30 Day Map Challenge 2019

Last November I took part in the 30 Day Map Challenge. An excellent project suggested by Topi Tjukanov on twitter:

I perhaps had a bit of an advantage. I had already completed a very similar challenge in 2014. Mapvember.

Where I made a post on this blog every day for all of November, primarily maps.

Where I made a post on this blog every day for all of November, primarily maps.

And a summary:
https://gisforthought.com/mapvember/

There are a lot of advantages to this style of map creation and a few down sides.

Advantages

  • It puts a time limit on the maps. This forces you to put them out there no matter the status. It is easy to leave maps half finished because they are not perfect. I know the internet can be a harsh critic sometimes, but you are making a map a day, it won’t be perfect.
  • You can revisit some older maps that have been discarded in the past. Perhaps they didn’t look so good, weren’t so interesting. That doesn’t matter, you are posting a map a day they don’t have to be perfect.
  • There are a lot of ideas out there. I use a Google keep note to store map ideas I have. The list keeps on getting longer and without some pushing it never gets shorter.
  • Collaboration. There were some great maps made, and every day you could enjoy them as well, feeling part of the community. Sharing ideas and techniques.
  • Increase your talents. The only way you are going to get better at mapping is by making some maps. No better way to do it than pushing yourself.
  • Work with new data. 30 maps is a lot of maps. You can explore new datasets and new software.
  • Grow your following. As the challenge is on Twitter it is a good way to build your following. I got 139 new followers over the month. Now for some people that isn’t much. But I only have 600 in general so it’s a sizeable amount. Although I’m not sure there is that much value to followers. But 197k impressions is good? 1 follower per 1000 who saw a map.

Disadvantages

30 maps is a lot of maps to make. A day is a short time to make one. My tactic, based on my previous experience, was to make a few upfront and ready to go. So by the time November started I had a few maps ready, so I could be ahead of the curve.

I used tweetdeck to schedule the tweets. I didn’t map on the weekend for the most part. I had other commitments, so scheduling and making some easy maps was crucial to completing the challenge.

There are no real rules to the challenge, interpret it how you wish. Do a map a day, or a map a week, but the important part is enjoying it.

Maps

There is a great website that collects all the maps created by theme and creator:

https://david.frigge.nz/30DayMapChallenge/index.html

I have posted all of my maps here.

With a select few favorites:

Day 1Points – Ireland’s population mapped as one point per person. 6,572,675 points in total:

Day 2Lines – 1 week of flying for Ryanair EI-DYP Boeing 737-800:

Day 5Raster – Total rainfall in Ireland in 2018 from Met Eireann data:

Day 10Black and White – Register of renewed liquor licences: Publican’s Houses Dublin:

Day 19Urban – Perhaps Dublin’s most confused street:

All in all I whole heartedly recommend taking part when November rolls around again.

Every Person in Great Britain Mapped

A follow up to my previous post: Every Person in Scotland on the Map. Winner of the 2016 OS OpenData Award for Excellence in the use of OpenData from the British Cartographic Society.

Full size interactive map.

The mapping process is pretty straightforward, and not accurate. I don’t know where you live. But I can make an educated guess.

I simply amalgamate the two sets of census data from the NRS (National Records of Scotland) for Scotland (2011 census) and the ONS (Office of National Statistics) for England and Wales (2010 census).

Postcodes were then created based on the ONS Postcode Directory, filtering for postcodes that were live in 2011 (which is the latest census data). The postcode centroids were turned into polygons using voronoi polygons.

Then we simply select all of the buildings in a postcode from Ordnance SurveyOpen Map product, filtering out most schools and hospitals. Then we put a random point in a random building for each person in that postcode.

I would have loved to include Northern Ireland, but the Ordnance Survey of Northern Ireland do not have an equivalent open building outline dataset, like Open Map from the Ordnance Survey.

Rendered with: QGIS tile writer python script. Processing done 100% in PostGIS.