|Authors:||Missing Maps Project|
|License:||(free of charge)|
|Platforms:||Android, and iOS|
Super-simple contribution to humanitarian mapping (indirectly) by helping find features in imagery
MapSwipe mapswipe.org is a new app developed by a team in collaboration with the Missing Maps Project as an easy way for people to contribute to humanitarian mapping efforts. The contribution is indirect. A form of "second level crowdsourcing".
The app is being launched July 2016. listen to a radio interview about it
Users swipe through satellite images of a region, tapping the screen when they see features they’re looking for including settlements, roads and rivers. This information is fed back to mappers who need this information to build detailed and useful maps. At present, they have to spend days scrolling through thousands of images of uninhabited forest or scrubland looking for communities that need mapping. Now, members of the public can directly contribute to MSF’s medical activities by locating people in need more quickly so mappers, and ultimately medical professionals on the ground, can get straight to work.
Open Source code & issue tracking on github: https://github.com/mapswipe
See the HOT mailing list posting for release information.
What happens to the results?
We're left with a view of where settlements are located across a very large area. This is available to download (somewhere), and is being used to guide further mapping priorities, for example feeding into the design of OSM Tasking Manager projects, in an manual observational way, or via automated project designing mechanisms which are still somewhat under development.https://gitlab.com/giscience/MapSwipeTools
MapSwipe is very intuitive.
- Choose your 'mission'. Each mission will indicate what you are looking for (for example, buildings and roads)
- Swipe right to see the next tile.
- Tap once on a square to indentify a feature
- Tap twice if you are not sure, but you think there is a feature
- Tap three times to identify bad / no imagery or cloud cover
See the guide, MapSwipe guidance: interpreting satellite imagery for more help on feature indentification