news-bounces(a)chrispy.net] On Behalf Of Alan E. Pisarski
Sent: Friday, December 01, 2017 8:59 AM
To: ctpp-news(a)chrispy.net<mailto:ctpp-news(a)chrispy.net>; 'Ed Christopher' <edc(a)berwyned.com<mailto:edc(a)berwyned.com>>
Subject: Re: [CTPP] The Washington Post: Scientists can now figure out detailed, accurate neighborhood demographics using Google Street View photos
Re auto ownership: it was at one time a pretty good proxie for wealth etc. but vehicles are so ubiquitous now that it is far less reliable. Not far from here in a neighborhood that is largely low/mid income housing the streets are lined at night with white vans that the immigrant painters, home construction guys use. Great area to steal a ladder. Alan
Alan E. Pisarski
alanpisarski(a)alanpisarski.com<mailto:alanpisarski(a)alanpisarski.com>
703-941-4257 landline
703 650-8925 cell
From: ctpp-news [mailto:ctpp-news-bounces(a)chrispy.net] On Behalf Of Krishnan Viswanathan
Sent: Friday, December 01, 2017 10:15 AM
To: Ed Christopher <edc(a)berwyned.com<mailto:edc(a)berwyned.com>>
Cc: ctpp-news(a)chrispy.net<mailto:ctpp-news(a)chrispy.net>
Subject: Re: [CTPP] The Washington Post: Scientists can now figure out detailed, accurate neighborhood demographics using Google Street View photos
Totally agree with you Ed. I think the Washington Post headline is a dose of hyperbole. I have a question about spurious correlations and as far as I know the ACS does not ask what type of vehicle is there in the household so this paragraph in their paper gave me pause:
Using ACS and presidential election voting data for regions in our training set, we train a logistic regression model to estimate race and education levels and a ridge regression model to estimate income and voter preferences on the basis of the collection of vehicles seen in a region. This simple linear model is sufficient to identify positive and negative associations between the presence of specific vehicles (such as Hondas) and particular demographics (i.e., the percentage of Asians) or voter preferences (i.e., Democrat).
On Fri, Dec 1, 2017 at 9:38 AM, Ed Christopher <edc(a)berwyned.com<mailto:edc(a)berwyned.com>> wrote:
Interesting stuff Krishnan--
If their basic assumption were true, that vehicle ownership somehow translates into demographics (ie voter behavior), then why not just cut Google out and process vehicle registration files. It seems to me that would be a lot easier and cheaper. Then again you have to buy the basic assumption. Also, if you look at precinct by precinct voter behavior two things will surprise you. First, precincts are not all one color (red or blue) in most places and the number of people who do vote are very small when considering the total population. While I found this work interesting I would not be out their trying to oversell what its capabilities are without a whole lot more work and research. As I see it we have a very long way to go before we have something that is a kin to the ACS and all its by-products.
On 11/30/2017 8:39 PM, Krishnan Viswanathan wrote:
This will interest people in this group and also foster discussion about the methods used. The article itself has a link to the paper.
Scientists can now figure out detailed, accurate neighborhood demographics using Google Street View photos
http://wapo.st/2AnuP9L<https://urldefense.proofpoint.com/v2/url?u=http-3A__wapo.st_2AnuP9L&d=DwMFa…>
Krishnan Viswanathan
5628 Burnside Circle <https://urldefense.proofpoint.com/v2/url?u=https-3A__maps.google.com_-3Fq-3…>
Tallahassee FL 32312
_______________________________________________
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https://www.chrispy.net/mailman/listinfo/ctpp-news<https://urldefense.proofpoint.com/v2/url?u=https-3A__www.chrispy.net_mailma…>
--
Ed Christopher
Transportation Planning Consultant
708-269-5237<tel:(708)%20269-5237>
--
Krishnan Viswanathan
5628 Burnside Circle
Tallahassee FL 32312
Given the importance of BLS data to the transportation community, it is
critical that we have a seat at the table. If you or anyone you know would
make a good nominee, please nominate them to be part of this committee.
https://www.federalregister.gov/documents/2017/12/06/2017-26224/technical-a…
Thanks,
Krishnan
Re auto ownership: it was at one time a pretty good proxie for wealth etc. but vehicles are so ubiquitous now that it is far less reliable. Not far from here in a neighborhood that is largely low/mid income housing the streets are lined at night with white vans that the immigrant painters, home construction guys use. Great area to steal a ladder. Alan
Alan E. Pisarski
alanpisarski(a)alanpisarski.com
703-941-4257 landline
703 650-8925 cell
From: ctpp-news [mailto:ctpp-news-bounces(a)chrispy.net] On Behalf Of Krishnan Viswanathan
Sent: Friday, December 01, 2017 10:15 AM
To: Ed Christopher <edc(a)berwyned.com>
Cc: ctpp-news(a)chrispy.net
Subject: Re: [CTPP] The Washington Post: Scientists can now figure out detailed, accurate neighborhood demographics using Google Street View photos
Totally agree with you Ed. I think the Washington Post headline is a dose of hyperbole. I have a question about spurious correlations and as far as I know the ACS does not ask what type of vehicle is there in the household so this paragraph in their paper gave me pause:
Using ACS and presidential election voting data for regions in our training set, we train a logistic regression model to estimate race and education levels and a ridge regression model to estimate income and voter preferences on the basis of the collection of vehicles seen in a region. This simple linear model is sufficient to identify positive and negative associations between the presence of specific vehicles (such as Hondas) and particular demographics (i.e., the percentage of Asians) or voter preferences (i.e., Democrat).
On Fri, Dec 1, 2017 at 9:38 AM, Ed Christopher <edc(a)berwyned.com <mailto:edc(a)berwyned.com> > wrote:
Interesting stuff Krishnan--
If their basic assumption were true, that vehicle ownership somehow translates into demographics (ie voter behavior), then why not just cut Google out and process vehicle registration files. It seems to me that would be a lot easier and cheaper. Then again you have to buy the basic assumption. Also, if you look at precinct by precinct voter behavior two things will surprise you. First, precincts are not all one color (red or blue) in most places and the number of people who do vote are very small when considering the total population. While I found this work interesting I would not be out their trying to oversell what its capabilities are without a whole lot more work and research. As I see it we have a very long way to go before we have something that is a kin to the ACS and all its by-products.
On 11/30/2017 8:39 PM, Krishnan Viswanathan wrote:
This will interest people in this group and also foster discussion about the methods used. The article itself has a link to the paper.
Scientists can now figure out detailed, accurate neighborhood demographics using Google Street View photos
http://wapo.st/2AnuP9L
Krishnan Viswanathan
5628 Burnside Circle <https://maps.google.com/?q=5628+Burnside+Circle+%0D+Tallahassee+FL+32312&en…>
Tallahassee FL 32312
_______________________________________________
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ctpp-news(a)chrispy.net <mailto:ctpp-news(a)chrispy.net>
https://www.chrispy.net/mailman/listinfo/ctpp-news
--
Ed Christopher
Transportation Planning Consultant
708-269-5237 <tel:(708)%20269-5237>
--
Krishnan Viswanathan
5628 Burnside Circle
Tallahassee FL 32312
Does anyone know if they looked at how well the model they developed predicted demographics in low car ownership areas like New York City, where less then half of the households have cars? It did not seem like they used any data from the NY area. In built up, high density areas, many of the cars are in structured parking or people do not own cars. On-Street cars may not represent who is living in the area. Same for high density areas in other cities.
From: ctpp-news [mailto:ctpp-news-bounces(a)chrispy.net] On Behalf Of Krishnan Viswanathan
Sent: Friday, December 01, 2017 10:15 AM
To: Ed Christopher
Cc: ctpp-news(a)chrispy.net
Subject: Re: [CTPP] The Washington Post: Scientists can now figure out detailed, accurate neighborhood demographics using Google Street View photos
Totally agree with you Ed. I think the Washington Post headline is a dose of hyperbole. I have a question about spurious correlations and as far as I know the ACS does not ask what type of vehicle is there in the household so this paragraph in their paper gave me pause:
Using ACS and presidential election voting data for regions in our training set, we train a logistic regression model to estimate race and education levels and a ridge regression model to estimate income and voter preferences on the basis of the collection of vehicles seen in a region. This simple linear model is sufficient to identify positive and negative associations between the presence of specific vehicles (such as Hondas) and particular demographics (i.e., the percentage of Asians) or voter preferences (i.e., Democrat).
On Fri, Dec 1, 2017 at 9:38 AM, Ed Christopher <edc(a)berwyned.com<mailto:edc(a)berwyned.com>> wrote:
Interesting stuff Krishnan--
If their basic assumption were true, that vehicle ownership somehow translates into demographics (ie voter behavior), then why not just cut Google out and process vehicle registration files. It seems to me that would be a lot easier and cheaper. Then again you have to buy the basic assumption. Also, if you look at precinct by precinct voter behavior two things will surprise you. First, precincts are not all one color (red or blue) in most places and the number of people who do vote are very small when considering the total population. While I found this work interesting I would not be out their trying to oversell what its capabilities are without a whole lot more work and research. As I see it we have a very long way to go before we have something that is a kin to the ACS and all its by-products.
On 11/30/2017 8:39 PM, Krishnan Viswanathan wrote:
This will interest people in this group and also foster discussion about the methods used. The article itself has a link to the paper.
Scientists can now figure out detailed, accurate neighborhood demographics using Google Street View photos
http://wapo.st/2AnuP9L
Krishnan Viswanathan
5628 Burnside Circle <https://maps.google.com/?q=5628+Burnside+Circle+%0D+Tallahassee+FL+32312&en…>
Tallahassee FL 32312
_______________________________________________
ctpp-news mailing list
ctpp-news(a)chrispy.net<mailto:ctpp-news(a)chrispy.net>
https://www.chrispy.net/mailman/listinfo/ctpp-news
--
Ed Christopher
Transportation Planning Consultant
708-269-5237<tel:(708)%20269-5237>
--
Krishnan Viswanathan
5628 Burnside Circle
Tallahassee FL 32312
Interesting stuff Krishnan--
If their basic assumption were true, that vehicle ownership somehow
translates into demographics (ie voter behavior), then why not just cut
Google out and process vehicle registration files. It seems to me that
would be a lot easier and cheaper. Then again you have to buy the basic
assumption. Also, if you look at precinct by precinct voter behavior two
things will surprise you. First, precincts are not all one color (red or
blue) in most places and the number of people who do vote are very small
when considering the total population. While I found this work
interesting I would not be out their trying to oversell what its
capabilities are without a whole lot more work and research. As I see it
we have a very long way to go before we have something that is a kin to
the ACS and all its by-products.
On 11/30/2017 8:39 PM, Krishnan Viswanathan wrote:
> This will interest people in this group and also foster discussion
> about the methods used. The article itself has a link to the paper.
>
> Scientists can now figure out detailed, accurate neighborhood
> demographics using Google Street View photos
> http://wapo.st/2AnuP9L
> Krishnan Viswanathan
> 5628 Burnside Circle
> Tallahassee FL 32312
>
>
> _______________________________________________
> ctpp-news mailing list
> ctpp-news(a)chrispy.net
> https://www.chrispy.net/mailman/listinfo/ctpp-news
--
Ed Christopher
Transportation Planning Consultant
708-269-5237