ICYMI – Week of July 21, 2017

 

  • Bloomberg reports that London’s housing prices have flat-lined. The article puts forward quotes from several authorities on real estate economics, but the gist of it is that housing prices went well beyond normal ranges in the last few years and are slowing to “normal” levels. In another article, Bloomberg reports that luxury properties are taking a hit as well.
  • In the realm of today’s infrastructure that will be obsolete tomorrow, consider gas stations. We all envision a world of autonomous electric vehicles, so what happens to the gas stations? Likely they’ll be redeveloped and reclaimed by the city, or become electric charging stations, but in the meantime, how about art?
  • Consumer values are crossing geographic boundaries, as marketers are increasingly seeing similar tastes and preferences in demographic cohorts in a globalized world. I suppose this is something new for marketing, but in broader demographic analysis I always found it frustrating how these cohorts/categories are made. “Millennial” preferences really just refer to things young people do, and whether one is young (in terms of tastes and preferences) is increasingly more a product of one’s life stage than age. Single 35-year-olds share more in common with single 25 year-olds than coupled 35-year-olds, and the same applies in the other direction. Tastes and preferences are more influenced by major life events than people realize.
  • The Guardian took a brief look at the “future gazing industry” (that includes people like me) and how it’s grown in the recent past. I really enjoy the process of forecasting and the insights it brings. People mistakenly assume it’s some black-box calculator when in fact it’s just a way of doing research and synthesizing information, together with a healthy dose of probability analysis. Something to really appreciate about this work, though, is how a good forecast has less to do with fancy insights and mathemagic (of the sort pundits become famous for) but more for its ability to build consensus. There’s a lot to say, but I should save it for a separate post.
  • In light of the many measures the Province of Ontario is taking to cool the housing market here, some rather interesting measures are being proposed in California. The state, particularly the San Francisco Area, has seen housing prices skyrocket in the last several years. In the face of a major affordability crisis, homeowners are facing off against municipalities and those who have been priced-out of the market in a battle between maintaining character and increasing densities and housing supply (sound familiar?). This is an interesting echo of what is happening in the GTA, though Ontario is contemplating amending the OMB to give local communities more say, while California is contemplating a fast-track process for affordable housing developments that will circumvent the rezoning process.
  • Not content enough with selling books, electronics, knick-knacks and soon fresh produce, Amazon is allegedly moving into online residential real estate services. The page which tipped GeekWire off has been taken down, but it would be an interesting move at a time when the realtor industry is rapidly digitizing (from searching for properties online to doing property showings on Snapchat and Instagram).
  • More exciting news as Elon Musk tweeted that he has “verbal” approval to start digging a tunnel between New York and Washington D.C. Initial thoughts on it sound like a legitimate test for his tunnel boring project as well as the Hyperloop. I’ve been very skeptical that the Hyperloop really was anything more than a pipe dream, but Musk has accomplished some rather extraordinary things since he got into the transport business, so I’ll remain cautiously optimistic.

Procedurally Modeled Cities

Procedural modeling of cities is a topic that’s been on my mind for a while now. In my day job, I spend a lot of time doing market and policy research in order to inform population and employment forecasts undertaken for land use and infrastructure planning. Whenever I talk to people about my work, I get the sense they assume I spend my day adjusting knobs on a giant black box that takes in one set of numbers and spits out another. This couldn’t be farther from the truth (and I would love it if it were that easy).

What is procedural modeling of cities? It’s an algorithmic process to create a visual model of a city based on a set of rules and relationships.

How does forecasting relate to procedural modeling? Because that’s essentially what we do when we forecast; we try to model how a certain region or city will grow based on a set of rules and assumptions. Procedural modeling may give us a platform with which to visualize our forecasts beyond the standard tables and graphs. It has the potential to physically illustrate the effects of various policies (dependent on responsible analysis).

Hold the horse right here in case you have no clue what I’m talking about and need some background info. I’ll admit this paper has been sitting on my “to-read” pile for a very long time and I still haven’t really dug into it to get to the technical bits and bobs. I’m mostly fascinated with the idea itself and its potential applications (the technical bits can be explored later if I actually pursue a project).

In the general public’s eye, the products are mostly visible in video games. Take Sim City – it essentially accomplishes the same thing but puts you in control of the shape and form (based on that set of underlying rules and relationships between different variables). Use of procedural modeling in games was limited to closed systems due to technological constraints for the longest time (or how much data your computer could handle) but with the recent release of No Man’s Sky we can safely say the sky is the limit (applause).

The potential for application beyond games is huge. With the onset of virtual reality and augmented reality (more important for what I’m thinking of), using procedural modeling to give people a taste of how their cities could grow can be a real game-changer. So much of how we try to present visions of the future to at public consultation relies on the limits to each person’s own imagination (and many people come with preconceived notions that are hard to overcome). Having such an immersive tool to show people how much, or how little, a potential project could change the urban fabric would be invaluable.

Of course it’s not all fun and games and rose-coloured glasses. Any number of nefarious characters could use the same means to turn public opinion over to their darker, more self-serving side. So take my excitement with a grain of salt.

However, it could still be an interesting way to approach scenario planning and policy analysis. Instead of trying to guess how a particular policy or strategy may play out, we could try to visualize it directly through modeling. In order to do it effectively, though, will require us to really test and come to agreement about the types of relationships and their thresholds between different socioeconomic variables that affect land use and infrastructure. We would also need to do a better job of collecting the relevant information in a format that’s consistent throughout time. Right now a lot of the physical features are pulled out of satellite imagery, which may work for things like games or entertainment, but not for serious policy analysis.