Mapillary Blog

The project ( Dar Es Salaam mapping ) is using OpenStreetMap technology and Data. And related to the Humanitarian OpenStreetMap Team ( https://hotosm.org/ )

- http://ramanihuria.org/resources/

- http://ramanihuria.org/about/about-openstreetmap-osm/

- http://ramanihuria.org/news/

"Dar Ramani Huria is a community-based mapping project in Dar Es Salaam, Tanzania. Dar Ramani Huria (which is Swahili for “Dar Open Map”) is training teams of local university students and community members from throughout Dar Es Salaam to use OpenStreetMap to create sophisticated and highly-accurate maps of Dar es Salaam. These neighborhoods (known as wards) were selected because the are the most flood-prone areas of the city." http://ramanihuria.org/about/

And the Mapillary blog post:

- http://blog.mapillary.com/update/2015/12/17/worldbank.html

And the Humanitarian OSM blogpost:

"A day mapping in Dar Es Salaam: drainage in Chang'ombe"

https://hotosm.org/updates/2016-02-16_a_day_mapping_in_dar_es_salaam_drainage_in_changombe

Yep I've contributed a fair few Mapillary images! I like that OpenStreetMap integrates with it well; I don't like that it no longer shows _who_ contributed an image (whether in the OSM viewer or the Mapillary viewer).

I believe OpenDroneMap uses OpenSfM which Mapillary open sourced:

https://blog.mapillary.com/update/2016/10/31/denser-3d-point-clouds-in-opensfm.html

> OpenSfM is also used internally by the OpenDroneMap project. OpenDroneMap creates 3D models and orthophotos from drone imagery. It includes all the steps of the pipeline so one can go from images to 3D models in one command. It uses OpenSfM to get the camera positions, and can now use it to compute the dense point clouds as well.

There's multiple efforts along those lines.

Mapillary provides sign detections to OSM:

https://blog.mapillary.com/product/2017/02/06/towards-global-traffic-sign-recognition.html

Telenav is doing similar through their OpenStreetCam project (but no good link). I'm not entirely sure, but I think they have the goal of running the detection locally.

Mapbox recently used Bing Streetside imagery to detect turn restrictions (which are important for high quality routing):

https://www.openstreetmap.org/user/daniel-j-h/diary/43242

Mapbox and Telenav also compare their incoming position data with OSM and flag discrepancies (missing roads, turn restrictions again, stuff like that).

This, on a software discussion board. So many horrible errors in such a small package! I sort of have ~3 different map+nav systems, and they won't even agree with each other what the situation is, never mind the Real World (tm). Speed limits specifically: they are in agreement about 80% of the time.

Machine vision, triple meh. Even with strictly standardized set of easily recognizable shapes, this is useful for post facto mapping ( https://blog.mapillary.com/tutorials/2017/08/21/mapping-traffic-signs-in-osm.html ), but nowhere near realtime without false negatives.

Maybe the relevant section is left over from the previous license, which was CC-BY-NC (http://blog.mapillary.com/update/2014/03/17/mapillary-goes-creative-commons.html). Alternatively, IANAL but I imagine that the individual photos could still be CC-BY-SA (if, e.g., someone else redistributes them) but that the service itself cannot be used for commercial purposes. As bulk exports are prohibited (2.1) and dumps are not provided, however, this would mean that the data is CC-BY-SA in theory but hard to reuse commercially except for individual pictures.

As to humanitarian use for OSM and how anyone can contribute by small tasks (I've tried it myself, was surprisingly exciting), enabling faster and more accurate response and travel to people in need, see:

https://wiki.openstreetmap.org/wiki/Humanitarian_OSM_Team

https://wiki.openstreetmap.org/wiki/OSM_Tasking_Manager

As to work in progress on detection of features and automatic conversion to maps, I've recently found the below website:

https://blog.mapillary.com/update/2016/07/15/mapillary-osm.html