tl;dr the release notes 📗
The latest version of MapRoulette, 3.3.3, was released today on maproulette.org. There have been a few notable new features and updates since I last wrote about MapRoulette in the 3.3 release post, so here’s a new diary entry to talk about what has happened since in MapRoulette land!
Challenges are organized in Projects. A Project lets you, or your organization, organize Challenges that belong together. You can create as many projects as you like, and move Challenges between them if you want. Each Project’s page lets you review progress metrics and comments for all challenges in a project, combined. This is pretty handy, but also a bit limited. That’s why we added Virtual Projects. Virtual Projects are different in a few ways:
Just like regular Project pages, your Virtual Project’s page has progress metrics and comments related to all challenges that are currently in your Virtual Project. You create a Virtual Project just like you would a regular Project.
We introduced a Mapillary overlay in version 3.1.1, but it was not so great to use yet. We have improved it a lot, it now shows Mapillary image locations that are more relevant to the task location, and we use the native Mapillary viewer widgets, so you can zoom in and easily skip to the next or previous images in a Mapillary sequence.
We hope to further improve Mapillary integration in the future, for example by letting Challenge creators define tasks based on available Mapillary imagery at the task location. Let us know if you have other ideas for integrating Mapillary into MapRoulette in meaningful ways, and what challenge ideas you have based on Mapillary images!
When you complete a task, you can now add a MapRoulette-specific tag to the task. Currently, you cannot search for these tags in MapRoulette, but they do appear in the CSV and GeoJSON task exports the Challenge owner can download. That makes them particularly interesting for Challenge owners. Say, for example, you have a challenge in an area where you know there may not be enough high-quality imagery available for mappers to complete all the tasks successfully. You can ask mappers to add a tag when they encounter that situation, for example bad-imagery. Later, when you download the tasks export, you can analyze the tags and find out which areas didn’t have good enough imagery (and start an OpenDroneMap + OpenAerialMap project there 🙂 )
We will add more support for MR Tags in the future. Let us know what you want to use MR Tags for! You can email us at firstname.lastname@example.org or open a ticket on Github.
As always, find the complete release notes on Github! Happy mapping!
💨💨On to MapRoulette💨💨