AI-Assisted Road Tracing
In 2016, Facebook started researching how various machine learning algorithms could be integrated into a mapping workflow. At State of the Map 2016 Facebook shared initial results on how one could use AI and new mapping techniques, such as advanced deep neural net models, to detect roads from satellite imagery. We have since received many requests to share our process and masks. Our goal is to collaborate with the OpenStreetMap community to create quality road data, validated by trained mappers and local OSM communities. Please send questions to email@example.com.
DigitalGlobe's Vivid+ product provides high-resolution (50cm / pixel, or zoom 18) color-corrected cloud-free satellite imagery with full country coverage. We now have license to extract road data from the imagery and contribute to OSM.
The following images show the benefits of using current high-resolution imagery. For example the quality of satellite image currently available to the OSM community for Mu Ban Don Sak Thani, Thailand is not optimal for mapping.
Mu Ban Don Sak Thani of Thailand. Vivid+ on left, Bing Aerial on right, at zoom 14, which is Bing Aerial's max zoom for the city.
The full resolution goes to zoom 18.
Another example of Ko Samui where Bing has zoom 18 but it's heavily covered by clouds.
Partnering with the local OSM communities, we will start testing our submission in Thailand in February 2017. Depending on the progress, we will expand our effort to Indonesia and Malaysia during the year. We chose these countries because of their relative low road coverage on OSM.
Update - November 2017
We have been mapping in Thailand since May 2017. Here are our Stats since.
26 of 79 Provinces Completed
5,588 of 17,574 Tasks Completed
201,992 New Ways Added
101,104 km’s of Road Added
2,764,716 Nodes Added
Update - February 2018
44 of 79 Provinces Completed
10,235 of 17,574 Tasks Completed
354,936 New Ways Added
150,188 km’s of Road Added
Road Density Change from Start to Now (Feb 2018)
3. Data Processing
We will only contribute roads to OSM. We use the latest deep learning algorithms to assist road extraction and mapping. Here is an example of a prediction using deep learning for an area in Thailand.
We then apply a series of post processing steps to generate .osm file that can be loaded into JOSM or our modified iD for manual correction and enhancement. The images below show the .osm file in our iD, where the grey road is an existing road on OSM, and green roads are new.
The submission process consists of the following steps summarized in the image below.
(1) We use the OSM Tasking manager to divide up tasks and create a flow of editing and validation for the Facebook mapping team.
(2) The Mapper picks a task and loads an .osm/.xml file generated from the post processing step into our enhanced version of iD (this includes both the roads generated by us and the current OSM data).
(3) The Mapper evaluates the roads we generated (styled in a different color) and inspect them for issues like crossing highways, disconnected roads, incorrect intersections, short road stubs, road types, etc., and fixes these issues manually one by one, using DigitalGlobe satellite imagery.
(4) Our modified iD tool is equipped with data validation functionalities similar to JOSM and osmlint. This allows us to check for quality and conflicts with current OSM data prior to submission. Some examples of what we check for include:
- Isolated roads that are not connected to rest of the map.
- Roads crossing waterways.
- Roads with repeating node IDs.
- Roads with possible connections after a short extension.
- Self-intersecting ways.
(5) In case of conflicts between our newly added roads and other OSM contributors' changes, our mappers will almost always choose “keep their edits.” If we end up changing another mapper's edits, (for example, to align better with the latest version of DG satellite imagery) we will leave detailed notes to explain why.
(6) Until all errors are fixed, Mappers will not be able t upload to OSM. Here is an example of a highlighted issue prompting the mapper to fix it.
(7) After fixing all the issues detected in the iD tool, the Mapper clicks the “Save local” button to save their edited roads locally for validation.
(8) A Validator then goes into the same task to verify that the data looks correct by re-validating the data, makes necessary changes as needed, and clicks “Submit” to finally upload the task to OSM.
(9) The Validator then conducts a post-submission review of the submitted edits in JOSM. If any errors are detected, the validator addresses the errors and submits necessary changes. A custom JOSM paint style is used to help distinguish our submissions from community submissions, so that all roads with the import=yes tag are highlighted in green. Some examples for what we check for include:
- Short Unclassified ways (between 10-60 meters)
- Highway crossing waterway without a bridge tag
- Highway crossing buildings
- Overlapping ways
- Unspecific highway tags
(10) We will continue to watch all comments made on our edits, reply to them in a timely fashion. We are happy to incorporate feedback and local expertise into our validation process and future mapping behaviors.
4. Data Preparation
Road Type Tagging
During the submission process, our mappers will assign and fix road types according to the general highway tag guidelines of OSM http://wiki.openstreetmap.org/wiki/Key:highway
Before moving to a new location, we will work with mappers from local OSM community in each country to verify our highway tagging method and make sure they align with local conventions.
Some other methods we use to tag roads include:
- Refering to local Wiki guides for each country.
- Looking at commonly used tags in the local area of mapping.
- When connecting to current OSM roads on the map we try to use the same tag where it makes sense to do so.
- Refering to local community for advice.
We use the following tags:
- comment = '#nsroadimport #country'
We use the above changeset tags in every import changeset, where the '#country' tag is the country of the submission. For Thailand the tags are '#nsroadimport #thailand'.
- source = digitalglobe
- import = yes
The 'source' tag indicates that road geometries are based on DigitalGlobe satellite imagery.
5. Data Merge Workflow
This import (data integration) will be done through a Tasking Manager, by engineers and a group of selected trained map editors. Among the skills required:
- Good experience with iD and JOSM.
- Familiarity with editing norms: how to merge nodes (M), join ways (J), combine ways (C) and un-glueing (G)
- S/he knows how to handle conflicts with both iD tool and JOSM.
Our map editing team consists of 17 Mappers and Validators, and their accounts are listed as below.
We are not bots :) The usernames (VLD001, RVR001, etc.) were made to help our internal process where we have paired Mappers and Validators to ensure quality. Please feel free to send us questions individually about edits or email all of us at firstname.lastname@example.org.
Humanitarian OpenStreetMap Team (HOT) Indonesia
In Indonesia, we have partnered with HOT's Jakarta office to coordinate with the local community and improve the road network of Indonesia. The team is comprised of: Wulan IRM-RV, Team Lead Adiatma IRM-RV, QA Hanif IRM-RV, QA Yeni IRM-RV, QA Akrimullah IRM-RV,QA Adam IRM-ED, Mapper Silvia IRM-ED, Mapper Dary IRM-ED, Mapper Irwan IRM-ED, Mapper Riyadi IRM-ED, Mapper Zainab IRM-ED, Mapper Deo IRM-ED, Mapper Anisa IRM-ED, Mapper atmahadi IRM-ED, Mapper Dennis IRM-ED, Mapper Fatri IRM-ED, Mapper Muty IRM-ED, Mapper Iko IRM-ED, Mapper Aglis IRM-ED, Mapper Diana IRM-ED, Mapper Aude IRM-ED, Mapper Arma IRM-ED, Mapper Elisabeth IRM-ED, Mapper Diah IRM-ED, Mapper
In summary, our overall mapping workflow is:
(1) We extract grey-scale road mask images from high resolution DigitalGlobe satellite imagery.
(2) We generate road vectors based on the road mask images and merge them with latest OSM data to produce .osm files.
(3) Our human mapping team does manual validation on the .osm files through our enhanced iD tool and on JOSM prior to submission (as described in the “Submission Process” above).
(4) After conflict resolution, submission, and post-submission review, we work with local OSM community to complete local validation as described in the “Validation Steps” below.
6. Validation Steps
There will be a 4 step
s validation process done by experienced OSM editors including local country Mappers.
- Our method for each country will include starting with small number of edits to gather feedback from the local OSM community before proceeding with larger edits.
- We then start with human validation from our Mappers as explained in the “Submission Process.”
- Before submitting our changes, our team will verify that our updates are based on the current dataset.
- After Submission (as described in the “Submission Process” above, a team of selected Validators and QA's conduct a second post-submission review by passing over chunks of multiple submitted tasks , region by region, by repeating the JOSM validation checks in described in Step 9 under “Submission.”
- Our validation process primarily only includes elements that our team has contributed, which can be identified by the “import=yes” tag. Elements that our team “inherits,” meaning elements that are authored by one of our usernames but lacking the “import=yes” tag, are not typically included in post-submission validation. For more about inheritance, see footnotes.
- We understand inherited versus contributed elements by exploring the ownership of nodes and their parent ways. We can identify inheritance based on authorship and tagging. Roads that are authored by one of our usernames, but does not include the Import=yes tag, is likely an inherited way. Because we are a team of remote mappers, using one data source, we want to avoid overstepping our contributions.
- Community feedback on imported roads is evaluated and incorporated for final edits in this stage as well. All edits can be identified with the changeset tags above and the team will respond to any e-mails or concerns about edits within 48 hours.
To facilitate the validation process, we share our road mask as a tile service that can be used in iD tool and JOSM as a background layer. The URL template of the tile service is distributed on a per-request basis. Please contact email@example.com for requesting a validated URL template.
So far we have prepared road masks for selected areas in Egypt and Thailand. We will announce the availability for other countries here as they become ready.
Local OSM Community Engagement - Using the list servers and wikis we contact local OSM community members before starting to edit in a specific country. Through this we invite members to collaborate and provide valuable local insight and feedback.
To use our tile service in iD:
(1) Click the “Edit custom background” button in iD
(2) Paste the URL template above in the input box of the pop-up dialog and click “OK”
To use our tile service in JOSM:
(1) Click Imagery > Imagery Preferences dialog
(2) In the Imagery providers tab, in the lower right hand side of the dialog box, click on “+TMS” button
(3) Enter the URL template in the input box and provide a name for the new layer
(4) Once added, this new layer will show up under the Imagery list. You can select this layer to be displayed in JOSM