Tag: mapping

• New York and Toronto population densities compared

  Today I came across this Reddit talking about how few census tracts there are in the United States with a population density greater than 150,000 people per square mile. 

  Basically, there’s a bunch in New York, one in San Francisco (Tenderloin), and one in Chicago that doesn’t really count because it’s an unusually small tract. Most other American cities don’t even come close.

  Looking at this New York Times mapping of the 2010 US census data, it turns out there are neighborhoods in NYC that go well beyond 150,000 people per square mile. Here’s one census tract (#154) at just over 200,000 ppsm:

  

  If you convert 200,764 into the globally accepted standard for measuring distances and areas, you get approximately 77,515 people per square kilometer. Pretty dense.

  As a comparison, I thought I would see how this number stacks up against what is commonly referred to as the densest neighborhood in Canada: St. James Town. 

  If you pull up that geographic code in the 2011 Canadian census data (#5350065.00 in case you’re that nerdy), you’ll see a map boundary that looks like this:

  

  And you’ll also find a 2011 population density of approximately 60,915 people per square kilometer. Also pretty dense – though the population did decline from 2006.

  Now obviously St. Jamestown is only one example. The rest of the city is, by and large, far less dense. But maybe when our 2016 census data gets released next year, we’ll find that we’ve become even denser. I suspect we will.

  2016.12.22

• The functional economic geography of the US

  PLOS One recently published a paper and a set of maps that looks at commuter flows across the United States (over 4 million data points). The objective was to identify all of the country’s “megaregions.”

  Here is one of those maps. I think it says a lot.

  

  We often think of cities as having discrete boundaries and population counts, but the reality is that studies and maps such as these provide a much better sense of the overall economic geography of a place.

  It’s worth noting that the commuter dataset used for this study is from 2006-2010. So things may look a bit different today. The full report can be found here.

  2016.12.08

• Mapping of global migration

  Max Galka has created an incredible visualization of country-to-country net migration (from 2010 to 2015) on his blog, Metrocosm.

  Here’s a screenshot:

  

  But you really need to view the full screen interactive version. 

  In that version, you can hover over a country to see the total net migration number (+/-) and you can click on a country to see where people are moving to and from. A blue circle indicates positive net migration (greater inflows) and a red circle indicates negative net migration (greater outflows).

  All of the data is from the United Nations Population Division. And though the numbers are estimates, it’s a fascinating look at global migration. For instance, look at the outflow from Syria.

  It would also be interesting to see these numbers on a per capita basis because some countries certainly punch above or below their weight in terms of migration. Off the top of my head, I’m thinking of Canada and Australia vis-à-vis the US.

  2016.07.06

• Crowdsourcing unsafe cycling conditions with a small yellow handlebar button

  Hövding – a Swedish company best known for its radical airbag cycling helmets (definitely check these out) – is currently crowdsourcing unsafe conditions and cyclist frustration in London.

  Working with the London Cyclist Campaign, they distributed 500 yellow handlebar buttons. Cyclists were then instructed to tap these buttons whenever they felt unsafe or frustrated with current cycling conditions. 

  Here’s what the button looks like:

  

  Every time the button is hit, the data point gets logged to a public map and an email gets sent to the Mayor of London reminding him of his promises around cycling. Both of these things happen via the rider’s smartphone.

  Here’s what the public map looks like at the time of writing this post:

  

  Not only does it tell you pain point locations, but it also seems to suggest the primary cycling routes. I think this is a brilliant initiative because, it’s entirely user-centric. It’s telling you how people feel on the ground.

  Supposedly, Hövding is actively looking for other cyclist groups around the world to help them distribute their buttons. So if you’re a group in Toronto or in another city, I would encourage you to reach out to them. The more data the better.

  2016.06.15

• Residential population densities compared

  The following diagrams were taken from LSE’s Urban Age website. I’ve sorted them from lowest to highest peak residential population density. In each case I’ve also included the year of the dataset. 

  It’s amazing how much these simple extrusion diagrams can tell you about the city. It also shows you that high population densities don’t necessarily need to equate to tall buildings. Barcelona, in particular, stands out for me.

  Berlin (Peak residential density: 21,700 people/km2, 2009)

  

  Stockholm (Peak residential density: 24,900 people/km2, 2012)

  

  London (Peak residential density: 27,100 people/km2, 2013)

  

  São Paulo (Peak residential density: 29,380 people/km2, 2009)

  

  Mexico City (Peak residential density: 48,300 people/km2, 2009)

  

  Barcelona (Peak residential density: 56,800 people/km2, 2013)

  

  New York (Peak residential density: 59,150 people/km2, 2012)

  

  Shanghai (Peak residential density: 74,370 people/km2, 2011)

  

  Istanbul (Peak residential density: 77,300 people/km2, 2013)

  

  Hong Kong (Peak residential density: 111,100 people/km2, 2013)

  

  Mumbai (Peak residential density: 121,300 people/km2, 2013)

  

  2016.03.12

• A breakdown of land use in Vancouver

  Last night when I was thumbing through Twitter before bed, I came across this blog post describing Vancouver’s land use types. The blog itself is called Mountain Doodles, but it’s not exactly clear who the author is. 

  In any event, what she/he did was analyze Vancouver’s land use dataset to come up with a series of charts that break down the percentage of each type: residential single detached, residential low-rise apartment, commercial, green space, and so on.

  Here’s what the chart looks like for Metro Vancouver:

  

  And here’s what it looks like for just the City of Vancouver, proper:

  

  When you look at the metro area, green / open space dominates. Although, the author states that, given the dataset, there could be a small overstatement of green space. There’s also the question of where the overall boundary was drawn.

  When you look at only the City of Vancouver, it’s land for residential housing (detached and duplex) and roads that dominate, with green / open space coming in a somewhat distant third.

  Of course, this does not speak to the intensity in which any of the above land might be used, such as the apartment lands (i.e., the third dimension). But from a two-dimensional perspective, you certainly get a sense of what we – for better or for worse – have chosen to privilege.

  2016.03.02

• Dimensioning pedestrian happiness

  The area that stretches between the property line on one side of a street and the property line on the other side of a street is called a public right-of-way here in Toronto. It may be called something different in other cities and countries.

  In the example below (taken from Toronto’s Avenues & Mid-Rise Buildings Study), it includes the sidewalks, the car lanes, and the streetcar lanes. But it could also include other public elements. In this instance, the buildings on either side of the street are assumed to be built right up against their property lines.

  

  ROWs obviously serve an important public function. But their size also has important urban design implications. As a pedestrian, it feels different to walk on a narrow street than it does on a broad street.

  The width of a ROW can also be used to inform what the preferred height of the buildings along it should be. In the example above, they’re talking about a 1:1 relationship between the width of the ROW and the preferred height of the buildings.

  Given their importance, I thought it would be interesting to share this map of Toronto (dated 2010) showing ROW sizing throughout the city. The mustard colored lines in the core of the city represent 20 metres, the red lines 36 metres, and the purple lines 45 metres or more. The rest of the colors fall somewhere in-between. For the most part, the purple lines represent highways, although there are a few other instances of purple.

  

  What’s interesting – but not surprising – to see is how we basically kept expanding the size of our ROWs as Toronto grew outwards. This was obviously to make more room for cars on the road.

  But the other, perhaps more interesting thing about this map, is that it could also serve as a guide to pedestrian happiness. The mustard/yellow lines are where it’s most enjoyable to walk. And the red and purple lines are where it’s least enjoyable to walk.

  If you’re from Toronto, give this framework a try and see if it holds true.

  2014.09.23

• Mapping where people run

  I’ve been meaning to write this post for about a week now. I stumbled upon a set of maps via FlowingData that used public running data to plot where people run in various cities around the world. And since I love maps, I couldn’t resist.

  Here’s Toronto:

  

  Here’s New York:

  

  Here’s San Francisco:

  

  And here’s Philadelphia:

  

  For the full set of maps, click here.

  What’s interesting is how people tend to gravitate towards the water rather than the parks. In the case of Toronto, High Park is barely touched, which may have something to do with the fact that it’s too far from downtown. The data could also be skewed based on the type of people who make their running data available and where they happen to live.

  Either way, a neat set of maps.

  2014.02.12

• Florence vs. Atlanta [Mapping]

  As I was browsing Tumblr this morning, I came across this image (linked from Quora):

  

  On the left is portion of Florence. And on the right is a single highway interchange in Atlanta. Both maps are at exactly the same scale.

  It’s a stark reminder of how varying land use patterns can be. On the left you have a dense and walkable city, and on the right you have an area that would be entirely inhospitable to pedestrians.

  2013.11.13