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https://github.com/ibaaj/dijkstra-cartography
Using Dijkstra's algorithm ("finding the shortest paths between nodes in a graph") to draw maps :earth_africa:.
https://github.com/ibaaj/dijkstra-cartography
algorithm cartography dijkstra dijkstra-cartography drawing openstreetmap paris
Last synced: 3 months ago
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Using Dijkstra's algorithm ("finding the shortest paths between nodes in a graph") to draw maps :earth_africa:.
- Host: GitHub
- URL: https://github.com/ibaaj/dijkstra-cartography
- Owner: ibaaj
- License: other
- Archived: true
- Created: 2016-04-11T20:19:57.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2016-10-27T21:56:18.000Z (about 8 years ago)
- Last Synced: 2024-09-25T22:32:59.918Z (3 months ago)
- Topics: algorithm, cartography, dijkstra, dijkstra-cartography, drawing, openstreetmap, paris
- Language: C++
- Homepage:
- Size: 47.5 MB
- Stars: 1,157
- Watchers: 38
- Forks: 75
- Open Issues: 0
-
Metadata Files:
- Readme: readme.md
- License: license.md
Awesome Lists containing this project
README
# Dijkstra Cartography
- All roads lead to my home (at least in Paris) [[HD 14016x9599 / 7.3MB](./results/HD/paris.png)]
- The Amazon river / Rio Amazonas with all its tributaries [[HD 11962x7625 / 3MB](./results/HD/amazon.png)]
- Eastern European Railway (from Paris) [[HD 29255x9624 / 10.8MB](./results/HD/railway.png)]
- World Flights (from Paris) [[HD 17900x6600 / 17.72MB](./results/HD/flights.png)]
## Introduction
I was fascinated by the project ["Roads to Rome"](http://roadstorome.moovellab.com/) by Moovellab but sad that it isn't opensource. Helped by [this project](https://github.com/Tristramg/roads-from-nd) (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](https://en.wikipedia.org/wiki/Breadth-first_search) 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](./results/errors.png)) or.. to have your own poster 😉.
## Extract
You may not want to use the [planet.osm](http://wiki.openstreetmap.org/wiki/Planet.osm) file (644GB - all the openstreetmap data in one file).
Choose the right file [here](https://download.geofabrik.de) 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](https://github.com/JamesChevalier/cities).
## Routing
| Map | Routing system used |
| -----------|----------------------------------------------------------|
| Paris | [Graphhopper](https://github.com/graphhopper/graphhopper) - "Dijkstrabi" |
| Amazon | Dijkstra's algorithm |
| Railway | [OSRM](https://github.com/Project-OSRM/osrm-backend) |
| Flights | Dijkstra's algorithm
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.
## Projections
| Map | Projection |
| -----------|-----------------------------------------------|
| Paris | Lambert 93-I EPSG:27571 |
| Amazon | ESRI:102032 (South America Equidistant Conic) |
| Railway | Mercator |
| Flights | WSG84 |
You can follow [this guide](http://www.georeference.org/doc/guide_to_selecting_map_projections.htm), search [SpatialReference](http://spatialreference.org/ref/) or [ESPG.io](http://epsg.io/).
## Drawing
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
- [Paris](./paris/)
- [Amazon](./amazon/)
- [Railway](./railway/)
- [Flights](./flights/)
## Bonus
## License
[See here](./license.md).