Hi OSM folks! I built a free browser game on top of OpenStreetMap: enter any address, the game fetches the area (Nominatim + Overpass, cached server-side to go easy on the public servers) and turns building footprints into extruded 3D blocks.
building:levels / height decide how tall a building is and how many points it's worth, and tagged landmarks (e.g. Westminster Hall in the screenshot) give a bonus. Map data is credited in-game.
It's also a fun way to spot gaps in your neighbourhood's mapping – flat or missing buildings stand out immediately 😄
Play (free, no account, no tracking): https://kaijumietz.de/?lang=en
Happy to answer questions about the OSM → game pipeline!

Hi everyone,

I built Pendelradius (https://pendelradius.de), a map that shows how far you get from any starting point in Germany within a given time by public transport. You pick a start (or tap the map), a departure time and a travel time, and the map draws the reachable area in bands of 15 minutes. Tap any spot and it shows the connection with lines and transfers.

How OSM is used:
- Base map: vector tiles from OpenFreeMap (OpenMapTiles schema, OSM data)
- Place names for the search and the "which towns can I reach" lists: OSM place=city/town/village, districts from place=suburb
- "Nearby" line: supermarket, pharmacy, doctor, kindergarten, school etc. read from the tiles, with walking or transit minutes from the start
- Federal states via Overpass for the 255 city pages (e.g. https://pendelradius.de/koeln)

Timetables come from GTFS (DELFI via gtfs.de), updated weekly. All routing runs in your browser (a Connection Scan Algorithm on preprocessed files), so there is no backend, no account, no cookies and no tracking.

One thing I learned the hard way: I first showed the nearest "swimming pool", and it turned out to be someone's private garden pond. leisure=swimming_pool includes private pools and the tiles carry no access tag, so I removed that category. If you know a clean way to get only public pools (or other POIs) without running my own Overpass extract, I'd love to hear it.

Known limits: Germany only, scheduled times without delays, and some regional bus data is currently missing upstream.

I built this as a student project with help from AI. Feedback on the map, the OSM attribution or anything else is very welcome!

It's at https://husforhus.se, in English and Swedish.

You can drag a timeline to watch the city grow, search for any address, and open a card for each of the 77,743 buildings in the municipality: its year, where the year comes from, and for about 900 notable buildings a photo and a short Wikipedia text.

A few notes:

- Over half the buildings have no recorded year in open data, so they show as "Year unknown" rather than a guess. Ironically the oldest part of town has the biggest gaps: 77% of Gamla stan's buildings have no year in the open registers, against about 10% in Östermalm.

- Private houses show only their decade, never the exact year or an owner.

- It's all open data (City of Stockholm, Riksantikvarieämbetet, OpenStreetMap, Wikidata) and open source (star and contribute here - https://github.com/amirelion/husforhus), with no cookies or tracking.

If you know the year of a building that's wrong or missing, the card has a "Something wrong?" link, and corrections with a source are very welcome.

Guys, how can I map this staircase in Catarcione, Nova Friburgo, Rio de Janeiro?

Is located here: https://www.openstreetmap.org/#map=19/-22.292586/-42.517848

Now I don't want to continue 😅

Hi! I made North Up Daily, a free browser puzzle using OpenStreetMap data.

Each map is split into 16 rotated tiles, with place names hidden. Turn the tiles until streets, rivers and coastlines line up and north points up. Solving it reveals the location, but you don't need to recognise the place to solve it.

Everyone gets the same daily puzzle, and there is unlimited practice if you want another round. No account or download needed; it works on desktop and mobile.

Play: https://northupdaily.com/

The maps use OpenStreetMap data rendered with OpenFreeMap. Thanks to everyone who contributes to OSM for making projects like this possible.

I'd be curious which maps you find easier: dense street grids, or places with rivers and coastlines?

Muss hier Hilfe haben

Hi everyone, I have a question about MapTiler.

I’ve developed a non-commercial map website and integrated MapTiler maps into it. I noticed that the free plan includes 100,000 times of loads per month, but I’m not quite sure what exactly counts as a map load.

I’ve only clicked around on my website a few times, yet the number of requests has already reached 2,000. Does this mean the 100,000 monthly limit might not be enough if more people start using my website?

If so, are there any good alternatives to MapTiler that offer a more generous free tier, especially for a non-commercial project?

I’d really appreciate any advice or recommendations. Thanks!

As you might know, we at Top-O-Map run the tile backend for OpenTopoMap since January, and we now have something new. We got another server and on it we render the OpenTopoMap with higher resolution. 2 times the resolution, 4 times the pixels to be precise.

In addition the database is updated daily.

You can have a look at it over at: OnlineTopoMap

Let me know what you think.

I moved to the UK from Canada, and the number of war memorials here and around Europe really stood out to me. Every village seems to have one. I thought it would be good to have an app to keep track of them and maybe raise their profile, so I’ve built HonourMap. Most of the data comes from OSM (memorials, war cemeteries, battlefields and Stolpersteine), merged with Wikidata, and the map tiles are from OpenFreeMap.

https://honourmap.vercel.app

I ran into a few things along the way. Loads of memorials have no name, so I name them after the nearest village. A lot of plaques have no inscription tag, so I can’t tell what there for. Outside Europe hardly any CWGC cemeteries have an operator tag.

It’s a website for now, but I’m hoping to turn it into phone apps eventually. I’d like to know whether it’s easy to find your way around, and whether you think it’s an interesting use of the data. If there’s anything you’d change or add, including tags I should be using, please tell me.

Cheers

Open-Planet turns OSM data into a playable world. Pick any place, the game downloads its extract from Geofabrik, adds Copernicus 30 m heights and ESA WorldCover land cover, and builds it: roads laid out from their tags and each country's design rules (lanes, widths, junctions, bridges, tunnels), buildings from their footprints and levels, forests, water and golf courses as mapped.

It's a nice way to see your own mapping: drive the streets you mapped. Where the map's thin, it shows.

Free and open source (AGPL-3.0), with OSM credited in the game and README.

https://github.com/inlighten420/open-planet

Hi everyone!

I'm developing an outdoor mapping app called Teta Maps, using OpenStreetMap data for roads and trails.

One problem I've been thinking a lot about is missing footpaths, especially in less popular hiking areas.

I'm exploring a community contribution system where people can record actual GPS traces, suggest missing paths and help validate each other's observations before they appear on the map.

The difficult part is making this reliable. A single GPS trace doesn't necessarily mean there's a real public trail, and satellite imagery isn't always enough to distinguish a path either.

I'd be interested to hear how OSM contributors think such a system should work, especially regarding verification and keeping the resulting data useful to the wider mapping community.

Here's the project: https://play.google.com/store/apps/details?id=com.tetasports.maps

Any thoughts or criticism are welcome!

To the bus stop tags or as a separate object?

I will help integrate and teach qgis and postgresql

If GIF on this post doesn't work https://i.imgur.com/nvUx4Zc.mp4

Music: https://www.audionetwork.com/browse/m/track/after-the-fall_84169

Motion extraction tutorial: https://youtu.be/NSS6yAMZF78?t=226

As nobody mapped this part, I decided to waste my time only for map this house, supermarket and this bar.

I don’t know the name of this bar, but anyway, look for this link:

https://www.openstreetmap.org/#map=19/-22.293772/-42.518667&layers=N

Does anyone else wander around town updating business opening times like I do hahahaha

I'm #1 this week!

Hi all, one thing has always bugged me: OSM and Wikidata hold an incredible amount of geographic knowledge, but it mostly ends up in navigation apps and routing. There’s hardly anything that just lets you explore the world the way a good old atlas does, with rivers, lakes, mountain ranges and countries, their records and rankings.

So I built one: Open Earth Atlas (https://openearthatlas.org/en/), a free interactive globe built entirely on open data. No account needed.

Questionable values aren’t hidden. Instead of quietly patching odd values from other sources, the atlas shows them as they are, marks them with ⚠ and links to where they can be fixed. All open issues are collected on one public page, currently about 1,900: https://openearthatlas.org/en/improve-data

When something is fixed upstream, the next update picks it up and records it as “improved”, with the old and new value. The idea is that the atlas helps make the source data better, not just use it.

How OSM fits in:

• River courses come from OSM (ways and river relations), about 59,000 rivers.
• Lake outlines come from OSM wherever a matching water polygon has a wikidata tag. HydroLAKES only fills the gaps.
• Every river and lake page has a link that opens iD on the exact object.
• When an OSM lake outline differs a lot from the satellite-derived one (typically reservoirs mapped as river sections), it shows up on the improve-data list instead of the atlas silently picking one.

Example: Lake Constance, https://openearthatlas.org/en/lakes/europe/lake-constance

To be upfront: I vibe-coded this over the past few weeks, and with 250,000 pages built from messy real-world data, I’m sure there are plenty of bugs and odd results I haven’t found yet. This is very much a start, and I plan to keep working on it for a long time.

So I’d really like to hear what you think of the idea in general. Is this useful to you as a mapper? What’s missing, what feels off? And if anything about how it uses OSM data clashes with community conventions (e.g. matching lakes via the wikidata tag), I’d like to know that too.

Hi! We’re building WikiPowder, a free ski resort guide with interactive piste maps powered by OpenStreetMap (OSM) data via OpenSkiMap and OpenSkiData.

We wanted to share a few things we’ve learned along the way and, of course, express our gratitude to the OSM community for making this project possible. We all come from tech backgrounds, so about 90% of it was vibe-coded. However, that also brought some challenges we had to overcome along the way, which ultimately helped us deliver what we think is a solid foundation.

Working with ski data at scale has surfaced some interesting challenges and insights that might be useful to fellow OSM contributors:

1. Commercial ski domains rarely map to OSM ski areas on a 1:1 basis. Large ski domains are often split across several OSM ski areas, sometimes even across national borders.
2. Resort names aren’t always unique. The same name can refer to resorts in different countries or even on different continents, making naive name matching risky. Automating this process is complicated, so manual verification was required in many cases.
3. Official resort coordinates can be misleading. They often point to the village centre, town hall, or tourist office rather than the actual ski slopes, so they don’t always align with OSM geometries.
4. Published piste kilometres vary significantly by source. Resort operators, third-party guides, and measurements based on mapped geometry can all report different figures because they use different methods. This is a nightmare. We can’t provide accurate or 100% reliable kilometer coverage.
5. A single named piste may consist of multiple OSM segments or sectors. This makes matching and aggregating piste data more complex than it might seem at first. We found a way to structure the data, but representing it is still complicated.

We’re still working through some known issues, but we’ve now reached a stable enough version to start rolling it out (just in time for the next season!).

That’s it for now! We’d love to hear your feedback, and we hope you find the project interesting.

Thanks to everyone in the OSM community for making projects like this possible!

Update:

Folks! We’ve been trying to respond to your feedback, but it looks like all the comments have been removed or moderated, perhaps because the user account is brand new.

Just wanted to let you know that we really appreciate your feedback! 🙏 One of the first decisions we've done is pivot towards a more community-driven approach, allowing people to edit and improve existing OSM slopes. The data is already good, but it’s not perfect, and we want to help the OpenStreetMap community make it even better. The idea of setting a general map with all the slopes is also quite interesting.

We’re also considering developing an open-source library to make it easier to manage multiple OSM segments. That’s currently our main focus, although we’re also fixing bugs along the way.

Thanks again for taking the time to share your thoughts and help us improve!

I make Runplanner, a free running route planner built on OSM, and used its loop generator to draw 40 random 5 km running loops in each of 25 cities, then counted the mapped traffic lights each loop crosses.

Two things OSM people may find interesting:

- Tagging style matters. Counting only highway=traffic_signals missed a lot: adding crossing=traffic_signals, crossing:signals=yes and UK crossing_ref (pelican/puffin/toucan/pegasus) raised the total by 22%, and doubled Birmingham. Lights within 20 m are merged, so a junction mapped both ways counts once.

- Jakarta and Bali had to be left out: their centres have about 2 mapped junction lights per km², against about 43 for the middle city. Probably a mapping gap more than a lack of lights.

Full method, limits and a CSV for all 25 cities: https://runplannerapp.com/blog/traffic-lights-per-km. © OpenStreetMap contributors, ODbL.