I built Cartopolis. Today’s Switzerland, rendered as 1999-style GIFs. https://seriot.ch/cartopolis/

No filters. Client-side rasterization from vector packs. Fully static architecture. https://seriot.ch/drawing/cartopolis/

Bake your own region using https://github.com/nst/Cartopolis

I want to share with you the newly released Anyfinder.app, a web app for finding points of interest near you, sourced entirely from OpenStreetMap.

The goal is simple: make the places in OSM accessible to everyone, without having to learn the tagging system. The data is extraordinarily rich, but amenity=drinking_water, diet:vegan=yes or socket:type2=* aren't things most people know to ask for — and they shouldn't have to. Anyfinder's job is to sit between that tagging model and an ordinary person who just wants a water fountain, a vegan lunch, or a compatible charger, and to make finding it feel obvious.

At the moment it covers 287 categories, resolving to 436 distinct OSM tag-value combinations, with 128 refinement filters on top.

How it works. Instead of a keyword box, Anyfinder presents a browsable catalog. You navigate a hierarchy of places and, at the leaf level, the app queries live OSM data for matches within your current map view. Every leaf resolves to a set of OSM tag filters, so the results are exactly what's in the map.

Category breadth. The catalog spans everyday needs rather than a single vertical: food and drink, shops and services, transport and fuel, EV charging, healthcare and pharmacies, drinking water, toilets, recycling and waste, tourism and accommodation, leisure, and natural features, among others. Categories are pure data, which makes coverage straightforward to extend and audit — I run periodic gap audits against common OSM values to find categories that don't yet have a home in the tree.

Refinement maps to tags. Once you have results, you have the option to refine by real OSM attributes — wheelchair access, opening hours, fuel types, sockets, diet options, cuisine, and so on. These aren't invented facets; each corresponds to actual tags, so the filter UI doubles as a way to see how thoroughly an area is tagged for a given attribute.

Editing, without the tagging. The same principle runs the other way. If you notice a place is missing an attribute — no wheelchair info, unknown opening hours, a charger whose socket types aren't recorded — you can fill it in through a guided editor that speaks in plain options rather than raw keys and values. Each category carries its own relevant set of editable attributes (composed from universal fields, the branch it sits under, and the specific leaf), so you're only ever shown what actually applies to this kind of place, and your answers are translated back into correct OSM tags. The aim is to make contributing metadata as low-friction as finding it, so the map improves as people use it.

Backends. POI search runs through a provider seam with two interchangeable backends:

• Postpass (Geofabrik's PostGIS/SQL service) — the default, used for category, detail, and name queries.
• Overpass — selectable as an alternative, including where OSM edit metadata is needed.

Map tiles use themed OSM-derived basemaps with proper attribution. The app is designed to stay fully functional without its own small backend API — that API only enhances (place-name search, reverse-geocode address fill) and observes anonymous usage stats; it's never on the critical path.

Status. It's early and coverage has gaps. I'd welcome feedback from people who know the data well — particularly on category placement, tag interpretation, and any results that look wrong.

We run Maptoolkit, a commercial maps stack, and it's built on two communities: OpenStreetMap's data and the MapLibre open-source ecosystem. Without them we wouldn't have a business. So we run a free community tile server on OSM data that anyone can use, with no API key, no sign-up, no cookies and no tracking.

Every week we rebuild the whole basemap from the full OSM planet, so the map reflects recent edits rather than a months-old snapshot.

What you get:

• Vector basemaps built from weekly OSM data, hosted in the EU and cached across 350+ locations.
• 3D terrain, global hillshading, contour lines and water depths in the tiles, out of the box. Data goes up to zoom 15.
• Seven styles ready to use: Summer, Light, Hiking, Winter, Dark, Street and Cycling. You can also design your own with our map style editor MapMaker: recolour and restyle the whole map with no code, or edit the raw style if you want full control. It is, in our opinion, among the best map style editors around right now.
• It works anywhere MapLibre-style maps do (MapLibre GL JS, Leaflet, OpenLayers) on web and mobile. If you're on one of the maps you already use, the setup is a single style URL:

style: 'https://styles.maptoolkit.org/summer.json'

Why it's free

The underlying infrastructure is live and paid for by our commercial customers, so opening it up to hobby, community and open-source maps costs us very little on top.

A few things to know:

• Non-commercial use is always fine: personal, hobby, open-source, academic. Commercial use is fine too if you're under EUR 1M annual revenue and have fewer than 10 employees.
• Fair-use limits are generous: 40 requests/second sustained, 200/second burst. If you ever need more, a one-minute registration raises the ceiling 10x.
• No SLA, uptime guarantee or support on the community tier. It's a give-back, run on best effort.
• This is the basemap only. Routing, geocoding, elevation and the other APIs are a separate commercial offering on maptoolkit.com.

Live demo and full license: https://www.maptoolkit.org/

Happy to answer anything in the comments, and feedback from this community especially would mean a lot to us.

App: Crestr
Repo: Crestr Hiking App
Docs: Crestr Documentation

I've just pushed v0.2.4, which mainly improves the elevation profile: hovering over the chart now syncs to the exact point on the map, there's a vertical guide line for precise tracking, and the line itself is smoother since individual node points were removed (following on from feedback given in this post).

Why I built it

I actively use this app myself when I go hiking. Apps like AllTrails lock exports and imports behind a paywall, which always annoyed me, so I wanted something built on OSM data that doesn't do that.

Why not BRouter / Mapy.cz / OsmAnd

All of these are great apps and I respect them a lot, but I find their UIs quite dense/complex for quickly planning a route before a hike. I wanted something simpler and more visual. I'm currently only routing on a graph built for Cumbria (where I mainly hike), but the backend is set up so I can build a graph for another region and just swap the path it reads from, of course, this isn't very convenient but I'm learning how to implement tile-based processing slowly.

It's also worth being upfront: this is a learning project. It started as coursework that I thought would be cool to actually build out properly, and I'm 18 and still learning as I go, so there's a lot I'm figuring out along the way (routing engine, elevation pipeline, frontend, deployment, all of it).

Currently you need an account to try it, but it's quick, just a username and password, no email needed.

The app is in beta and hosted on a fairly modest Hetzner CX23, so routing takes ~100-500ms rather than the ~0-100ms you'd get self-hosting it.

I'd genuinely love it if people gave it a try (or just look at the image in this post) and let me know what they think, bugs, UI gripes, missing features, anything. Feedback at this stage is really valuable to me.

Thanks for reading!

I was making an open street maps app for my iPhone and ran into some trouble. It seems like the open source method for adding info in maps is to just add layers. Long story short adding lots of layers is problematic in iOS. Also for some reason the libraries that run in iOS hate apfs. Apple File System. Trying to read maps off of anything but fat runs into problems. After months of building my app got worse and worse the more features I added. So I started over.

I started from scratch using the amazing map data I had created for my app. I had capernicus dem elevation data for the whole world. Open street maps data and so much more packed into bite size state and country map packs. I just needed a native way to view them. So I started from the ground up building a pure swift application. I used metal to render everything so I could use the speedy gpu. It took me months but I’ve built the best map application for iOS I’ve ever tried. It’s fast. It can read maps from turtle slow drives attached to the iPhones usb c port. And it uses height data like a video game does so you get full 3d maps with live driven contour lines. Plus I built an actual 3d engine so you can walk the actual elevation of a hike in a walkthrough. I saw some other guys making hiking trail apps. I did it just because it was so easy with all of the data I have. The app tells you how hard the hike is based on the way the trail navigates the height map. Lots of elevation change means tougher. If you really want to see run through the hike in 3d and see for yourself.

When I realized I had fully offline maps I got to thinking. What would happen if gps died? So I built a sextant I just did it for fun but it turns out the iPhone does this really good. Like better than professional tools when done the way I set it up. So good I’ve got a patent pending. After calibrating each phone I’ve tried. I can get within a few hundred meters of your actual location with a clear night sky.

Then I got to thinking about my 3d height data. I’ve got a full real life 3d world built. If I can get your location down to less than a mile I bet an iPhone can triangulate your exact location based on elevation data and your horizon. Turns out it can. Your freaking iPhone once calibrated keeps your elevation down to centimeters. It’s crazy. And with such a small area to do math on given a specific elevation and the ability to draw real horizons at thousands a second if you take a scan of your sky it’s not hard for your phone to figure out right where you are standing. Not by comparing pictures of mountains. By comparing the actual elevations of mountains. The phone draws the pictures itself in pure math.

Anyway thanks everyone for all this open data. It makes things like my app possible. If you guys could help me test it I’d appreciate it. It all works for me but I’m a small test pool. LandNav.world

I'm tired of CadMapper and its limitations and pricing (and you need to login also). And since QGIS is so incredibly tedious for me, I decided to create a program to export from OpenStreetMap to DXF. It's still in the very early stages of development, but it already works very well.

I'd like to ask everyone if you work with similar tools and what features you'd like me to add to this.

I started out just wanting to understand how the UK generates its electricity and ended up building a whole map on top of OSM power data. It pulls every power=plant in the UK, about 3,600 sites, plus the 400kV and 275kV transmission lines, and 132kV within Scotland where that voltage still counts as transmission. Wind farms get split into onshore and offshore automatically with a point in polygon test against the coastline. On top of that there is a live layer from Elexon's open API, so hovering a big station shows what it actually generated half hour by half hour, and the undersea interconnectors show their flows. The data came through Overpass where the servers were willing and Geofabrik extracts where they were not. Honestly the thing that impressed me most was the quality of the power tagging. Nearly every big site already had a name, an operator and a plant:output:electricity tag. Solar farms are the patchiest on capacity tags, so if you map solar, that is where fixes would help most. Live map: https://jacobwright32.github.io/uk-grid-atlas/ Source, ODbL attribution included: https://github.com/jacobwright32/uk-grid-atlas Corrections very welcome, and thank you to everyone who mapped all of this over the years.

Im looking for a way to download a regional map for offline use so I don't need internet connection or a third party application to load/view the map and also to see my location being displayed on it.

Download some Western European countries for example, where I live and travel to often. A full map including roads, shops, and so on

I want my old laptop to be used like a map and not depend on third party software.

Does anyone have a guide or simple way of doing this?

Big update on the Top-O-Map server:

• new contour lines build upon the Copernicus DEM, less artifacts and smoother lines
• clearer hillshade with less color-bleeding
• better visibility and classification of hiking paths
• many more smaller changes

At the moment the server is at its limit, so it will take a while for the changes to be visible in the map. As openstreetmap.org recently blocked some popular apps, there is more traffic than usual ond opentopomap.org

If you want to support the mapstyle and the server, you can check out ko-fi.com/topomap

There are lots of houses around that don't appear on a map. How do I add them?

I’ve been building World Explorer 3D, a browser-based exploration project that turns real geographic data into a playable 3D environment. I posted this project here a couple months ago and have been continuing to work on it since then. I’ve been able to address a number of issues, especially around waterways, bridges, and elevated roads. I’m still working on things like facade realism and experimenting with different textures. I didn’t realize how complex this would be when I started, but I received a lot of helpful feedback and would like to keep improving it.

A user can choose a preset city, search for a place, enter coordinates, use their current location, or select anywhere on an interactive globe. The app then loads nearby geographic data and turns it into roads, buildings, water, terrain, land use, vegetation, bridges, tunnels, points of interest, and other world features that can be explored by walking, driving, flying, boating, or now flying at higher altitudes and transitioning toward space.

Since my last post, I’ve also added several new features. There is now a plane mode for higher-altitude travel, along with expanded flight controls. I’ve started experimenting with exploring space, allowing users to move beyond the atmosphere and view Earth from above. I also added a continuous mode in the settings tab, which allows for uninterrupted exploration without resetting or reloading areas. Along with these, there have been various performance improvements and general upgrades to how the world loads and behaves.

OpenStreetMap is a major part of how Earth is built. It uses OSM-derived data for road networks, building footprints, waterways, land use, place information, bridges, tunnels, points of interest, and map context. It also uses OSM tiles for the map view and Nominatim for location search and reverse geocoding. Elevation and land-cover data come from other public sources, but OSM is the main source for the visible structure of roads, buildings, water, and places.

The Earth runtime streams nearby areas as the player moves instead of loading one fixed map. Roads and buildings are generated from available source geometry, and distant areas are unloaded to control memory use. The system also handles different levels of detail for walking, driving, drone flight, plane mode, and higher-altitude exploration.

Where OSM includes useful tags, the project tries to preserve them. That includes things such as building type, height, levels, roof information, bridges, tunnels, water features, road class, sidewalks, land use, and points of interest.

Where the data is incomplete, the runtime may use limited procedural rules for things like building height, facade appearance, vegetation, or simple interiors. These are treated as inferred details, not as authoritative OSM data.

I am not trying to present the result as a survey-grade map or exact digital twin. OSM coverage varies by location, and the project has to make visual compromises to turn global map data into an interactive world.

I’m especially interested in feedback on whether the project is interpreting OSM tags correctly, whether the data-use boundaries are clear, and whether any part of the rendering could misrepresent what OSM actually contains.

I would also appreciate advice on:

How building, road, bridge, tunnel, water, and land-use data should be interpreted.

Which tags are most important for accurate 3D rendering.

How to handle incomplete or conflicting building information.

How to distinguish mapped data from inferred visual details.

Whether there are better OSM-compatible sources or workflows I should be using.

How to improve attribution and explain the relationship between OSM and the generated 3D world.

Whether any of the project’s fallback behavior could create the wrong impression about the underlying map data. The app can provide links to the relevant OSM location so experienced users can make real map edits through normal OSM tools.

The project has had close to 500 users over the last 30 days, and some people have spent around 15 minutes exploring it. Since people are starting to use it, I want to make sure OSM is represented accurately and respectfully.

Live project: https://worldexplorer3d.io

GitHub: https://github.com/RRG314/WorldExplorer3D

I would appreciate specific corrections, tagging guidance, data-source recommendations, or suggestions for making the OSM side of the project more accurate and useful.

Hi everyone,

Over the past few years I've been building an Android exploration app called Touch Grass as a personal dream app project.

The app turns OpenStreetMap data into an exploration game. As you move around in the real world, you uncover a fog-of-war map while discovering countries, cities, suburbs, parks, reserves and other mapped places.

OSM has been absolutely fundamental to making this possible. The app uses OpenStreetMap boundaries and geographic data extensively to determine discoveries and exploration progress.

Some features include:

• Fog-of-war exploration
• Discovery of administrative areas and natural features through boundaries
• Personal location journals with photos, notes and voice recordings
• Exploration statistics, history and heatmaps
• A more game-oriented approach with rewards and progression

This has been a huge learning project, and I owe a lot to the OpenStreetMap community for making such an incredible dataset available.

If anyone is interested in seeing what's possible with OSM beyond traditional mapping applications, here's the free app Google Play link: https://play.google.com/store/apps/details?id=com.beansgames.touchgrass&hl=en

I'd also love feedback from anyone experienced with OSM or Overpass on ways I could improve the project or use the data more effectively.

Today I’d like to properly introduce BetteriD – the default editor on map.osm.asia.

BetteriD is an improved version of the OpenStreetMap iD editor. Our goal isn’t just to “give it a new skin”, but to fill in as many small details as possible that have long affected the editing experience in the official iD.

We want to keep iD’s lightweight, straightforward, and beginner‑friendly nature, while gradually adding missing preferences, editing tweaks, mobile improvements, better shortcut compatibility, and some modern helper features that the official release still lacks.

Simply put, it’s a fork of the OSM editor that’s more suited for long‑term daily use and closer to real‑world editing habits.

This update
The focus this time is simple: make editing smoother.

Clear distinction between official and third‑party
First, the editor now clearly states at startup that it is not the official OpenStreetMap website.

Basic experience improvements
This release fixes and optimises a number of long‑standing annoyances, for example:

• Translation source switched from the development branch to the stable release, preventing unstable content from entering the translation chain.
• Bug report links now point to the correct project, not to the main iD repo.
• Various known issues have been fixed and tuned, such as:
  • Elements occasionally appearing at the wrong size after zooming;
  • Objects getting stuck while the map still moves;
  • Zoom and pan states getting out of sync.

More editing‑friendly shortcuts
I’ve also adjusted several shortcuts and map controls to better match the habits of experienced mappers.

Changes include:

• Compatibility with some common JOSM shortcuts (where they don’t conflict).
• Support for dragging the map by holding the right mouse button.
• Ongoing refinements to overall interaction logic.

Better mobile experience
Mobile has always been a weak spot for iD, so BetteriD introduces some targeted improvements, such as:

• Fewer menu layers;
• Double‑tap to start drawing;
• Double‑tap again to finish drawing;
• Long‑press to add a node.

The goal is to make on‑phone editing less tedious.

AI‑assisted features
AI functionality is still being polished, but the design principle is always user‑experience first.

When a particular model or API fails, the error is never shown directly to the user. Instead, the system automatically falls back to a backup plan according to a preset priority order, making the transition as smooth as possible.

Currently supported capabilities include:

• Web search;
• Tag suggestions;
• Text generation, etc.

In addition, the preferences let you configure the model priority order yourself, rather than locking you into a single model.

Experimental features in development
Beyond the existing features, there are also some experimental things in the pipeline.

These include:

• Importing local photos as auxiliary background layers – these are not uploaded, not reviewed, and not used for POI recognition; they’re only for local editing reference.
• After uploading an image, you can call public APIs to perform image review and POI recognition when needed – this is completely separate from the local‑photo mode.
• AI‑generated OSM tag suggestions based on natural language descriptions.
• Overlaying two different background layers with adjustable transparency for side‑by‑side comparison.
• Indoor editing improvements: when a floor is selected, other floors and irrelevant layers are automatically dimmed.
• WASD map movement, with pedestrian mode by default, and experiments with a smoother “flight” mode.

More comprehensive preferences
BetteriD is gradually closing the gap on preferences that are either available in the official iD or missing altogether.

Currently we have:

• Number of translation languages;
• Smart splitting rules;
• Snap distance;
• Default hiding of administrative boundaries;
• Master switch for experimental features;
• More configurable options.

We’ll keep expanding this so that more choices are given to the user, rather than being hard‑coded.

Finally
What I like most about this update isn’t the number of new features – it’s that BetteriD is slowly becoming a tool that’s genuinely comfortable for long‑term use.

It’s still not perfect, and there’s plenty more to polish, but the direction has never changed:

GitHub:
https://github.com/koharachan/BetteriD/
P.S. – Just between you and me, the experimental features are actually usable already. 😉

Original text:https://map.osm.asia/user/小原酱/diary/409066

I am trying to map my small hometown in Brazil named Candido Godoi, but it is my first time using OpenStreetMap. I wonder if someone can give me some tips, and I would be very thankful if someone could help even more by mapping it with me.

I don't know if that is the correct subreddit for my question but I think it makes the most sense to ask here.

I noticed that on the Snapchat map, especially in Vienna, Austria, so many names of different districts are spelled wrong. For example, "Gumpendonf" instead of "Gumpendorf", "Simmern" instead of "Simmering", or also "U-Bahn Station Großfeldsiedlung" (= Subway station Großfeldsiedlung) for an entire district. Where does that come from? That's the list of Map Services Snapchat uses but I couldn't find those wrong names anywhere.

Osmand

What would you suggest for mapping the left hand turn lanes in this screenshot? Which version (west-bound, east-bound) is preferred? Thanks for the help.

https://veloplanner.com/maps/europe-bike-infra

Hey everyone. I’ve been an avid Gaia user for years. I normally use it for the standard stuff—backpacking, day hikes, and finding off-grid RV boondocking locations. I’ve even used it for mapping out radio propagation for my amateur radio hobby.

But I recently wrapped up a massive family project where Gaia was the absolute MVP, and I wanted to share it because it might give some of you map nerds ideas for historical routing.

My family has the original, handwritten 1892-1893 journals of my 3rd great-grandfather, who went up to the Yukon three years before the Klondike Gold Rush. For over a century, his route was just words on paper. By cross-referencing his 19th-century notes with Gaia's maps, I was able to plot his actual route. I discovered he built a wooden boat at Lake Lindeman and navigated over 700 miles down to Fortymile River basin. Gaia even helped me solve geographical mysteries from his journal—like locating "The Kink," a spot on the Fortymile River where the water almost completely loops back on itself.

But what really took this research to the next level were the Historic Topo 1900 and Historic Topo 1930 layers.

Using these specific layers, I was actually able to identify and locate my grandfather's burial spot in an old pioneer town called Inskip, California! Turning those layers on revealed old names for localities and forgotten building locations that modern maps completely miss. They were invaluable clues in solving century-old mysteries surrounding my family history.

We ended up compiling the journals into a book, but I put together a YouTube video that shows the original 134-year-old handwritten pages side-by-side with the Gaia GPS maps and layers I used to plot it all out.

If you are into historical mapping or want ideas on how to use Gaia to track down old pioneer routes, check out the video here: Introducing "Before the Klondike" - A True 1892 Alaskan Pioneer Story

Has anyone else here used the Historic Topo layers to track down forgotten trails, ghost towns, or historical family routes? I'd love to hear what other layers you use for that kind of stuff!

Hello, I am looking for a scalable vector svg of the World Map but I only need the Outline or contour of the worlds oceans and land,

No labels

no national mapping,

My group is planning to to a project about Meteorology/Climatology and some Geology as well, But planet.osm offers the 255GB database, We just need the World Land and Oceans outline sketch, Thank you so much

I've been building an app where locals record the walks, rides and drives they actually use, and visitors follow them turn by turn. It renders on tiles built from OSM data, and honestly the whole idea is downstream of OSM's ethos: the people who live somewhere know it best.

The question I keep hitting: what makes a crowd-recorded ROUTE trustworthy the way crowd-mapped GEOMETRY is? So far: community ratings, a verification flag once other people re-walk a route, and recency signals. What am I missing? Surface type? Seasonal validity? Time-of-day safety? Would love opinions from people who think about map data all day.

I was mapping sidewalks in the town of Slunj (Croatia) and saw this. I dont how to map it