A vehicle could be used for mapping bins or litter. OpenLitterMap data could be used in planning the location of cleanups, resurveys, or even future bins. One could then locate the bins on OSM when disposing of garbage or litter.

Here is the gist of it.

Its format certainly leans more collaboratively. One may say it’s neither reduced nor detailed and instead has a capacity to adapt due to its structure.

I am glad you see it as a journey, too. OpenAerialMap hosts imagery which is viewable by third-party applications via a TMS hyperlink. WebODM may be used to generate a structure-from-motion-generated mesh, (which can be exported and saved to Cesium Stories or QGIS). Ideally we would want an editor plugin to leverage the outlines to generate parts of a basemap. This in turn can be used to train RoboSat.

I definitely like to see more discussion of OSM hardware like this here and in WeeklyOSM. Mapping demand can continue be satisfied by removing entry level barriers like cost.

‘Blade of grass’ almost sounds like a metaphor for a type of feature that contributes a level of detail that no one - not even one with an eidetic memory - could recall. If that is true for grass, then a more reasonable representation for the plant might be using a crown shape like for trees. :)

Das ist hier die Lösung! Macht die App evtl mit mehreren Empfänger mit? Denn vielleicht kann man die Durchschnittsposition zwei Geräte oder den kombinierten Satellitenempfang zwei Hemihimmel-Taschenfelder annehmen. Oder um mehrere gpx Daten aufeinmal zu schreiben. Und ohne Kabel vom Hut zum Handy, fällt es gar nicht auf, dass die Schwäche auf dem OnePlus liegen könnte. 😀️

https://github.com/Microsoft/USBuildingFootprints open with JOSM.

I just looked at one of the recent edits I made with iD-indoor in iD. Selecting the room feature and mapping it as an area in iD-indoor, in iD its closed boundary line is not shaded/recognized as an area. For “room 202”, I guess this would just be a line with the tags: indoor=room level=2 name= ref=202

We could use Mapillary deltas to generate the eaves of buildings that are otherwise impossible to see on satellite imagery. I imagine the lower right table is for cropping, saving, and mapping your favorite Mapillary image of a building facade to a texture database.

Overpass might be used to search friends