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What's new in OSMCha

Posted by nammala on 11 October 2017 in English. Last updated on 16 October 2017.

If you have been a daily user of OSMCha, you have already started using the new version. Wille has been working with Mapbox on new developments of OSMCha. We have been testing the stack stability, and collecting feedback from Mapbox data team and community members for few months now.

I would like to use this diary post to introduce few features in the new version of OSMCha and talk about ways we can use them for validation.


The development challenge has been to make OSMCha easier to use, faster to review changesets, and a robust tool for filtering OSM edits. We needed to add contextual information on mappers & changesets, improve the user-friendly UI, add keyboard shortcuts, and a lot more using an API driven frontend.

Along with a brand new design, a lot of things have been improved in the new version. Here are some of the new features.


The sidebar is similar to how the History tab on OpenStreetMap shows a list of changesets. The sidebar on OSMCha also gives a count of changesets in the search, and supports keyboard shortcuts to move through the list.


Many filters correspond to the metadata associated in changesets. To help make this clear, we now have descriptions for each filter that briefly explain what a certain filter does in the search.

Saving personal filters - Area of interest

One key request from OSMCha community users has been ability to save a set of filters for easy sharing, and reuse. This is now possible! You can save a filter with a custom name and share the url with the folks you work with or find it in your profile for future use and reference.

For example: Here is a filter that lets me see all changesets in New York

GeoRSS feed

If you would like to be notified when a new changeset comes into your personalized filter, we now have GeoRSS feed that can do that for you. Here is an example changeset feed link for the New-york filter I have made above

Open a list of changesets by ids

If you need to open a list of changesets by id (for example, returned from Overpass), OSMCha now supports filtering by comma seperated changeset ids.

The bbox search works by retrieving all changesets whose bboxes have an intersection with the bbox we give. A problem with this method is that global scale changesets can overlap the local search area. This problem has been wonderfully explained here by Athalis. One way to solve this problem is to have a bbox size bound search.

Bbox size bound search limits the retrieval of worldwide edits by taking a multiple from the user that essentially limits the max bbox size in the search. Example: 2 only shows changesets whose bboxes are at maximum twice the size of bbox we have provided.

Keyboard Shortcuts

Keyboard shortcuts enrich user experience. In the new version of OSMCha, we have keyboard shortcuts that allow us to sift through panels, sidebar changeset list and even verify a changeset. Read more about keyboard in the about page for OSMCha

Tag the changesets

Another new feature is the possibility to tag the changesets. This way we can add a little more information about the changesets, besides saying that it’s good or bad. We have some tags to evaluate the severity degree, if the errors were resolved or not and if they were intentional.

It is important for us to review changesets we are reviewing as good or bad, as it indicates other community members that they need not spend time on that particular changeset.


If you have ideas or suggestions on OSMCha, please feel free open an issue in one of the below repositories.

OSMCha frontend -

Backend API repo -

Find all the necessary documentation related to the API here:

API docs -

We are delighted to introduce the new version. This was a collaborative work and we hope you like it just as much as we do.

Happy reviewing!

Resuming from previous diary posts, we would like to start off with interesting changesets we have observed over the last month. Nearly all of these changesets have been flagged by currently existing filters in OSMCha.

Here is what we found

image We found randomly added parks in the form of letters K N N in this changeset. This was detected while we were reviewing changesets from pokemon nest by new user filter in OSMCha.

image Added park over residential area. Here is the changeset. This was detected by park added by new user filter.

image We found a juggling teddy bear in Belarus which was posted in the Russian forum. Here is the associated changeset.

image We found a changeset which consisted of fictional edits that were basically some names and random characters. This was flagged through feature overlap filter. Feature overlap filter takes a feature and downloads nearby features to check if there is an overlap. We have been testing this filter with thresholds of overlap. Code for this can be found here.

image We found fantasy water bodies over a residential buildings. This changeset was detected by waterbody added by new user filter.

image Similar fantasy parks and waterbodies were found in this changeset. It was detected by waterbody added by new user filter.

image A park was found over buildings. This changeset was detected by park added by new user.

image We noticed suspicious edits in Japan by a new user, who is adding random parks, waterbodies, footways etc. This was detected by Park added by new user , Waterbody added by new user, and Footway added by new user filters in OSMCha.

If you are interested in getting into details of Pokemon specific edit detection, you can refer to the previous diary post for better understanding.

This is a very small subset of issues we have reviewed. Rarely do we find these kind of intentional errors on the map. We also have come across some detailed mapping activity. One of those is this changeset which added some beautiful details to a castle in Ludwigsburg. ✨ gif

Look forward to more such validation scoops from us. Let us know if you have feedback on any of these OSMCha filters. It would be great to hear similar stories of inconsistent or detailed mapping activity that you have come across. Comment on this diary post and share them with us (We ❤️ screenshots).

Continuing from our previous diary post on inconsistent edits observed, here are the inconsistent edits observed in OpenStreetMap between 26 December 2016 - 27 January 2017 using OSMCHA.

We commented on the changesets:

  • Deleted main stream and added an incomplete one: changeset
  • Deleted existing roads and buildings: Changeset 1, 2, 3
  • Added unnecessary trunk roads: Changeset
  • Deleted buildings: Changeset 1, 2, 3
  • Deleted roads: Changeset 1, 2
  • Added unconnected footways with footway=crossing, crossing=zebra for the whole length of the road: Changeset
  • Added self intersecting footway that goes over a building: Changeset
  • Added address in name tag: Changeset
  • Added single large buildings for many buildings instead: Changeset

Community members commented on the following changesets:


  • Added waterbody which doesn’t exist in the imagery: changeset
  • Added christmas tree saying Happy new year: changeset

screen shot 2017-01-03 at 12 40 50 pm

  • Added a waterbody with water=sound tag in the ocean with name as Doodoo water : changeset
  • Changed name of the highway: Changeset 1, 2
  • Added duplicates of POI’s: changeset
  • Added footways all over one place: changeset

screen shot 2017-01-12 at 10 12 17 am

  • Deleted Valid data on map: Community reverted the changeset
  • Deleted buildings: Reverted the Changeset
  • Testing Opengeofaction data in OpenStreetMap (OSM): Community reverted the changeset
  • Deleted roads: Reverted the changeset
  • Deleted existing footways, major highways and renamed highways: Changeset 1, 2, 3, 4, 5, 6, 7, 8, 9
  • Changed highway tag: Community reverted the changeset
  • Inappropriate information: Community reverted the changeset
  • Inappropriate temporary race track mapping: Reverted the changeset
  • Added a primary highway not connected to anything and has an access=private tag: Changeset
  • Added Fictional roads: Reverted the changeset 1, 2


  • Added cricket and football pitch in a park: Commented on the changeset.
  • Fictional data by Pokemon mapper: Reverted by the community Changeset
  • Added number of footways in one location: changeset

screen shot 2017-01-03 at 9 39 30 am

  • Added Pokemon gym stations: Reverted the changeset 1, 2, 3, 4
  • Pokemon Go mapper. Reverted the bad stuff Changeset 1, 2, 3
  • Changed residential roads to footways: Reverted the changeset
  • Fictional footways. Reverted the changeset 1, 2, 3, 4, 5

If you are interested in validation, check out our validation guide on using OSMCha. From the past one month, we have been observing a lot of Pokemon Go mappers adding footways, cycleways, pedestrians, parks etc. Some of them are adding valuable data and while some are doing fantasy mapping. Do keep an eye on the edits happening in your neighborhood and comment on changesets which seem inconsistent to let the user know which will help them become better mappers and also lets us maintain the data quality on OpenStreetMap

Look forward to another roundup in the coming week.

Following up from our previous diary post on inconsistent edits observed, here are the inconsistent edits observed in OpenStreetMap between 28 November - 23 December using OSMCHA.

We commented on these changesets:

  • Deleted road: changeset 1, 2, 3, 4, 5
  • Added inappropriate name tag to the highways: changeset
  • Added building=yes to nodes for some features: changeset
  • Added lots of POI’s: changeset
  • Deleted rail road: changeset
  • Buildings that were not split: changeset
  • Circular polygon over university: changeset

Community members commented on the following changesets:


  • Deleted buildings: Community commented and reverted the changesets 1, 2, 3, 4
  • Deleted roads: Reverted the changeset 1, 2, 3, 4, 5, 6, 7, 8
  • Overlapping buildings: Reverted the changeset
  • Added a ton of ways with relation type=lanelet at intersections. DWG reverted the changeset
  • Fantasy mapping. Community reverted the changeset 1, 2
  • Deleted landuse. Reverted the changeset
  • Deleted track: Community reverted the changeset
  • Mass incorrect edits of road graph. We reverted 52 changesets
  • Adding bad import hotel data. Community reverted the changeset
  • Added POI to a major road. Community reverted the changeset
  • Deleted tunnel on a significant highway. Reverted the changeset
  • Added private information. Reverted the changeset

If you are interested in validation, check out our validation guide on using OSMCha. Do keep an eye out and comment on changesets which seem inconsistent to let the user know which will in turn helps users become better mappers and lets us maintain data quality on OpenStreetMap.

Look forward for another roundup next week.

Here are the few observations from the OpenStreetMap edits between 11 November - 25 November. We looked into the filters like mass deletions, iD editor + mass deletions, possible imports, edited a name tag, mass modifications using OSMCHA for reviewing the changesets.


  • Deleted tracks: changeset
  • Added random pedestrian highways and buildings: changeset
  • Deleted highways and few buildings: changeset 1, 2, 3
  • Deleted buildings and some amenities: changeset 1, 2, 3
  • Incorrect tagging: changeset
  • Changed road classification: changeset
  • Deleted neighborhood tags: changeset
  • Added Korean names in name:en tag: changeset
  • Deleted streams: changeset

Community members commented on the following changesets:


  • Added province tags to address: Community member commented and reverted the changeset
  • Undiscussed import: Community member commented and reverted the changeset 1, 2
  • Deleted houses and residential roads: Reverted the changesets with a comment 1, 2, 3
  • Deleted buildings and roads. Community member commented and reverted the changeset.
  • Added orphan nodes over buildings and highways. we reverted the changeset with a comment

These were some of the inconsistent data for this week. Do keep an eye out and comment on changesets, which will make us maintain the quality of data in OpenStreetMap.

Look forward for another roundup next week.

Here are the few observations from the OpenStreetMap edits between 24 October - 11 November.


  • Bad imports: changeset 1, 2, 3, 4
  • Deleted roads: changeset
  • Deleted natural=wood: changeset
  • Deleted existing buildings: changeset 1, 2, 3, 4
  • Adding fictional data: changeset 1, 2
  • Adding buildings overlapping with highways: changeset
  • Changeset comment mentioning google: changeset
  • Deleted river: changeset
  • Added improper data: changeset
  • Deleted relevant information in neighborhood: changeset 1, 2

Community members commented on the following changesets:

These were some of the inconstant data for this week. Do keep an eye of the bad edits and comment on those changesets, which will make us maintain the quality of data in OpenStreetMap.

Look forward for another roundup next week.

One of the most important uses of the map during car navigation is to find the correct exit off a motorway to get to a destination. Missing an exit can be quite costly in terms of the time and fuel wasted in a much longer route than desired. In OSM, the tags that help to map this information are highway=motorway_junction(exit number) and destination(destination sign).

The Mapbox data team has updated over 247 motorway exits and 1285 destination sign information in United States & Canada in the last year. Here’s the workflow we followed to create tasks on the Mapbox Tasking manager if you would like to create a community project for your own area. This workflow creates convenient tasks that can be distributed to review the data on individual highway routes on checkautopista2 for a particular area of interest.

screenshot 2016-11-14 13 12 21

1. Defining the area of interest:

Draw a boundary for the area of interest you want to cover in JOSM tagging as area=yes and save it as .osm file.

2. Converting .osm to .json:

Using osmtogeojson we can convert .osm file to geojson.

3. Now we should get the city boundary polybox coordinates:

Use polybox to convert the geojson of the area of interest into a polybox format.

4. Extracting the highway routes in the area of interest:

For the exit numbers and destinations task, we wanted the highway routes inside the area of interest along with the relations. So, we use overpass query giving the polybox coordinates for getting the data and exporting it into geojson.

5. Filter out highway=motorway along with relations:

Using this repository we can filter out features with highway=motorway, flattens relations, merges ways with the same relation and adds a buffer around them (so that they show up in tasking manager). Bus route (route=bus) are ignored.

Example of highway with relation:

6. Merging multiple geojson to single geojson:

Incase if we want to do it for various areas of interest, we need to combine multiple AOI’s geojson’s to single geojson using geojson-stream-merge.

The final single geojson is then imported into tasking manager. In the tasking manager instructions give a link to checkautopista2 and use the format{rel} because it takes the rel property in the geojson and displays the ways in the tasking manager.

Hope my workflow will help you in creating the tasks effectively. Let me know if there is any other simpler way of doing this procedure.

Happy Mapping!

Imagery offset database in JOSM

Posted by nammala on 24 October 2016 in English.

Satellite imagery is one of our common source of data for mapping, however, not all imagery is exactly aligned to real world features. Every mapper should be aware of this and should consider adjusting imagery from aggregated GPS tracks or from features which we know have correct location.

Adjusting imagery offset

The usual approach is to align the imagery to GPS traces as best as possible using the Adjust imagery offset tool before making any edit. screen shot 2016-10-20 at 11 53 08 am

You can also save the defined offset as a bookmark so you can access them later on, for specific places. krishna

These offsets are stored in your local machine and only you can access them.

Using the Imagery Offset Database

The Imagery Offset Database allows a mapper not only to store imagery offsets but also to share them with the community. This crowdsourced approach for managing imagery offset is a great way to make sure that data derived from imagery have a consistent offset adjustment. This database can be accessed through a JOSM plugin.

Here is the wiki page for Imagery Offset Database and step by step tutorial with illustrations to install and use it in JOSM.

Aligning the imagery using aggregated GPS traces

  • In JOSM, load the imagery layer you wish to align (for example, Mapbox or Bing).
  • Load the Strava heat map or OpenStreetMap Traces layer.
  • Make sure the satellite or aerial imagery aligns as best as possible with aggregated GPS sources. how_to_offset3

  • To verify the alignment check the offset at a nearby area with a very high density of GPS data and wide roads. screen shot 2016-10-19 at 4 34 48 pm

Store the imagery offset

To record the offset for sharing with others and later use Imagery > Store Imagery Offset. Make sure the offset imagery is on top of other imagery or you would get a warning message. how_to_store

Using the stored offsets

To use the offsets stored in the database, download the area in JOSM and place the imagery on top and click on Imagery Offset DB icon to show the offsets stored in that area and select the best suitable offset corresponding to aggregate GPS traces. 222

Hope this database is useful for the community. Please do comment on this diary if you have any suggestions on storing and sharing the imagery offsets while mapping at different regions.

Continuing from our previous weekly round up, these are the observations between 12 September - 30 September.


  • Deleted buildings: changesets 1, 2, 3.
  • Deleted admin boundary of region in Burma: changeset.
  • deleted mosque: changeset.

Community members commented on following changesets:

  • Adding numbers on the name tags for lot of buildings: changeset.
  • Renamed a department store in Italy to multilingual name tag with Chinese added: changeset.
  • Deleted name tag of a multipolygon and other features: changeset.
  • Deleted lake that exists in the imagery: changeset.


  • Deleted tertiary roads: changeset community member reverted the changeset.
  • Bad imports: changeset. We reverted the changeset.
  • Uploaded learnOSM test data to the map. changeset community member reverted the changeset.
  • Added fictional roads and deleted many existing highways & other features: changeset. We reverted the changesets.
  • Deleted buildings in Philippines. We reverted 4 of his changesets 1, 2, 3, 4.
  • Added natural=water to all the nodes of the lake. changeset. We deleted the edits with proper comment.

These were some of the inconsistent edits for this week. Do keep an eye and please comment on such changeset, this will help in maintaining the data on OSM accurate and coherent.

Look forward to another roundup next week.

Last week, as a part of making OpenStreetMap more navigable, we started updating possible missing turn restrictions in 5 cities of Germany i.e., (Berlin, Stuttgart, Wolfsburg, Munich and Frankfurt), with the help of OSM Navigation map which uses Mapillary detected traffic signs. Around 1900 turn restriction were reviewed in these 5 cities and we managed to add 112 OSM notes where probable missing data was found.

screen shot 2016-09-19 at 3 00 19 pm

We have received a great response from the community on this task, and as of now, 71 notes are resolved. It would be great if the community could resolve remaining 41 notes to enhance the accuracy of navigation data present on OpenStreetMap.

Here is the list of OSM notes for missing turn restrictions.

We thank the community for all the support. We look forward to more interactions with everyone. Few of our team members will be present at SoTM Brussels this week, catch up with @PlaneMad, @jinalfoflia, @ramyaragupathy, @pratikyadav and @geohacker to talk more on this and the latest data team projects at Mapbox!


From Mapbox Data Team.

Updating Navigation data in Germany

Posted by nammala on 9 September 2016 in English.

As a part of making OpenStreetMap more navigable and accurate for routing, we started updating missing turn restrictions and exit numbers & destinations in 5 cities in Germany: Berlin, Stuttgart, Wolfsburg, Munich and Frankfurt. We started off with 3 cities and later jumped into other 2 cities, Munich & Frankfurt and managed to update missing turn restrictions and exit numbers & destinations through OSM notes with the help of community support.

Summary of improvements:

The Mapbox data team started updating turn restrictions on August 26. The The turn restrictions signboard conventions in Germany were quite different from what we followed for Canada and United States. We went through the German wiki to understand the tagging system and carried out our initial research and came up with our observations in this diary post, where we received valuable feedback from the community. We came to a conclusion that adding OSM notes for the missing turn restrictions is a good way for the community mappers to verify the data with their local knowledge.

We used OSM Navigation map which uses Mapillary images to detect the missing turn restrictions for this. Around 1900 turn restrictions were reviewed in these 5 cities and 112 OSM notes were added by the team where possible missing data was found.

For the Exit numbers and destinations task, the team followed the wiki to review and added OSM notes for the missing exit numbers and destinations for the community to verify and map. For this process, we used tasking manager and checkautopista2 for identifying the missing exit numbers and destinations.

Progress update of missing turn restrictions:

screen shot 2016-09-09 at 2 14 20 pm

Progress update of missing exit numbers & destinations:

Notes added for exit numbers and destinations : 2 out of which 1 was resolved now

You can find the list of OpenStreetMap notes added by the team here:

Status of existing data and Mapillary coverage:

Germany is one of the best mapped places on OpenStreetMap, the community is very active in giving feedback and helping us solve all the queries that we faced through out the project. Since Berlin, Munich and Frankfurt had a great Mapillary coverage, we managed to review and update more turn restrictions in these cities over the others. We reviewed the exit and destinations in a span of 2 days as everything was very well mapped :boom:.

Community support:

Both the exercises went very well with the community response and participation in improving OpenStreetMap . It was good to see some of the community members like jacaobbraeutigam, anbr, wasat, kaltuna, mueschel, peter mailwald, bergaufsee, jonas-erik, hdy3er, loth, jojo4u, hca, FvGordon, mucx, Fuss-im-Ohr, MichaH taking part in resolving most of the notes. It will be great if the community can come together and resolve the remaining 55 notes, which will help in making OpenStreetMap data more awesome :rocket: . We will continue navigation mapping in Germany, specifically in Stuttgart and Wolfsburg once there is enough Mapillary or OpenStreetView coverage to help us to add data/verify.

We’re going to be at SOTM in Brussels next week. Catch up with @PlaneMad, @jinalfoflia, @ramyaragupathy, @pratikyadav and @geohacker on the latest data team projects at Mapbox!


From Mapbox Data Team

Germany navigation data review update

Posted by nammala on 1 September 2016 in English.

Following the previous diary post on improving navigation data in Germany, around 1000 turn restrictions detected on Mapillary were reviewed and 72 notes were added on OSM where there was a mismatch with the data for community mappers to verify with local knowledge. The community response has been extremely quick to verify an resolve these notes almost within a day of them being added. The whole exercise resulted in adding 27 new turn restrictions to the map which is already highly detailed and up to date.

screen shot 2016-09-01 at 8 42 44 pm (Blue=added to OSM; Orange=not required to add to OSM; Red=Invalid detection or location)_

Exit and destination signs on motorways

Now that we have completed with turn restrictions in 3 test locations in Germany, we would like to continue working with community to review exit numbers and destinations in these 3 cities. We plan to follow the wiki to review and we intend to add OSM notes for the missing exit numbers and destinations for the community to verify and map. For this process, we will be using tasking manager and checkautopista2 for identifying the missing exit numbers and destinations. Here is the guide and detailed workflow of the task.

Happy to hear your feedback on the process and if anything could be improved.


From Mapbox Data Team

This diary post last week outlined an overarching goal of making OpenStreetMap navigable, and our intent to investigate and add missing turn-restrictions in Berlin, Stuttgart, and Wolfsburg using Mapillary as a source. We received some good questions from the local OpenStreetMap community about using Mapillary as a source. Considering the concerns of the community, we did a preliminary research on the Mapillary imagery to ascertain their recency. We want to share our findings here.
Here is an animation showing Mapillary traces in Berlin, Stuttgart, and Wolfsburg spanning the last six months (March - August 2016). Not surprisingly, Berlin was found to have the best Mapillary coverage. The coverage in Stuttgart and Wolfsburg was sparse in comparison.

Berlin2 Berlin Mapillary Coverage

Stuttgart2 Stuttgart Mapillary Coverage

Wolfsburg Wolfsburg Mapillary Coverage

Recency of Imagery

When adding data on OpenStreetMap using any type of source, recency is an important aspect to consider. The plan is to add data on OpenStreetMap only if Mapillary imagery is more recent than when the turn-restriction was added. If this is not the case, or there was a recent change in the area, the intent is to add a note, and rely on the knowledge of the local community to verify accuracy. Based on this approach, here are a few cases where turn-restrictions could be added. To the best of our knowledge, these are valid turn-restrictions that are not added on OpenStreetMap. To do this, we’re using the OSM Navigation Map to detect turn-restrictions, and their absolute positions using Mapillary. We’d appreciate if anyone with knowledge of these areas can verify if these detected signs are in fact correct or not.

screen shot 2016-08-23 at 11 48 50 am

We had carried out our preliminary research in reviewing Mapillary detected turn restrictions in these 3 cities, using OSM navigation map. We time boxed this task to 2 hours with two people working on Berlin and one each working on Stuttgart & Wolfsburg. We were able to find 25 missing turn restrictions out of the 110 we reviewed. Turn restrictions are categorised as valid/invalid/redundant based on the Mapillary detected signboards and by the OSM data present.

Case 1:

screen shot 2016-08-23 at 12 03 25 pm Missing No Left Turn (Link to OSM note)

Case 2:

screen shot 2016-08-23 at 12 08 56 pm Missing No U Turn (Link to OSM note)

Case 3:

image Missing only_straight_on (Link to OSM note)


screen shot 2016-08-23 at 12 45 20 pm

Missing only_straight_on (Link to OSM note)


screen shot 2016-08-23 at 12 54 41 pm Missing only_right_on (Link to OSM map)

Also, some other missing cases are listed here.

While we reviewed turn restrictions that can be mapped using Mapillary, we also verified some of the existing turn restrictions and encountered few cases where community feedback would help

Case 1:

  • In the case below, the image shows that there are restriction signages for each lane
  • Also the turn restriction added was a no_u_turn, which did not show up in the Mapillary.
  • In such a case, what is the approach community would suggest?

screen shot 2016-08-23 at 4 07 49 pm Link to the map.

Case 2

  • In this case the signboard is showing only_staright_on but it was added as two separate turn restrictions, no_left_run & no_right_turn.
  • As per the German wiki it should have been added as only_straight_on.
  • We would like to get feedback on adding such turn restrictions, what is the general convention the community follows?

screen shot 2016-08-23 at 5 38 25 pm Link to the map

Case 3

  • We have observed a no_straight_on restriction which seemed odd as it was on a dual carriage way with highway=teritiary tag.
  • We could not verify this with Mapillary images, as there was none on the road. It would be great this can be verified by the local mappers.

screen shot 2016-08-23 at 5 52 39 pm Link to the map

Based on the community feedback received, we are ready to add OSM notes for the missing turn restrictions if the community has no issue with this and also open to getting any thoughts you have on improving the OSM Navigation Map whether it’s feature requests, or bug fixes here.

Thank you :)


From Mapbox Data Team

Weekly roundup of edits

Posted by nammala on 19 August 2016 in English.

Here are a few observations from the OpenStreetMap edits between 8 August - 19 August. Most of these helped us understand common mapping issues faced by the new mappers.

  • Added untagged nodes 1, 2. These were reverted by the community.
  • Added nodes with numbers as names 1. Reverted by community.
  • Bad imports of data 1. Reverted by commuinty.
  • Deleted waterway=riverbank , natural=water tags and stream 1, 2, 3 respectively. Asked for clarification.
  • Deleted building 1. Asked for clarification.
  • Deleted highway=service roads inside the park 1. Asked for clarification.

It is always good to let the user know of such issues and encourage them to do active and quality contributions to OpenStreetMap.

Looking forward to another roundup next week. Happy Mapping.

Turn restrictions, exit and destinations are important components of navigation system and enhance the routing and guidance accuracy of any routing engine. To improve OpenStreetMap, broaden its reach globally and make it more accurate for routing, we would like to join hands with the community to map missing turn restrictions, exit and destinations in Europe using Mapillary as the primary source.

pasted image at 2016_08_19 04_49 pm


First stop is Germany, we want to concentrate on three major cities: Berlin, Stuttgart, Wolfsburg and map turn restrictions, exit and destinations, slowly branching out to other cities and countries in Europe.

Mapping workflow

Turn Restrictions

We have devised a simple way to add turn restrictions using the Mapillary and detected traffic signs using OSM navigation map that displays the detected turn restrictions from Mapillary, making it easy to know the position of the signage and to mark it as valid/invalid once it has been reviewed and mapped if required.

Marking a detected no left into a oneway as redundant restriction on the OSM navigation map

You can go through the detailed workflow: guide for mapping turn restrictions using Mapillary to know about the working procedure for mapping, tagging system and certain exceptional cases.

Motorway exit numbers & destinations:

Checkautopista2 by k1wi is a neat tool that highlights all the highways and their exits which makes it easier to add the missing exit and destination tags.

Here’s the detailed workflow for mapping exit & destinations using Tasking manager and Checkautopista2 with Mapillary as the primary source.

If you are a local mapper, please review the workflow and provide your suggestions on how it can be improved. When in doubt, notes will be added and local mappers contacted before updating an existing value.

Existing data

Current number of turn restrictions in 3 cities were extracted using overpass.

  • Berlin: 1057
  • Stuttgart: 828
  • Wolfsburg: 72

Current number of exit & destination tags in 3 cities extracted from overpass.

screen shot 2016-08-12 at 5 56 07 pm

Join in!

We have had tremendous support from the OpenStreetMap community so far, guiding us in every endeavor, suggesting us with new ideas and improvisations on how to make our workflows better, calling us out on occasional errors, answering our questions and clearing our doubts. We would love that collaboration and contribution to continue working together. Let’s all join in making OpenStreetMap the best!

From the data team at Mapbox

Understanding common mapping issues is helpful to know difficulties faced by new mappers and can give insight into improving the editors for a better mapping experience. Here are some of the issues observed between 4 July - 15 July on the map:

  • building=house tags added to the nodes of the buildings: 1, 2. These were reverted.
  • Roads without any tags: 1. Asked for clarification.
  • Deletion of highway=track ways without explanation or source: 1 . Asked for clarification.
  • Roads were deleted as they are ‘not public’: 1, 2. Community responded asking for clarification.
  • Duplicate buildings & incorrect tags: 1, 2, 3. Community responded with a comment.
  • Deleted roads: 1, 2. Commnunity responded with a comment.
  • Deleted landuse=residential tags: 1, 2. Asked for clarification.
  • Deleted highway=primary roads: 1. Asked for clarification.
  • Overlapping buildings: 1. Community responded with a comment.
  • Added duplicates of few buildings: 1. Was fixed by the community.

It is always good to let the user know of the mistake to encourage active, qualitative contributions to OpenStreetMap.

Look forward to another roundup next week.

Mapping Destinations Signs on US Motorways

Posted by nammala on 5 May 2016 in English. Last updated on 6 May 2016.

The data team at Mapbox has been mapping destinations signs in the US. Based on Mapillary images, Department Of Transportation (DOT) documents, crosscountryroads, and Interstate guides.


Imagery source- Mapillary

We started working on 9 states:

  • California
  • Florida
  • New Jersey
  • Maryland + DC
  • Pennsylvania
  • Washington state
  • Colorado
  • Texas
  • Illinois

We are using checkautopista for adding destination tags like destination,destination:street,destination:ref after verifying from the above sources.

The team worked on this task last month and reviewed 220 highways and added 3,417 tags

  • Number of destination tags added: 1663 (map)
  • Number of destination:ref tags added: 1481 (map)
  • Number of destination:street tags added: 273 (map)

This is the workflow we followed.

Happy Mapping!

Visakhapatnam is my hometown, a coastal city in Southern India, it is popular tourist spot with temples, hills, parks and beaches. This city is also home to Indian Navy’s Eastern Naval Command. A constantly evolving city, Visakhapatnam ranked 8th in the smart city list of the Government of India for futuristic infrastructure development.


Aerial photographs of Visakhapatnam by Candeo gauisus, CC BY-SA 3.0

I have done a lot of mapping of my hometown in the last 4 months. But after going through several mapping guides and discussion with my colleagues at Mapbox, I realized that I can improve my mapping even further.

So, I started cleaning up my earlier edits and added points of interest (POIs) with proper tagging and naming practices.

This is how I went about the whole process:

  • Add missing POIs.
  • Add correct tags for existing features such as roads, statues, sculptures,o verhead tanks, fitness centres, parking areas.
  • Correct alignment of roads based on imagery.
  • Remove duplicate roads.
  • Split roads into correct segments.
  • Add missing connections.
  • Fix letter case for names.

Throughout the process I made sure to go through the feedback on my changesets and made the necessary corrections. After working on the feedback the map looked cleaner and I continued adding POI’s and buildings.


  • Communication during the task and clarification of doubts straightaway.
  • Mapping my hometown helped me in getting to know the correct tagging system in OSM and naming protocols.
  • Shortcuts in JOSM
  • Proper use of Building Plugin
  • Using proper tags for road classification using Indian roads classification wiki

The entire process has been a great learning experience for me and it definitely helped me improve my mapping skills. That said, lots of features can be added in my hometown. So, I will be continue my work here on OpenStreetMap.

Mapping my Hometown

Location: Old Binnamangala, Bengaluru, Bangalore North, Bengaluru Urban, Karnataka, 560001, India

Hello OSM mappers,

I ‘m new to OSM community and this is my first diary post in which I want to explain my mapping experience in using field papers

As a part of mapping using Field Papers for which I selected an area in my neighborhood (Visakhapatnam), I have chosen Andhra University college of engineering. The main reason for selecting this region as area of interest (AOI) is, I had done my bachelors from this University and also it is not yet mapped in OSM.

The general idea was to micro-map this area using field papers by identifying the number of missing buildings,roads,hostel blocks,canteens,shops,paths,tracks,statues,gallery stands,layout maps etc. For this, I printed the field paper copy (which consists of already mapped OpenStreetMap data) of the selected area and went to the field for collecting the missing data. It was very interesting to go to the field carrying the field papers, pencils, erasers etc. Basically, it was my first experience to survey in this manner because previously I had carried out survey using instruments like Total station to collect the data, go to laboratory for analysis and finally make edits to prepare a map. So, it’s a different kind of exposure for me to survey using field papers. Then I started going through the area and I have drawn sketches on the paper of particular buildings and gave numbering to that so it will be easy for me to identify while mapping, and I carried out the same procedure for rest of the area. It approximately took 2 hours for mapping the entire University. Mapped Field Paper Uploaded

After completing the survey mapping I scanned the mapped field paper and integrated it into the digital environment i.e., JOSM using the field papers plugin. I used scanned field paper as one of the base map above Bing imagery for reference while editing, which made my work much easier in identifying the AOI’s.

In this way I completed mapping Andhra university college of Engineering (AUCE) using field paper procedure. Thanks to Mapbox for assigning me such a skillful task and giving me the exposure to this kind of open mapping. I would really appreciate the OpenStreetMap community members if they can review my work and give their valuable comments or suggestions in which I can improve further. Final Map