Making a map

As mentioned before, I am interested in producing a free/non-copyrighted map of Edinburgh. There are several reasons for this, but the main motivation is ideological. Information about the city I live in ought to be free. It’s *our* city. Information about our city ought to be a public asset. The Ordnance Survey keeps a very tight hold on its data, and charges lots of money for it, despite being a department of our own government. This situation is unlikely to change, unless some crazy geeks bypass the whole establishment and produce their own (totally non-derived) map data. That’s the ideology.

The second reason is more pragmatic. If I want to find where someone lives, I can look at multimap. However, if I’m writing trying to write a route-finder computer program then I need the data about roads/junctions in a form which my program can process. Multimap doesn’t help me with this. So, a secondary benefit of producing a map myself is that I can annotate with with metadata (like, streetname, one-way status, steepness of hill) in a form that a computer can understand. Additionally, any other location-related computerized data sources (such as postcode regions, location of wifi hotspots, or pollution measurements) can be meshed together with the map data.

There are three methods that can be used to produce a map. The classical way is to perform laborious ground surveys. That’s soo yesterday! The more modern way is to use satellite imagery or aerial photographs as a starting point, and trace roads/buildings manually or with computer assistance. While high-res satellite imagery is available to the public, it’s expensive and so I discounted that option (for now). The third option, which I’m looking at just now is to use a handheld GPS system and gather trails as I walk/cycle/motorbike around the city.

I wasn’t sure how well GPS would work in the city. There are a number of GPS satellites orbiting around the earth, each broadcasting a time signal. If your handset can see enough of these satellites, it can figure out its longitude and latitude to some degree of accuracy. In the open, accuracy is typically to within 10m, but in a city you often don’t have a good view of the sky and accuracy suffers. An accuracy of 10m doesn’t sound great, but consider that most roads are probably 10m wide so it’s not too bad.

So, I borrowed my brother’s Etrex GPS system and carried it around as I travelled round the city. The GPS handset shows you a graphical view of where you’ve been, and this was enough to confirm that GPS probably did work well enough in the city.

Next step was to get the data onto my PC for processing. GPSbabel took care of downloading the data from the handset into GPX, which appears to be the preferred interchange format for GPS data. I then converted this into the shapefile format, which is a format for vector data commonly accepted by GIS systems. GIS systems are usually hulking great beasts of software, designed to slurp in terabytes of satellite imagery, vector roadmaps, elevation data and the like, and allow you to query it efficiently. However, many GIS systems are obscure and have a steep learning curve. After looking through lots of options, I settled on the JUMP project as being the most hopeful candidate. It happily imported my raw shapefile/GPS data, and I was able to generate a simple map layer from the data and annotated the roads with attributes like “steetname”.

And so …. *drumroll* … here is the beginings of what will hopefully turn into my free Edinburgh streetmap.

Now, there are still some issues to be resolved here. The map data has been sheared at some point on its journey into the JUMP system. If you are familiar with Edinburgh, you’ll know that the roads which join Princes St should all join at right-angles, which isn’t the case in the above map. I imagine that there’s some disagreement about coordinate systems somewhere. The cause will doubtless be blindingly obvious after I’ve figured out what is going wrong, but this is all part of the learning curve.

So, this represents a pretty succesful spike solution. I’ve done a pretty minimal amount of work to establish that the GPS method works, and that the software exists to allow me to make a pretty reasonable map. Now, I might actually start gathering data a bit more seriously, and see about organising a bit of infrastructure to allow other similarly minded people to contribute GPX trails of their own. I’ll also see about integrating SRTM elevation data (which was gathered on a space shuttle mission) to provide height data – although it’s only on a 100m grid, and the presence of tall buildings will cause problems.