The Wrong Side of my Car
The blog that wants to go obsolete
The scale on maps is… quite fluid
Remember when the map was still this huge folded sheet of paper in the door of your car?
By now, that has become yet another thing inside your phone, just like your FM radio, your flashlight, MP3 player, agenda, alarm clock, newspaper. Maybe not that FM radio anymore, but you get the idea.
Even though that old paper map and this map inside your phone come from the same reality, they are not quite the same. Below is a modern slippy map (I picked OpenTopoMap, based on OpenStreetMap data *1) and the stuff that used to be printed on the Michelin paper maps.
Can you spot the differences?
The isthmus buses really are better
I often tell people that there is one little corner in Auckland with an existing functional public transport network: the western half of the isthmus. That’s it. Usually the response from public transport advocates lies somewhere between derision and bewilderment. I find this odd, because this is completely obvious if you just look at a bus map.
Cycling Hill Misery Index
A few years ago I moved from Milford to Birkdale, and I have always felt that in Milford I could easily get around on a bicycle, whereas in Birkdale an acoustic bicycle is pretty much useless. It is really hilly.
So here I introduce the Bicycling Hill Misery Index, an estimate of how annoying hills are. A value of 0.0 means flat as a pancake. 1.0 means an area is so hilly that it doubles the effort required to go the same distance. By looking at the slopes of streets, we can put this on a map.
Apartment living: disadvantages only
A while ago I made an interactive version of the population density map on Observable, and I noticed something.
What do street name suffixes like “street” or “avenue” mean?
After living in a suburb for a while you get used to streets being randomly tagged as ‘Street’, ‘Road’, ‘Avenue’, or others. Here’s a top 10 for Auckland. *1
| Street type | amount | |
|---|---|---|
| 1. | Road | 3809 |
| 2. | Place | 2491 |
| 3. | Street | 1853 |
| 4. | Avenue | 1439 |
| 5. | Drive | 977 |
| 6. | Lane | 521 |
| 7. | Crescent | 483 |
| 8. | Way | 285 |
| 9. | Terrace | 227 |
| 10. | Court | 225 |
How do you choose a type? Do they just choose a random one for each street? It looks like it for sure.
But these words actually have distinct meanings.
Unique street names counted in the area covered by the maps I generated from the census data.
The cycling dot map
After tinkering with these maps for a while, it struck me that the cycling mode share is low enough to visualise the census data directly.
Census 2018 mode shares
With the travel data out for the census, we can now make our cycling modeshare GIF. Purely for posterity — the COVID-19 crisis has made all of this pretty much obsolete.
Census 2018: population density
Last year (2018) there was a census, and after a long and turbulent process, the data is now gradually being released to the public.
One of the data tables already available is about population by Statistical Area 2 (formerly known as Area Units). In general over here these are areas of about a kilometre across, with a few thousands of people living in them.
The estimated population was given for the previous census years as well (2006 and 2013) so of course we are going to make a GIF. *1
Is driving for the rich too?
After creating that cycling mode share map, why not get them for other ways to get around as well? *1
First, walking:
Is cycling for the rich?
An argument often made against bicycling is that is only for the rich, and investment in bicycling infrastructure is thus a regressive measure. A casual glance at success stories seems to confirm this. Grey Lynn. Point Chevalier. Belmont. If you want to live there you and your significant other had better both get a 6 figure salary.
Is that impression correct? One way to get an idea is to look at census data. One of the questions asked is how you get to work. This is not a perfect measure (more local errands like shopping or going out are often more feasible on a bike than commuting), but it should give us an idea of where cycling is popular.
Making the relief map: the base
If you download a DEM it looks roughly like this:
By itself, visualizing relief as a greyscale image has an advantage: the eye is quite sensitive to changes in brightness, making it a good choice if you want to discover fine details in the image. But I wanted to overlay a street map over the relief, and doing this in a clear manner is really hard if the background varies between black and white.
So what I want to do is 2 things:
- Turn the height into a color map,
- add relief shading to emphasize local relief.
1m DEM
Last time, one of the questions was, which digital elevation model (or DEM) should I use. Initially I worked with the relatively low-resolution DEM derived from the 20m contour lines.
Of course, Auckland Council has had a 1m DEM derived from lidar data for a while. There’s also a digital surface model, which doesn’t follow the ground level, but which models the ‘surface’ visible from above. You’ll see the buildings and tree tops on that one.
I made a map: relief in Auckland
And now, back to that other interest of me: maps.
One of my favourites is maps showing the relief in the landscape. There’s the relief shading in Google’s terrain maps, or the height contour lines on topographic maps. But I find both hard to interpret. While both are good at showing the local relief, it’s difficult to make out the bigger picture. What I wanted was a map which uses a simple color map to represent elevation.
Let’s make one.
