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@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@swensson.us<mailto:pete@swensson.us> From: ctpp-news [mailto:ctpp-news-bounces@chrispy.net] On Behalf Of Steve Wilson Sent: Friday, December 01, 2017 9:04 AM To: ctpp-news@chrispy.net<mailto:ctpp-news@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@cutr.usf.edu] Sent: Friday, December 01, 2017 10:58 AM To: ctpp-news@chrispy.net<mailto:ctpp-news@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@chrispy.net] On Behalf Of Scott Ramming Sent: Friday, December 01, 2017 11:55 AM To: ctpp-news@chrispy.net<mailto:ctpp-news@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@drcog.org<mailto:sramming@drcog.org> [2016DRCOG-Logo-Side-PMS.png]<https://drcog.org/> 1290 Broadway • Suite 100 • Denver, Colorado 80203-5606 main: 303-455-1000 • email: drcog@drcog.org<mailto:drcog@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=cp_followed_name_denver-regional-council-of-governments> From: ctpp-news [mailto:ctpp-news-bounces@chrispy.net] On Behalf Of Alan E. Pisarski Sent: Friday, December 01, 2017 8:59 AM To: ctpp-news@chrispy.net<mailto:ctpp-news@chrispy.net>; 'Ed Christopher' <edc@berwyned.com<mailto:edc@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@alanpisarski.com<mailto:alanpisarski@alanpisarski.com> 703-941-4257 landline 703 650-8925 cell From: ctpp-news [mailto:ctpp-news-bounces@chrispy.net] On Behalf Of Krishnan Viswanathan Sent: Friday, December 01, 2017 10:15 AM To: Ed Christopher <edc@berwyned.com<mailto:edc@berwyned.com>> Cc: ctpp-news@chrispy.net<mailto:ctpp-news@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@berwyned.com<mailto:edc@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-3… Krishnan Viswanathan 5628 Burnside Circle <https://urldefense.proofpoint.com/v2/url?u=https-3A__maps.google.com_-3Fq-3D5628-2BBurnside-2BCircle-2B-250D-2BTallahassee-2BFL-2B32312-26amp-3Bentry-3Dgmail-26amp-3Bsource-3Dg&d=DwMFaQ&c=euGZstcaTDllvimEN8b7jXrwqOf-v5A_CdpgnVfiiMM&r=hPWPlrrP3ltC4p6xf2M1dSXBtZJFDefT0j92MuY91_U&m=OaFuPnt5_e2qlw7V0mqAXMDxcY9jvm14ieUs7u8VTHg&s=X9IQwhkjhUp3KPbDhFnQsh7aVTisGC8B-W0mm4gcIGA&e=> Tallahassee FL 32312 _______________________________________________ ctpp-news mailing list ctpp-news@chrispy.net<mailto:ctpp-news@chrispy.net> https://www.chrispy.net/mailman/listinfo/ctpp-news<https://urldefense.pr… -- Ed Christopher Transportation Planning Consultant 708-269-5237<tel:(708)%20269-5237> -- Krishnan Viswanathan 5628 Burnside Circle Tallahassee FL 32312