Mountain Doodles

spare time data, analysis, visualization

Trick-or-Treat 2016

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A year ago, as were were just getting CensusMapper up and running, we put out three Halloween-themed census maps. Those maps almost broke our servers when they went viral. At least as viral as census data goes. They were viewed by over 150,000 Canadians over the course of three days. And many of those came back to view the maps more than once.

Lots of things have happened at CensusMapper since last year, and we heeded the call and put some of CensusMapper’s prowess to use to make some important improvements for this Halloween.

Secondary Suites and Taxes

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A couple of weeks ago I started thinking about secondary suites, laneway houses and taxes in the City of Vancouver. The number of secondary suites and laneway houses has been continuously growing. Rental income is probably one of the main reasons people choose to activate a secondary suite. What are the tax implications?

Sea Level Rise

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Sea level rise comes up regularly in coastal cities. And nowadays every costal area, including Vancouver has their flood assessment and detailed plans on how to deal with sea level rise, although some plans are more interesting than others.

The web is awash with sea level rise maps, some static, some interactive, some global ones and some national maps. Data sources range from high detail LIDAR data to satellite data and other datasets. When Mapzen put out their global elevation tiles I gave it a quick test drive to check it out and then forgot about it. When the topic inevitably bubbled up on my twitter feed I decided to do some minimal styling using Mapzen’s ridiculously easy to use Tangram map engine and added a search bar to make it easier to jump to different locations on the globe.

That’s all there is to this. Check out yet another interactive global seal level rise map.

The preset for the sea level rise is 10m, which is a little excessive. Current predictions hover around 1m until 2100. Adjust the slider to see how the flooded areas change depending on the simulated sea level rise.

The map is global, and it’s worthwhile to compare Vancouver’s sea level threat to that of other places, for example Holland where 21% of the country is below current sea level, not counting any future sea level rise.

Measuring Housing Affordability

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Housing affordability is a serious issue that deserves attention. Affordability is generally defined comparing incomes to housing costs. And ideally also factoring in transportation cost, although that’s seldom done and we will not attempt today.

Recently we took a detailed look at income data. Using what we learned, together with our detailed data on the development of prices of single family properties in Vancouver, we turn to the never dying question of affordability of single family homes.

Quick Guide to Income Data

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The news media has an extraordinarily difficult time with income data. And that’s only partially the media’s fault. In general, income data is a funny beast. So I decided to give a quick overview over income data that’s available through Statistics Canada. To make things a little more concrete I focused on Vancouver as an example, but everything applies equally well to any other area in Canada.

Most journalists I talked to care about accurate and relevant statements. If that’s you, you will need to keep reading and dive down the slightly wonkish income rabbit hole.

For those that don’t really care, I made a quotable random income generator. Just hit the “generate” button copy & paste the result and link this post as source. (Use at own risk!)

Mobi Running Stats

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I keep getting questions about Mobi stats these days. Rather than ansering them one by one I decided to just offer a live view into data generated by our shadow API. I made two simple views, the most recent month of daily bike checkout counts and the most recent week of hourly bike checkout counts. The data issues mentioned in our previous post still apply. For data geeks, here is a link to a very useful paper that compared estimates like I make to real usage data.

Mobi – a First Look

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Vancouver finally has a bikeshare system. And everyone is hoping it will succeed, despite the obstacles BC’s mandatory helmet law poses for the system. So we are eager to find out how things are going with Mobi.

To set the background, consider that Seattle’s Pronto is getting less than 1 ride per bike per day after half a year in operation. In comparison, bike shares that are considered ‘successful’ in North America get 3 to 5 rides per bike per day. Taipei’s system, which I am particularly fond of, gets over 11 rides per bike per day.

So how about Mobi? It barely started, and it’s not really fair to run the numbers right now. But we just couldn’t hold our curiosity back.

What’s Up With RT?

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RT is Vancouver’s zoning for duplexes. Over time, various areas have been zoned to allow duplexes. Examples are Kits Point, much of Point Grey Road reaching up to Broadway, much of Granview-Woodlands, parts of Mount Pleasant and many other areas.

Recently I have had some interesting conversations on Twitter regarding RM-6 and over BBQ dinner about RT-7. Then the Granview-Woodland plan passed by council, and it contains a curious provision of reducing the outright FSR for the RT-zoned properties from 0.6 to 0.5.

All of which got me thinking. What is RT supposed to accomplish, how does the diverse RT-zoning rules influence development and how is RT overall performing?

Bike Share Map

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It is no secret that we at MountainMath like bikes. And maps. And open data and sharing. We guess you know where this is going.

Vancouver has finally gotten a bike share system, and we are loving it. So we took the occasion to take our old bike infrastructure maps, polished them up a bit using Mapzen’s bike map style and adapted it for our purposes.

The result is our Vancouver Bike Share Map. (Fair warning. While this map works great on your iOS and Android phone, it may not work on old desktop computers.)

Add it to your phone home screen, and it will be right at your fingertips when you need it!

Mixing Data

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Census data is very rich and with CensusMapper we now have about 1 billion data points right at our fingertips. And we have managed to open up some of our interfaces for everyone to explore data and make their own maps and freely share them.

Things really get interesting when one mixes custom data with census data. While, at this point, these are not part of the freely available CensusMapper functionality we still wanted to share what can be done.

At CensusMapper we have developed three basic ways to rapidly mix custom data with census data. So this is really three blog posts in one.