- All roads lead to my home (at least in Paris) [ HD 14016×9599 / 7.3MB ]
- The Amazon river / Rio Amazonas with all its tributaries [HD 11962×7625 / 3MB]
- Eastern European Railway (from Paris) [ HD 29255×9624 / 10.8MB ]
- World Flights (from Paris) [ HD 17900×6600 / 17.72MB ]
I was fascinated by the project "Roads to Rome" by Moovellab but sad that it isn’t opensource. Helped bythis project (thanks @tristramg ) I started to build my own map.
I did not have any GIS background but it was very interesting to discover what we can do with. The code isn’t very good (I’m not a C++ guru ).
The project is named " Dijkstra Cartography " but sometimes BFS algorithm is better (if all the edges have the same weight).
This code can be useful for cartographer, as I found a lot of errors for the river Amazon (see here) or.. to have your own poster
You may not want to use the planet.osm file (644GB – all the openstreetmap data in one file). Choose the right filehere and extract what you really need with openstreetmap’s tools : osmconvert, osmfilter, osmosis, osmium…
One interesting way is that you can extract all the data within a polygon with osmconvert, and here are some cities polygons .
|Map||Routing system used|
|Paris||Graphhopper – "Dijkstrabi"|
The first thing to do is to gather the statistics of usage of all paths : for each location, execute the routing algorithm you chose to your root location (your home for example). Merge all and sort the data by the most used path.
|Paris||Lambert 93-I EPSG:27571|
|Amazon||ESRI:102032 (South America Equidistant Conic)|
Considering the data is sorted and well projected.
The width and height of the image are defined like this :
width = (maxX-minX)/scale; height = (maxY-minY)/scale;
To draw these paths, I used this function (plotted using R) :
as it gives me a percent (between [0;1] here) of how the line width must be important. Also I can accentuate the decreasing by modifying parameters inside exp() .
I used cairo and I was really suprised that I can understand these map without using any shapefile.
Details for each map
See here .