Problem we would like to solve is finding out what methods are to calculate the most efficient routes in a map with distance/travel time, pop density and facility capacity as co-variables! Perhaps somebody with more experience knows where to find a useful tutorial?
Currently, I have been able to create a map (see image above) using:
- Eurostat data
- Input from a csv with consumption rates per country
As a result, consumption per capita has been mapped on NUTS2 level in the EU. The next thing I have done was adding the different types of facilities to the maps, based on postal codes which then have been transferred by a script to the location on the maps with the projection of CRS EPSG:3035 - ETRS89 / LAEA Europe - Projected. Sidequest: I am also wondering how to add more data to these facility points.
All of this is saved as geojson, but I suspect it would be better to use rasters instead to overcome the issue. I am new to QGIS and think the network analysis tool or an approach with Python combined with the creation of some own formulas would be a way to solve it.
What I have tried before are checking out some tutorials on YouTube, however these handle very simple queries rather than the more complex one from this issue. Also esri's documentation on proximity analysis or finding a service area seems to answer the question partly, however it requires integration / synthesis which currently lies outside my level experience.