Recently at the Portuguese OpenStreetMap Telegram group we have been discussing the issue of the Pokémon Go! Players that become OSM contributors with bad intentions, by adding fake parks or wrongly to their ingame interest.

We decided to check how many parks existed in Portugal by using overpass turbo back in August (kudos to Luis Forte for the help). To our surprise there was over 7000 parks. We decided to create a map roulette mission to validate the parks. Some are indeed hard to validate by arm chair mapping, some are not. Up til now we have validated 20% of the parks on OSM and acknowledged that more than 12 percent were indeed badly tagged and only 7% were correctly tagged.

As example,gardens of private property or grass in roundabouts. https://maproulette.org/challenge/9053/task/24888572

https://maproulette.org/challenge/9053/task/2488485599

https://maproulette.org/challenge/9053/task/24883197

During this we acknowledge that some of these tags were added long before Pokémon Go existed,which left us intrigued. We investigated that most of the users were using id editor and realized that the translation on Transifex to Portuguese was mixing synonymous of gardens, grass and some of those were done by Brazilians (for those that are not familiar, Portuguese from Portugal and Brazilian Portuguese have even harder differences than English from UK or English from USA). We decided that the translation needed to be fixed, António Madeira and myself started to translate what’s not translated and validating what already was. This should be an example to none English communities as having translators that have a high knowledge of OSM tags, discussing the best words to be added to synonymous of tags is crucial to have a consistent translation to id, which is the most used editor on OSM world. This is an important step to avoid misleading tags to newcomers,but obviously won’t fix everything as some will add the park tag for their own Pokemon Go activity.

Therefore we decided until the map roulette mission is going and probably afterwards, we have a OSMCHA filter to flag the new parks being added with Reasons for Flagging “Park added by new user”. Everyday or two days we check and enquiry the contributor about the park that they recently added, the concept of what a park is does not meet our OSM tag. As common examples we have contributors using park for gardens or for picnic sites. City halls usually refers to parks, gardens or picnic sites in Portugal as “Parque” which misleads contributors that are not informed of the OSM park tag. If the contributors does not reply, continues to edit and we do an internet search and can’t find any reference to the park in question,the tag is changed to garden. Red flags are parks that either have the word garden (Jardim in Portuguese) or that have been added without name. Common sense is an important key on this, don’t be a dictator and explain to the contributor what a park is in OSM.

The map roulette mission is still available, feel free to contribute as mentioned some don’t require knowledge about the area in question are can easily be fixed remotly. Tip: activate the nearby feature on map roulette, usually a contributor that added parks wrongly added multiple wrong tags in the same are, which you can edit as a batch quickly to avoid going back and forth between Map Roullete and the editor of your choice. In case of doubt, skip, we will deal with the ambiguous ones later when the mission is completed

Map Roullete mission link

Thanks to those that already helped validating 20% of the parks in Portugal.

Im posting this trying to support someone that contributed a lot to OSM via his street level imagery, either being on Mapillary or OpenStreetCam for others to map on OSM. If you could donate, to help him repair his vehicle to get back on photo mapping, go to his GoFundMe page

Heres the story:

My name is JB Brown. Online I am often known as JBTHEMILKER. I have become something of a legend in the digital mapping world. In just over a year of contributing to Mapillary I became their top worldwide contributor with 8.3 million images and 146 million meters mapped. Mapillary account

I’m also #2 (I was #1 For a while) on the Openstreetcam app I’ve contributed 1.2 million images in less than 4 months and mapped 22,400 miles for them. All this has been done at my own expense.

I’m a retired, disabled firefighter. For the last 5 years I’ve been serving the Amish of Ohio by hauling families when their trips were longer than they can go with a horse and buggy. My van had nearly 400,000 miles on it. Recently the repairs out did what I was bringing in. Then in Wisconsin the transmission went. I ended up giving what was left of my beloved van to the firm who towed it up in Wisconsin. The other side of who I have become is the mapping photography I’ve been doing. Back when Google Earth was accepting pictures I was among the top contributors in this country. When Google pulled the plug on Earth I started contributing to Mapillary and later to Open Street Cam, both are firms that are working to gather digital data to improve our digital maps. I am the top contributor worldwide on botth these sites or I was until my van broke down on Christmas eve. I’m asking for contributions now, just as I have given freely in order that I might continue to serve those who have come to depend on me, those who I enjoy serving.

For those that have check my previous tutorials, are aware of the benefits of using Mapillary imagery (especially the traffic signs detections), however some crosswalks don’t have traffic signs nearby. By using Mapillary AI we are able to detect them fast and add them to OSM. Here’s the video tutorial how you can use AI Detections for OSM.

Find out more about Mapillary AI Detections

My previous tutorials: ID Editor and JOSM

Interesting reading: https://agile-online.org/images/conference_2017/Proceedings2017/shortpapers/77_ShortPaper_in_PDF.pdf

Abstract

An increasing number of crowdsourced geo-data repositories and their services allows volunteer mappers to utilize information from various data sources when contributing data to a crowd-sourced mapping platform. This study explores to which extent OpenStreetMap (OSM) contributors use the crowdsourced street level photo service Mapillary to derive mappable data for OSM during their editing sessions in the iD and JOSM editors. We cross-check the location of OSM edits with the geographic areas from which OSM contributors loaded Mapillary images into the editors to determine which OSM edits could have been based on information from Mapillary images. The findings suggest that OSM mappers are beginning to utilize information from street level images in their mapping workflow. This observed “cross-viewing” pattern between different datasets indicates that the use of data from one VGI platform to enhance that of another is a real phenomenon, leading to implications for VGI data quality.

After seeing the diary of how to use Mapillary to add building attributes on The state of San Francisco buildingsi decided to create this article on how to use Mapillary as a tool to improve OSM road data. This article will focus on how to use Mapillary traffic sign detection to implement turn restrictions, Mapillary imagery to add lane value and turning lanes. I won’t get into how to capture Mapillary images using smartphone or action cams, as you can find that information on Mapillary website check here and you can request a car or bike mount for your smartphone here

(Please note that from my experience, after uploading the photos to Mapillary, the traffic sign detection can take from 24 to 96 hours to be processed and being displayed on the map).

Editor used JOSM. JOSM plugins needed: Mapillary; RoadSigns; Turnlanes-tagging; Turnrestrictions.

Open JOSM, go to EDIT and then pick PREFERENCES. Once in the options, head to the PLUG-INS menu and search and install these three plug-ins: Mapillary (for being able to use Mapillary imagery and “Mapillary object layer”); RoadSigns (if you want to add the traffic signs to OSM); Turnlanes-tagging (for being able to add turning lanes); Turnrestrictions (to create turn restrictions on intersections).

To make a thematic editing easier, head to VIEW/Map Painting Style and select Map Paint Preferences. Scroll until you find “lane and road attributes” by Martin Vonwald, select it and send it to the right using the arrow and then click ok.

Head back to VIEW/Map Painting Style and select LANE AND ROAD ATTRIBUTES, using this layer will be easier to check the current attributes on the OSM data (notice the number of lanes and lanes direction being displayed).

Pick a location with Mapillary photos that you or others have gathered. Go to IMAGERY and select: Mapillary and Mapillary object layer (the traffic signs will be shown on the map and the green dots are the Mapillary photos, you can turn off the layer if its too much information for you to handle.

Mapillary object layer with the detected traffic signs: ## Case 1: Adding turn restrictions

In this intersection it’s mandatory to go straight (notice that the there’s a traffic sign on the Mapillary photo layer, which means that a traffic sign was detected in that photo, if you pick that photo on the map (turns it into orange), the photo will be displayed and you can see the sign in the photo.

Lets add the turn restriction to the OSM data (notice, make sure to split the lines in every intersection or when there’s different attributes): First select the “from” line and then press CONTROL key on your keyboard and select the “to” line.

On the TURNRESTRICTION, click on “create a new turn restriction”, a menu will pop up with the road names. In this case pick “Straight Only” and click ok.

Turn off both Mapillary layers and notice a Straight Only sign appears on the Data Layer. Submit the changes to OSM.

Case 2:

Adding speed limits and bumps

Notice the traffic sign with the speed limit of 40 that was detected on the Mapillary object layer.

Lets pick create a node in that line and move the node to where the traffic sign is located and press “P” to split the line. On our right pick “+add” on the tag and enter the “maxspeed” and its value.

Add a bump. Check the detected bump sign by Mapillary.

Create a node in the line where the bump is (notice, bump signs are located 50 meters or less before the actual bump, so make sure to click on “next picture” on the Mapillary photo preview, until you visualize the actual bump).

Go to the menu and go through PRESETS/HIGHWAYS/WAYPOINTS/TRAFFIC CALMING and pick BUMP

The bump has been added, submit changeset to OSM.

Case 3:

Adding turning lanes

Notice the lane turn restrictions detected by Mapillary (left one is mandatory to go left and the right lane turn left or go straight).

Let’s use the Turnlanes plug-in to add the data to OSM. First select the line, then ALT+SHIFT+2 the plug-in menu will pop up. Add the number of lanes, in this case 2, and the mandatory turning lanes (left lane goes left, right lane goes left or straight)

Click ok. Notice how useful the “lane and road attributes” by Martin Vonwald is to visually display the data you just added. Submit changeset to OSM.

Case 4:

Adding traffic signs

Give way sign detected by Mapillary

Create a node in the line, select it, go to PRESENTS/TRAFFIC SIGNS/pick the sign

Menu will pop up, asking the location of the sign and in which direction does it apply.

Apply and notice the traffic sign is now added (you can clearly spot it as it has a white background, which does not occur with the Mapillary object layer that is transparent).

Case 5:

Adding sidewalk information:

By navigating through Mapillary imagery you can add the sidewalk attributes.

Notice on the Mapillary photo that after the intersection, there’s only sidewalk on the right side of the way.

Select the line before the intersection and add the a tag with “sidewalk:both”. Select the line after the intersection and add the tag “sidewalk:right”

As you can see with the “lane and road attributes” paint style you are now able to see the sidewalks attributes.

By implementing this workflow, we can assure high quality road data on OSM and the best data for routing.

I advise you if you have a strong local community of mappers to have a similar approach as Chetan did and use a OSM Task Manager to better organize: Collecting Mapillary photos; Adding the data to OSM; Validating.

Similar approach can be used to add street names, house numbers, fire hydrants or POI (like stores, bars, etcetera) if you capture photos on Mapillary with the smartphone pointed to the sideways instead of forward.

If you use OSMand, I recommend you to check how to add Mapillary overlay, so you can calculate your route to capture new sequences of streets that aren’t on Mapillary

Hope it helps, capture photos with Mapillary and improve OSM with them.

Happy mapping