Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Ensure population is distributed sensibly across the study area for 3rd zoom level #35

Closed
Robinlovelace opened this issue Jan 18, 2021 · 9 comments
Assignees

Comments

@Robinlovelace
Copy link
Contributor

Related to #34

@joeytalbot
Copy link
Contributor

If this relates to destinations, then it's more about workplace population than resident population.

@Robinlovelace
Copy link
Contributor Author

For origins and destinations - see #32 (comment)

Also from @joeytalbot - ensure not everyone goes to small random places (e.g. assign probability relative to building size).

@dabreegster
Copy link
Collaborator

Area of buildings multiplied by the building:levels tag seems relevant. Also the number of POIs / businesses located inside could be relevant.

@mvl22
Copy link
Contributor

mvl22 commented Jan 22, 2021

It might be worth using the OSM landuse tag to determine whole commercial, education, or other areas. These will likely be a proxy for where people work.

I expect that would result in a reasonable correlation with the manual list of employment areas for Cambridge that I listed in another thread.

Obviously residences can easily be found from residential buildings.

@Robinlovelace
Copy link
Contributor Author

Agreed. Do you think it would be useful to visualise landuse polygons in the Zoom 2 work @mvl22? Could also be useful in terms of considering other sites (imagine there's a 'brownfield' tag) is my thinking.

@Robinlovelace
Copy link
Contributor Author

image

Great Kneighton start of day.

@Robinlovelace
Copy link
Contributor Author

image

End of day.

Robinlovelace added a commit that referenced this issue Feb 24, 2021
@dabreegster
Copy link
Collaborator

To clarify how to find commercial places in OSM: sometimes the way or relation representing the building has useful tags, but often not. For example, https://www.openstreetmap.org/way/191546286 just has building=yes. You need to import all of the nodes and look for things like amenity=... -- example https://www.openstreetmap.org/node/298858209. If you wanted to match that to a building, you have to find which building physically contains the point. But since abst snaps trip endpoints to a building anyway, you could just skip that step and use the node's location.

And per https://github.com/a-b-street/abstreet/blob/23b19fa7ce9e5098705b9b5852efaca1c0891ee1/convert_osm/src/extract.rs#L535, looks like sometimes things're listed as shop=... too

@Robinlovelace
Copy link
Contributor Author

Update:

image

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

4 participants