Yes, of course there is obviously some correlation between demographics and car ownership. But this paper makes it seem that their method is good to replace a in-the-field census.
Basically, replacing all demographic data that the census brings with the single factor of car ownership. In the region where the actual correlation is less than 90%, the data generated is completely useless.
> But this paper makes it seem that their method is good to replace a in-the-field census.
Ah, I missed that, sorry! To be honest I only skimped through the description, for other lazy people like me here's the relevant line:
> Our results suggest that automated systems for monitoring demographic trends may effectively complement labor-intensive approaches, with the potential to detect trends with fine spatial resolution, in close to real time.
which I also find as a little bit crazy.
Otherwise I find the project quite interesting. I quite like to lose (too much time) on GStreetView, and at the same time I developed an interest in 20-30-40-year old cars, so I wrote a small Chrome extension that allows me to locally save images of old cars that I find on my country's roads while "taking a walk" on GStreetView, along with the relevant info (lat-lng, address, and the make and model of the cars which I input by hand using said extension). I had also noticed that there's a distinct correlation between a city's economic status and the cars you can find on its streets, and I was wondering how hard would it be to do the car "recognition" using some AI-thing and try to draw some conclusions from that. Glad that someone actually did it.
Basically, replacing all demographic data that the census brings with the single factor of car ownership. In the region where the actual correlation is less than 90%, the data generated is completely useless.