Written 2025-10-30… Published 2026-11-03

About three years ago, during my day-to-day mapping activities, I came across a golf course that had some obvious errors. I didn’t think much of it at the time. Just a fairway that was drawn right across the top of a green. But the more golf courses I looked at, the more frequently I encountered this error.

I soon learned about a golf course simulator video game that was built on OpenStreetMap data and was attracting a large influx of simulator enthusiasts who weren’t seasoned OSM mappers. Along with that came various tools to aid in converting OSM data into these simulators, as well as tutorial videos that made some very bad assumptions about how golf courses should be mapped. These factors set the stage for some very bad mapping practices to spread around the world.

My understanding is that attempts were made to correct these bad habits at the source, but the tutorial author wasn’t interested in revising or removing his video. Combine that with YouTube’s bad decision to hide down votes on videos, and you’re left with de facto training material that is widely disliked but that new golf course mappers have no way of knowing is a poor source of truth.

So this is where I come on the scene and try to make the map better.

I’m a big fan of the broken windows theory. I’ve seen it play out in my own town. A minimally maintained but abandoned pizza parlor near me stood for years waiting for a new occupant to lease it. You’d see prospective tenants touring it every once in a while, but no takers. Eventually, someone tagged the building with graffiti. It wasn’t cleaned up in a timely manner, and things spiraled downward from there: more graffiti, broken windows, stolen copper, garbage left behind by homeless people, and eventually, the building was razed.

I saw similarities with golf courses. This broken “style” of drawing a fairway, intersecting the green, crossing over it, and then intersecting the green again on the way out to the rest of the fairway was becoming commonplace. I fixed one, then another, and another. I thought about contacting the original mappers and educating them, but these were often edits made years ago, and the mappers were probably no longer active.

This is when I came up with my “Broken Greens Theory.” Any green that was “broken” could lead to more greens being “broken” when someone stumbled upon it and thought, “Oh, so that’s how you map a fairway and a green together.”

Any corrections would need to be made soon after the error was introduced, while the edits were still fresh, the mapper was possibly still active, and the damage was limited in scope. At the same time, existing errors would have to be fixed as well, or we’d never reach a point where people weren’t learning bad practices from the existing maps.

I’ve learned a lot over the last three years working on this project, from editing techniques in JOSM (even though I was already well-versed in its use) to spatial database queries. One of the neatest things I learned was about the Dimensionally Extended 9-Intersection Model and how it could be used to query for specific ways that fairways intersected with greens.

I figured out how to construct PostGIS SQL queries to identify all of these intersections and was shocked to find well over 20,000 of them in the United States. I put together tools to group these intersections and feed them, course by course, into JOSM to be manually edited and saved back out.

At the start of the year, I set a goal of fixing this one specific type of golf course error by the end of the year. As I progressed through the year, the number of remaining fixes dropped, and it looked like I was on track. Then I started noticing some intersections on nearby holes, close to ones I was already working on, that hadn’t been caught. Uh oh.

My query only caught intersections where the fairway line crossed into the green and then back out. It wasn’t catching cases where the fairway shared a node with the green, followed the green for one or more nodes, and then crossed into and back out of the green. I was disheartened to revise my query and discover that several thousand more pairs with this slightly different intersection pattern had been overlooked.

I doubled down on my efforts and increased my daily goal. A few months later, I discovered yet another type of mapping error. Some fairways shared every single point as they went around the outside of the green, where a green’s fringe would normally exist.

So I repeated my routine: fixing the query, being disheartened by the discovery of thousands more errors, and redoubling my efforts to get the job done by the end of the year.

Along with all of these edits, when my wrists could no longer take the repetitive strain for the day, I would work on developing more tools to download daily map diffs for the entire globe.

Things are different in the diff world, no pun intended. You can’t simply load diffs for the United States into the database and query them. But I wrote some code to process the XML stream and handle the unusual way that changes are grouped together. I developed tools that would examine changes to golf courses in the target area of the United States, load only those changes into my database along with nearby data, test the new edits for errors, and generate a “report” of edits that warranted further investigation by hand.

Since the start of the year, I’ve identified about 300 cases of people making “bad” edits that were significant enough that I felt reaching out and working with the mapper to correct their behavior would benefit the community.

The first thing I discovered is that changeset comments are almost useless. I’m guessing that over 90% of them are completely ignored. It’s unclear whether they were even read in the first place. I’d love to see someone put together a study on the effectiveness of changeset comments, especially when directed at newer or “drive-by” mappers.

I started requesting blocks for some of these repeat offenders from the Data Working Group and had some success getting their attention through that method. However, some mappers were combative and felt that OSM needed to bend to their will. They were challenging conversations, to say the least.

Over time, I’ve learned that messaging a mapper directly has a much better ROI, but still nowhere near 100% effective. I believe they see the unread message count and are more likely to click on it than to check for changeset comments in an email inbox that they probably use only for spam.

As the year went on, I started seeing fewer and fewer of these fairway/green intersections. Possible explanations include there being fewer courses left to map from scratch, or perhaps it’s the weather, as the season changes and people spend less time mapping. It will be interesting to see how the numbers change over the next year.

With these two approaches to tackling the problem (fixing existing issues and finding new ones), I’ve finally finished fixing every single fairway/green intersection in the United States.

I estimate that I’ve fixed over 30,000 fairways over the past few years. I consider that a big success, and I hope that ongoing maintenance will be quick and manageable.

I’ve been building Wandering Around, a free browser game in which you can walk around any town or city on Earth. The whole world comes from OpenStreetMap, so I’d like to share how it uses OSM data and ask this community for feedback.

Play it here: https://wanderingaround.games (works on phone and desktop, no account needed) Screenshots and a short video: [link naar je itch.io-pagina]

How the map is built

• Streets, buildings, water, parks and bridges come from OpenFreeMap vector tiles (zoom 14, OpenMapTiles schema). The game fetches the tiles around the player, decodes them in the browser, stitches buildings that are split across tile edges and turns everything back into OSM-style features with tags. The game logic works on those tags, so it is the same code whether the data comes from tiles or (as a fallback) from Overpass.
• 2D and 3D: the same data drives a 2D map and a 3D eye-level view. Building heights come from OSM where they are tagged.
• Transit: train routes and stations, city buses, ferries and signposts come from Overpass queries, so you can travel between real stops and stations.
• Country map: towns, airports and ferry ports within 100 km come from pre-built tiles made from Overture, OurAirports and Natural Earth.

What the game adds itself

Vector tiles leave out some details, such as single trees, benches, crossings, traffic lights and roof shapes. The game fills those in itself so streets don’t look empty. These are decoration, not data: they are never written back anywhere.

Wikidata postcards

Every feature with a wikidata tag (and, in the Netherlands, ref:rce for national monuments) becomes a landmark. When you visit one you get a postcard with:

• a photo from Wikimedia Commons (P18), with the photographer and licence shown,
• year built (P571), height (P2048) and floors (P1101),
• a summary from Wikipedia in your language.

In the 3D view the game uses the Wikidata height for the building and takes the facade colour from the photo. So a good wikidata tag on a building directly improves what players see.

What I’d love feedback on

• Does your own area look right? Missing buildings, odd water or bridges, or stops in strange places usually point to a tagging pattern I don’t handle yet.
• How do performance and rendering hold up in very dense city centres, compared with rural areas?
• Any ideas for using more OSM data in a game in a way that is fun and encourages people to improve the map.

Thanks to everyone who maps. Without your work this game would be an empty grey square.

Map data © OpenStreetMap contributors · tiles by OpenFreeMap · Wikidata · Wikipedia · Wikimedia Commons

قشلاق ساری قوئی میکائیل

Bande dessinée qui explique en partie la situation actuelle des chemins perdus plus ou moins facile à retrouver, voire parcourir. Ce voyage dans le passé de nos campagnes m’en a rappelé d’autres ; notamment les films Farrebique (1946), puis Biquefarre (1983) ; mais aussi une série d’émissions radiophoniques et télévisuelles, peut-être diffusées en 2009, sur l’essor agricole français, rétrospectivement.

https://www.editions-delcourt.fr/series/serie-champs-de-bataille

بندرعباس کوی فرهنگیان کوچه گل افشان بن بست اول ضلع شمال غربی ساختمان مجاهد.

https://yamatt.github.io/osm-user-home/

Er is vooral goed te zien wie waar ter wereld zoal mapt. Na een rondje medemappers bekijken bleek: we mappen tamelijk consequent in eigen land en overschrijden de landgrens zelden.

Edit: De OSM Home Predictor laat in het gunstigste geval zien in welke plaats je woont en zeker niet in welke straat en nog minder in welk huis. In OSM zit trouwens direct onder je account de functie “Mijn dashboard”, waarmee je >Andere gebruikers in de buurt< kunt zien. Die hebben veelal zélf hun exacte adres opgegeven en hebben soms ook nog hun eigen naam als accountnaam en in het beste geval ook nog een profielfoto …

While walking around, surveying, I’ve often theorised it would be possible to work out where I lived based on the centre of all the edits I’ve made.

So I made a tool to estimate it. And it’s pretty close.

It gets closer or further away depending on how much history you look at.

But you might find it informative.

https://yamatt.github.io/osm-user-home/

Edit:

It’s an interesting problem.

OSM needs and wants contributions. But by it’s very nature it can give away users data, without them even realising.

I don’t think there is even a technical fix for that.

But there does need to be a serious discussion with contributors about their data privacy.

Some might not care.

Some might be alarmed.

And alarmed is good.

We need to talk about how we balance users privacy and the power of OSM contributions.

Currently i am investigating if a comparison of the "nearest" call between a car and a foot profile reveals issues in osm.

Basically its the difference in intermodal routing. So in the first case you get sent to the nearest point on the car legal road network. In the second case you get sent on the walkable path network.

Of course its unfair to go from the car to the foot point as in real intermodal routing the car point would be at the modal swap/change intersection.

Nevertheless it may reveal issues in our current modelling of the data, and how we map things.

Just for an illustration - This is an address i found while testing. You can see that the nearest road network point is very "far" away from the foot point. Routing solves the labyrinth for us.

X marks the spot to the crossroads of America. Route 30 travels east to west and Route 41 north to south spanning the whole country. Schererville, Indiana

A fantastic guide. But my god, could it make the changeseys a bit more bulky instead of creating a new one for every single edit?

I feel like I’m spamming now…

I had a great time at SotM LATAM in Mexico City this past week. I got to hear so many talks on diverse subjects, I met friendly and interesting people, and there was a general acceptance that a random person from Canada would be there. Kudos to the organizing team and volunteers who put on a smooth, well run event.

I have never been to a State of the Map before despite thinking about going since way back in 2016 when I happened to already have a visa for Brazil. That certainly would’ve been harder with my level of Spanish understanding then. I will definitely be back.

Gracias a la comunidad y hasta la próxima. Espero encontrar oportunidades para colaborar.

22/10/2026-28/10/2026

Mapping

• Andy Mabbett has proposed a tagging scheme for the concrete arrows and illuminated beacon towers along the historic US Transcontinental Airway System. These physical navigation aids were built to guide early airmail pilots. Concrete arrows were enormous arrows painted or laid out on the ground, often on hilltops or open land, pointing pilots towards the next route segment. Beacon towers were tall structures equipped with powerful lights that helped pilots follow the route at night.

• LordGarySugar is proposing the tags flat_ride=track and water_ride=track so that, in the case of flat rides and water rides, the track can be distinguished from the ride area. Currently, attraction=log_flume is used for both, meaning that renderers cannot interpret the tag on paths. The tag attraction:part=* is intended to identify components such as stations and platforms, whilst a site=attraction relation is intended to link all parts of an attraction. The discussion is taking place on the OSM Community forum.

Community

• rtnF has analysed the diversity of addr:neighbourhood values in Indonesia.

• simaransharma has been adding and fixing temple map data in Surat, Gujarat, and is currently looking for other mappers in Gujarat who are also interested in mapping temples.

Local chapter news

• OSM US published another instalment of their Mapper Highlight series, which highlights mappers, projects, and OSM communities. This October, they interviewed William Edmisten (aka wcedmisten), a Virginia mapper who recently mapped every hospital network in the United States and kept invested followers updated on the OSM US Slack.

Events

• As part of its Gender Programme, the Unique Mappers Network hosted a virtual breast cancer awareness and geospatial education event on Friday 23 October. The theme was ‘Every Story Is Unique, Every Journey Matters’. It covered breast cancer awareness, prevention, early detection, and the importance of seeking medical advice. It also looked at the role of open mapping in community health awareness.

• The organisers of the fifth State of the Map Nigeria have postponed their conference from 10 to 13 November to 17 to 20 November 2026, as the University of Uyo has scheduled its graduation ceremony for 9 to 14 November. The venue remains the Town Campus of the University of Uyo in Akwa Ibom State, and the theme remains ‘Open Geospatial Innovation for Climate Action and Community Resilience’. The programme includes workshops, specialist talks on GeoAI, OpenStreetMap, citizen science, and climate action, as well as networking opportunities. Further information can be found on the conference website.

• The Asociación OpenStreetMap España is hosting ‘SotMes 2026’ at the TomTom offices in Madrid on 6 and 7 November. This free gathering of the Spanish OSM community combines talks with an ‘unconference’. Anyone interested can register .

Maps

• The Cunning Conquests Atlas is a free resource containing interactive maps of an ever-growing library of journeys. It was built with coastline data from OpenStreetMap and was released on 17 October. You can also watch the videos on YouTube with detailed legends.

• Proton built a web map where you can look up any ZIP code in the US and find how many surveillance devices (flock cameras) are near your home. The device locations on this Flock camera map come from independent research by cybersecurity researcher Joshua Michael.

• vetsurgeo launched The Church Atlas, a free map of more than 3,000 churches in 18 languages, using OpenStreetMap data, with Wikidata and Wikipedia providing addresses, summaries, and photos. He also shared the lessons learned about church tagging in a diary entry.

• rpollock has published Walkably, a map showing pedestrian-friendliness across 31 European countries, based on OpenStreetMap data. Each hexagonal cell that intersects a road is assigned a score for the walkability of everyday destinations and for road quality (traffic, noise, shade in summer, main roads, gradient). An OSM blog post documented the checks made against census data. The full methodology is explained on the project page.

OSM in action

• ^[1] Jiri Podhorecky worked on the graphic design and cartographic preparation of a printed tourist map of Prague, built directly on up-to-date OpenStreetMap data.

• copilot.travel developed a dynamic map that shows each European capital claiming territory on the basis of the nationality of the first car to reach surrounding places, using typical road speeds and including ferries.

Software

• Chris Debian has developed PillarPoint, an open-source Android app for people who find, visit, and record British trigonometrical points (trigs) and Ordnance Survey benchmarks. For each trig the app checks whether OSM already has a matching survey point and flags any OSM node that is some distance from the recorded station location.

• GeoDesk released GOL Tool 2.5, adding support for incremental updates to keep local copies of OpenStreetMap data up to date.

• Martin Faust has built Rücksitzhelden, a free app for families on long car journeys that shows ► attractions and family-friendly restaurants along the route using OpenStreetMap data.

• Axel Piepgras has developed ► rueckenwind, an iPhone bicycle navigation app powered by OpenStreetMap data.

• The well-known ‘Strava Slide’ algorithm, which allows drawn routes to be automatically adapted to and optimised for the Strava heatmap, is now available both as a browser extension ‘strava-heatmap-extension’ for Chrome and Firefox, or a JOSM plugin ‘josm-strava-tracer’. This tool allows the geometry of routes to be captured much more quickly and accurately based on aggregated GNSS tracks.

• Ukrainian developers Vladyslav and Daryna Shinkarenko have developed Орієнтир, an iOS navigation app that works without GNSS. Instead, the app uses smartphone sensors to estimate the car’s speed and turns. It also offers offline maps of the whole of Ukraine, powered by OpenStreetMap data.

• Victor explained how OsmAnd’s new search engine, built from scratch and recently released in version 5.5, works.

Programming

• anthaas described how he automated marking small tasks, related to the Ebola campaign in the Democratic Republic of the Congo, as done in the HOT Tasking Manager using JOSM and the TM API.

Releases

• HeiGIT has introduced a new openrouteservice web client, which replaces the two previous route planners. This article explains the new features, current limitations, and what users need to know before the old clients and deprecated API URL are shut down on 16 November.

Did you know that …

• … the Magic Earth navigation app is based on OpenStreetMap data? It offers turn-by-turn navigation, offline maps, and speed camera alerts for iPhone, iPad, and Android; navigation is free, whilst additional features are available via a freemium model. The source code is not open. mobilsicher.de tested the Magic Earth navigation app back in 2019 and gave ► it a positive review (we reported earlier).

Other “geo” things

• Geografías acuáticas: espacios de conectividad y sociabilidad, edited by Guadalupe Pinzón Ríos and Flor Trejo Rivera and published by the Universidad Nacional Autónoma de México, demonstrates how aquatic environments, rather than being peripheral or serving as spaces that separate societies, should be viewed as settings for diverse forms of connectivity, and within which forms of social interaction were also established that are, in fact, of great significance in a region such as this, where bodies of water deserve greater attention.

• Sven-Erik Volberg posted a map of the approximate historical boundaries of the larger European states (those with an area over 100,000 square kilometres). The map covers around 1500 years from 500 CE.

• The Direção-Geral do Território has announced ► the ‘XVII Jornadas Ibéricas de Infraestruturas de Dados Espaciais’ (Iberian Conference on Spatial Data Infrastructure), to be held from 11 to 13 November in Porto, Portugal. Those interested can register ► now.

Upcoming Events

Country	Where	Venue	What	When
🇲🇽	Ciudad de México	Antiguo Colegio de San Ildefonso	State of the Map Latam 2026	2026-10-27 - 2026-10-29
🇨🇭	Rapperswil-Jona	OST RJ Gebäude 6, Rapperswil	20. Mapathon & Mapping Party Rapperswil 2026	2026-10-30
🇮🇹	Pesaro	Biblioteca-Archivio “Vittorio Bobbato”	Linux Day Pesaro	2026-10-31
🇮🇳	नई दिल्ली	Jitsi Meet (online)	OSM India - Monthly Online Mapathon	2026-11-01
🇩🇪	Hannover	Kuriosum	Stammtisch	2026-11-02
🇭🇺	Budapest	United Platforms, Fény utca 16.	OSM térképest – 2026 november	2026-11-03
			Missing Maps London Mapathon Beginner Friendly (with Training) (Online) [eng]	2026-11-03
🇨🇭	Bern	Provisorium46	Berner OpenStreetMap-Znacht	2026-11-03
🇩🇪	Stuttgart	Forum 3 Café	Stuttgarter OpenStreetMap-Treffen	2026-11-04
🇫🇷		Bar Le Schmilblik	Rencontre mensuelle des contributeurs Paris sud	2026-11-05
🇪🇸	Madrid	TomTom, Edificio Aqua, Calle Agustín de Foxá 4	State of the Map España 2026 (SotMes 2026)	2026-11-06 - 2026-11-07
🇫🇷	Angers	L’Arrière Train, 3 rue de Frémur, Angers	Angers Rencontre mensuelle OpenStreetMap	2026-11-06
🇦🇹	Salzburg	HTL Itzling	Maker Days Salzburg	2026-11-07
🇮🇹		Angera	Mapathon @ Angera	2026-11-07
🇩🇰	København	Cafe Bevar’s	OSMmapperCPH	2026-11-08
			CartONG : Mapathons en ligne 2026-2027	2026-11-09
🇹🇼	臺北市	MozSpace Taipei	OpenStreetMap x Wikidata Taipei #94	2026-11-09
🇺🇸	Salt Lake City	Woodbine Food Hall	OSM Utah Monthly Map Night	2026-11-10
🇩🇪	Hamburg	Voraussichtlich: “Variable”, Karolinenstraße 23	Hamburger Mappertreffen	2026-11-10
🇺🇸	San Jose	Online	South Bay Map Night	2026-11-10
🇬🇧	City of Westminster	The Volunteer pub	London pub meet-up	2026-11-10
🇩🇪		temporärhaus	OSM-Stammtisch Ulm/Neu-Ulm	2026-11-10
			iD Community Chat	2026-11-11
🇩🇪	München	Echardinger Einkehr	Münchner OSM-Treffen	2026-11-11
			OSM US Mappy Hour: Mapping Route 66 Past & Present	2026-11-11
🇮🇳	Kottayam	Kottayam, Kerala	State of the Map Kerala (SoTM Kerala)	2026-11-14 - 2026-11-15
🇮🇪	Dublin	4 Inns Court, Winetavern Street, Dublin, D08 XY00	OpenStreetMap Ireland AGM - 2026	2026-11-14
🇮🇳	New Delhi	South Delhi	OSM Delhi Mapping Party No.34 (South Zone)	2026-11-15

This weeklyOSM was produced by MatthiasMatthias, PierZen, Raquel Dezidério Souto, Andrew Davidson, barefootstache, derFred, vicksun.
We welcome link suggestions for the next issue via this form and look forward to your contributions.

Today i made my first steps using Claude (sonnet-5) to add coverage, unit and mutation testing to addressextract. The testing needed synthetic input data which claude proudly produced.

I find it really fascinating how it derived the corner cases from the code and made the transformation into an osm.xml which contains all those cornercases.

The first shows admin and postal code boundaries, buildings and addresses in all sorts of relations. Some positions are to evade caching tricks in the Quad Tree. Some really present errors addressextract shall find like address A on node within building outline with address B. All kinds of missing tags, wrong tags, overlapping tags.

Some are to trick the position inside the bounding box, but outside of the geometry.

Fascinating times.

Surprised myself and participated for rrrreal! (well, ok, missed the first day)

Very nice event, liked it a lot.

Report 🫡

https://m-d.me/notes/osm-dailychallenge-2026/

31DayOSMChallenge #Maptober #Maptober2026

Bar Ehiala’S Deck, parte das antenas

On 29 October I presented OSM for Cities at State of the Map Latam in Ciudad de México. The project shows how well OpenStreetMap covers a kind of data in a given city, and how recently anyone touched it.

The slides are online, in Spanish.

Photo by Jordan Jasuta Fischer

Most of the talk was a live demo with Mexico City bus stops, coloured by when each one was last edited. When I made the slides, 317 stops had been edited in the past week, almost all along a few routes in the west of the city. Someone was mapping them right then. Most of the rest had not been touched in over 90 days.

That is what the platform is for, following a dataset over time instead of looking at it once. Save a dataset and it is refreshed from OSM every day, and a notification arrive by email if it changes. A city team can see when its bus stops get mapped, and a mapper can see whether anyone else is keeping their area up to date.

Vector tiles are coming soon

Today a dataset loads into the page as one GeoJSON file. That works for bus stops, but not for the buildings or streets of a large city, which is why those are not on the platform yet.

Buildings matter most for disaster response and health planning. They show where people live, which is what a house-to-house campaign during an epidemic needs.

The fix is to bake each dataset into vector tiles (PMTiles), so the browser only loads what is on screen. It is ready and in testing, and should be released soon.

Thanks, State of the Map Latam!

It was great to be in Mexico City and see old and new friends from the OpenStreetMap community. The conference was very well organized, with an amazing diversity of talks. I’m looking forward to the next one, which will be both Latin American and global, State of the Map 2027, in Bogotá, Colombia.

Disclaimer: Written by me with AI assistance.

Registered in 2014, but I only started using OpenStreetMap actively last year.

After watching some Aboriginal movies of Australia, I switched from the Himalayas to Down Under, and then with chasing tracks in the outback of Australia—uncovering hidden reservoirs, basins, homesteads, cattle stations, farms, and surprisingly, some generous peaks. From there, I switched over to China, where the clever use of land through greenhouse horticulture stands out as one of the best examples of resourcefulness.

Flipping to Ethiopia brings a blend back to Nature: homes and huts constructed from natural elements offer a grounding perspective, even as the region slowly turns toward the so-called “blinded modernization.” Crossing over to South America, dense forest covers reveal hidden streams and alpine lakes tucked high in the mountain ranges, though the sheer scale of deforestation is disheartening to see.

Jumping to Japan and the Korean peninsula, the structured, disciplined approach to farming is among the finest in the world, matched by remarkable urban and human development.

Further north, the vast expanses of Alaska and Siberia ground you completely—reminding us of our fragile place within Nature and how quickly our so-called "development" will simply be reclaimed by time.

OSM has helped keep me calm, though it is still easy to get agitated. Now, I’ve even started mapping via my mobile browser as well, which has been a lifesaver while traveling on public transport. In a world full of towering billboards and aggressive roadside slogans, mapping on the move gives me the perfect excuse to ignore the visual pollution.

Of course, whenever I'm passing through true valleys and breathtaking landscapes, the phone goes straight into my backpack so I can take it all in.

Title: OpenHVRA: a free hazard, vulnerability and risk assessment tool built on OpenStreetMap

Hello mappers!

For years I have watched the same thing happen. A flood or any hazard hits a place, and the first questions are always the same: how many people live near the river, which schools and health posts are in the way, and what will it cost? Very often the best data to answer those questions is already sitting in OpenStreetMap, mapped by volunteers. But turning those buildings and waterways into a risk picture usually needs desktop GIS, paid software, or a specialist.

So I built a tool based on my professional experience, OpenHVRA (Open Hazard, Vulnerability and Risk Assessment) with help of my friend Claude, a free web map that does that analysis straight in the browser, using only open data.

Try it: gomalhunzai.github.io/openhvra Code (MIT License): github.com/gomalhunzai/openhvra

No login, no install.

How it works

You draw an area on the map (or upload a boundary as Shapefile, GeoJSON, KML, GeoPackage and a few other formats). OpenHVRA pulls buildings, roads, waterways and facilities from OSM through the Overpass API, adds open elevation tiles, and walks you through eight steps:

1. Area and data: download OSM layers, with a “light” mode for slow connections.
2. Population model: estimates residents per building from footprint and storeys, which you can calibrate with a census total.
3. Cursor probe: hover anywhere and see live counts of people, buildings and facilities within a radius.
4. Exposure by distance: what lies within X metres of rivers, streams or roads. It also checks height above the channel, so homes high on a hillside in a mountain valley are not wrongly counted as flood-exposed.
5. Flood risk and risk finance: flood depth per building for different return periods, damage using JRC depth-damage curves, average annual loss, and how losses could be split between reserves, credit and insurance.
6. Social vulnerability: a 0 to 1 index per home based on access to health care, emergency services and roads, housing fragility and crowding, plus optional census data and World Bank figures for vulnerable groups.
7. Multi-hazard risk: scores every building for river flood, flash flood, landslide, earthquake (USGS catalogue), coastal flood, glacial lake outburst flood (GLOF) and snow avalanche, then combines hazard and vulnerability into one risk score and a likelihood × impact risk matrix.
8. Report and downloads: one click gives a ZIP with CSVs, GeoJSON layers, 300 DPI map layouts and charts, all stamped with the tool version so results can be traced and cited.

There is also a 3D view that raises buildings to their mapped height over the terrain, which turned out to be a great way to explain risk to people who do not read maps every day.

Where you come in: better mapping, better risk estimates

OpenHVRA is only as good as the map underneath it. Some tags make a real difference:

• building:levels drives the population estimate and the 3D view. Even a rough count of storeys helps a lot.
• Building type (building=house, hut, apartments, commercial, etc.) feeds both the population split and the housing fragility score. Plain building=yes gives the tool much less to work with.
• Waterways drawn in the direction of flow are used to trace GLOF paths. A stream drawn backwards breaks the trace.
• Health facilities, schools, shelters and emergency services (amenity, healthcare, emergency) are what the critical facility analysis counts. If the clinic is not on the map, it is not in the report.
• Bridges and road classification matter for access and exposure.

If you run mapathons for disaster preparedness, this is a nice way to show volunteers what their mapping is used for: map an area, then open it in OpenHVRA and see the risk picture appear.

Status and feedback

OpenHVRA is in beta (v0.10.1). The methods are documented in the README and CHANGELOG, and version 1.0 will come once they are validated against real events. It is a screening tool to help prioritise, not a replacement for a detailed engineering study.

I would really like to hear from you:

• Try it on an area you know well and tell me if the numbers make sense.
• Open an issue on GitHub for bugs or ideas.
• If you use it in a project, mapathon or paper, please let me know. The “Cite this repository” button on GitHub gives you a citation.

Thanks to everyone who keeps mapping the places that need it most. This tool exists because of you.

Happy mapping!

Za poslední půlrok proběhlo výrazné oživení několika menších měst v Jižních Čechách. Namátkou jmenuji Jindřichův Hradec, Prachatice, Vimperk, Třeboň… tedy města, kde místní OSM mapovači asi jen tak nežijí.

Nemluvím jen o prostém doplnění zákresu podle letecké mapy, která je každým rokem detailnější, ale i zpřesnění různých cest v okolí, objektů a subjektů, typicky firem a obchodů v městě. To je výsledkem práce více lidí, nevím přesně, ale věřím že mnoha. Za mne jsem dostával i tipy přímo od lidí z místa, například z místního obecního, nebo městského úřadu.

A nutno říct, že oni mají občas velmi konkrétní informace, které se u jiných veřejných zdrojů nedají vidět. Jen je trochu nelehké to info posbírat. Chvilku mi trvá, než si na každé mapované místo zvyknu, stane se mi víc známým. Vidím v něm něco prostorově unikátního. Z fotografií se dozvím, že město má nějakou tvář, nějaký profil… tvar vycházející nejen z historie, ale i z krajinných dispozic. Když vidím že náměstí je celé z kopce, hned to na mne působí jinak.

Ještě je hodně jiných měst a obcí, zajímavých oblastí, kde jsou úpravy třeba 10 a více let staré. Současnost je už jiná. Nejen v popisu míst, ale i v rozvoji periferií, v přirozeném městském prostředí kde jsou kulturní i komerční body zájmu.

Do pozornosti přijdou města jako např. Blatná, Milevsko, Domažlice… Zajímavé k mapování pro mne byly i některé oblasti Šumavy, Novohradských hor, dalších mikroregionů. A nemusí být jen turisticky atraktivní.

Přijde mi to jako sbližování s místy, kde jsem ještě nebyl. Až se tam někdy vydám, už budu vědět líp, kde právě jsem.

Budu mít totiž s sebou mapu!

Gemeinsam hacken, mappen und diskutieren

Am 24. und 25. Oktober 2026 hat sich die OpenStreetMap Community wieder zum Hackweekend in Berlin getroffen. Mit 25 Teilnehmenden an beiden Tagen war es das bisher größte Hackweekend in Berlin. Ein Hackweekend ist kein reiner Programmier Marathon. Es ist ein offenes Treffen, bei dem neue und erfahrene Leute zusammenkommen, sich gegenseitig helfen und am Ende konkrete Verbesserungen mitnehmen.

Wir danken Wikimedia Deutschland herzlich für die erneute Gastfreundschaft: für die Räume, die gute Arbeitsatmosphäre und die tolle Verpflegung.

Die Themen waren auch diesmal bunt gemischt. Es wurden Karten gestickt, LiDAR Scans zusammengepuzzelt, Quasi-Luftbilder aus 360° Straßenfotos erzeugt und Druckkarten um Seezeichen erweitert. Dazu kamen Verbesserungen an bekannten Diensten wie dem BBBike Extract Service, der Straßenraumkarte und der Obstbaumkarte. Ein Thema, das sich durch viele Gespräche zog, war die Frage, welche Rolle KI und Agentic Coding im OSM Umfeld spielen und spielen sollten.

Wenn du neu dabei bist, reicht oft schon ein Laptop und Neugier. Du kannst aber auch ganz ohne Technik mitmachen, zum Beispiel beim Mapping, Testen, Dokumentieren oder einfach im Austausch. Vor Ort gibt es kein festes Programm, stattdessen entstehen spontan Aufgaben und Mini Sessions, und jemand findet sich fast immer, um dich beim Einstieg zu unterstützen.

Weitere Informationen zum Event finden sich im Wiki. Wenn du die nächsten Termine nicht verpassen willst, beobachte osmcal.org.

Im Folgenden sind einige der Themen gesammelt, an denen gearbeitet wurde.

Christopher und Lars: Konferenz-Dashboards und Hackweekends 2027

Die Dashboards für die kommende FOSSGIS-Konferenz in Heidelberg haben sich Christopher und Lars gemeinsam nochmal angesehen und letzte Features hinzugefügt. Es wird eine Abfahrtstafel geben, die alle Fahrplanabweichungen gegenüber dem Programmheft anzeigt, und eine Anzeige, welche Workshops und Exkursionen noch freie Plätze haben. Jetzt warten wir auf die Veröffentlichung des Programms im Dezember 2026.

Auch 2027 soll es wieder zwei Hackweekends geben. Christopher und Lars haben zwei mögliche Termine gefunden, die müssen jetzt aber noch mit anderen Stellen abgeklärt werden. Ziel ist es, Anfang 2027 die Termine zu veröffentlichen.

Lars: uMap Seite, EqualStreetNames und lokale KI

uMap Seite für openstreetmap.de

Ich habe an einer uMap Seite für openstreetmap.de gearbeitet. Hier besteht noch Review-Bedarf und es muss geklärt werden, wer die hübschen Titelbilder erzeugt.

EqualStreetNames Berlin

Vor einiger Zeit gab es für Berlin auch ein EqualStreetNames-Projekt. Nach einem Serverumzug und aus weiteren Gründen ist das Projekt leider offline. Ich habe an dem Setup weiter gearbeitet und einige Verbesserungen eingebaut. Es entstand ein neuer Hell-/Dunkel-Stil, der einen besseren Kontrast und damit bessere Lesbarkeit ermöglicht. Gängige Standards für Farbfehlsichtigkeit wurden auch so weit wie möglich berücksichtigt. Ein großer Punkt war die Performance, hier wurde eine deutliche Verbesserung sowohl im Ladeverhalten als auch bei der interaktiven Nutzung der Karte erreicht.

Leider war das Hackweekend dann doch zu kurz, um das Ergebnis online zu stellen. Die Änderungen betrafen zum Schluss nicht nur den Code der Berliner Instanz, sondern auch den Upstream-Code des EqualStreetNames-Projekts. Hier ist im Moment noch unklar, inwieweit der Code separiert werden kann. Außerdem fehlt auch noch der Ansible-Code für das Deployment auf einem FOSSGIS-Server.

Lokale KI

Bereits im Vorfeld des Hackweekends habe ich mich mit lokaler KI beschäftigt. Mich hat interessiert, wie so ein Setup funktioniert und was für Komponenten man benötigt. Kann ich es in meine Tools (IDE, QGIS) einbinden, und wie sieht die Performance aus? Auf dem Hackweekend habe ich mein lokales Modell tatsächlich benutzt, z. B. für die Arbeit an EqualStreetNames. Außerdem habe ich mir mehrere Chat-Oberflächen angeschaut. Bisher nutze ich GlyphStream, aber es gibt auch noch Open WebUI und LibreChat. Mein Fazit: Ich werde noch weitere Tests machen und viel ausprobieren. Wenn alles nach Plan läuft, könnte es einen Vortrag auf der nächsten FOSSGIS-Konferenz in Heidelberg geben.

Hartmut: Druckbare OSM Karten mit SeaMap Overlay

Druckbare OSM Karten mit print.get-map.org:

• CartoOSM Stil Version Upgrade
• SeaMap Overlay Implementierung, Work in Progress
• GitHub: github.com/hholzgra/mapnik-seamap-overlay

Aktueller Status (Klick auf das Bild öffnet die volle Auflösung, 19866×14043 Pixel)

Tordanik: 3D-Rendering und Prototype Fund 2027

Tordanik, der Autor von OSM2World, hat sich mit 3D-Rendering beschäftigt, unter anderem mit dem 3D-Rendering von Brücken mit bridge:structure, bridge:support etc. Außerdem ging es um die Planung für den Prototype Fund 2027 (3D, Straßenflächen, Stadtmodelle o. ä.).

Transitous: ÖV Daten aus OSM und Wikidata anreichern

Grundfrage: Wie kann man Transitous ÖV Daten mit Linien, Haltestellen, Betreibern etc. aus OSM und Wikidata anreichern?

Wikidata und/oder OSM

• Nicht zu viel in Wikidata, also eine separate Wikibase Instanz OSMWikibase?
• OSMWB kann in Wikidata freigeschaltet werden für föderiertes SPARQL Querying
• Wikidata Lookups erstmal auf Nicht-Bus beschränken, um zu verhindern, dass zu viele neue Entitäten entstehen
• OSM für Linien priorisieren mit Tagging Alternative (keine Ways)?

Wie an Wikidata Daten rankommen?

• Wikimedia Enterprise Snapshots für inkrementelle Dumps? Trial/Pay/Exceptions?
• XML vs. RDF vs. Snapshots (nicht kompatibel, also mit dem anfangen, was man wirklich verwenden will)
• Es gibt keine freie Möglichkeit, inkrementelle Dumps zu bekommen
• wdumps: filtern nach Properties etc.
• Wikidata Dump (oder gefilterten Dump) direkt in MOTIS parsen?
• Wikidata Dump nach “GTFS” konvertieren, für einfachen Import/Merging in MOTIS (Wikidata/Wikibase ist vermutlich mit den Datenmengen queryable, also ist kein direkter Dump Import nötig; GTFS ist ein sinnvolles Zwischenformat, auch von anderen konsumierbar)
• Erster Schritt: primär auf OSM matchen, dann mit Wikidata IDs aus OSM Daten aus Wikidata anziehen
• Agency: Wikidata IDs in OSM, Lookup von speziellen GTFS anhand von IDs
• Linie ebenso?

Geo Projektidee

OSM wayless route relations shape generator (osm2gtfs -> MOTIS?)

Die ausführlichen englischen Notizen gibt es im Transitous Wiki. Einen Bericht über das Wochenende hat außerdem Volker Krause in seinem Blog veröffentlicht.

Austausch zu Agentic Coding im OSM Umfeld

• LLM Benutzung in Foren (lieber einfach den Prompt schicken)
• OSM Ressourcen überlastet (Overpass)
• Projekte, die Maintainer selbst nur mit KI Hilfe verstehen. Total demotivierend
• AI Vandalismus (what to do?)

Marcus: Brauchen wir noch eigene Anwendungen?

Meine Frage für das OSM Hacking Weekend war: Welche Bedeutung hat KI für das Programmieren rund um OpenStreetMap?

Zunächst habe ich dazu einige Artikel in der c’t gelesen. Anschließend wollte ich selbst ausprobieren, wie gut KI beim Programmieren helfen kann.

Als Erstes habe ich meine Geldautomaten-Suche mithilfe von KI um einen Vektorlayer erweitert, der zusätzliche Daten zu Geldautomaten von der Obstbaumkarte einbindet. Die Erweiterung war innerhalb einer halben Stunde fertig.

Dann habe ich die KI gefragt, wo sich die nächsten Geldautomaten genossenschaftlicher Banken befinden. Sie hat sie sofort gefunden – und damit den Sinn meiner eigenen Geldautomaten-Suche ein Stück weit infrage gestellt.

Ähnlich ging es mir mit meinem nächsten Projekt: Ich möchte eine Anwendung entwickeln, die einen Wanderweg aus einer GPX-Datei in Tagesetappen zerlegt, deren Endpunkte an Haltestellen des öffentlichen Nahverkehrs liegen. Auch diese Aufgabe habe ich zunächst der KI gestellt. Das hat funktioniert – und damit stand auch der Sinn dieses Projekts infrage.

Eine Frage blieb offen: Was verbraucht eigentlich mehr Energie und verursacht mehr CO₂ – für jede Anfrage eine KI zu bemühen oder spezielle Such- und Planungsanwendungen zu entwickeln und zu betreiben? Eine Antwort könnte sein, dass eine selbst programmierte Anwendung weniger CO₂ verbraucht, wenn sie häufiger benutzt wird. Wird sie aber nur ein paar Mal benutzt, könnte die Entwicklungszeit gespart und stattdessen einmal eine KI genutzt werden.

Trotzdem habe ich mit meinem Wanderplanungsprojekt begonnen, natürlich mit Unterstützung der KI. Vielleicht finde ich ja ein Alleinstellungsmerkmal: etwas, das andere Planungsanwendungen nicht bieten und etwas, das eine KI allein nicht so gut kann.

Mein vorläufiges Fazit: KI macht das Programmieren erstaunlich einfach. Gleichzeitig stellt sie die Frage, welche Anwendungen wir überhaupt noch selbst entwickeln sollten.

Und: auch bei meinem Text habe ich mich von einer KI beim Schreiben unterstützen lassen.

Tobias (remote): Find Deleted Data, OSMCha2 und Quasi-Luftbilder

OSM Find Deleted Data auf API v2

Die ohsome API wird bald abgeschaltet, das Tool läuft jetzt auf der API v2:

• Demo

OSMCha2 weiter poliert

Das Projekt hat zwei Ziele: Ein neues UI explorieren und vor allem ein sehr gutes mobiles UI bauen. Außerdem soll das Kommentieren, Bewerten und Diskutieren verbessert werden. Man kann zum Beispiel Kommentare auf einzelne key=value Zeilen machen oder Kommentare mit einem Pin anreichern.

• Beispiel

Straßenfotos zu Quasi-Luftbild Pipeline

Für dieses Projekt hatte ich schon lange viele LLM Sessions und konnte jetzt erste Erfolge erzielen. Auf der HOT OpenAerialMap sieht man eine Quasi-Luftbild Ansicht, die aus 360° Straßenfotos (Fahrrad und Helm mit 360° Kamera) entstanden ist. Das Repo muss ich noch aufräumen, bevor ich es Open Source schalte.

• Zweiter Testlauf (gehend mit Selfiestick)

Oliver, Pauli und Till: Geodaten sticken

Ziel war es, den Prozess zu vereinfachen und zu automatisieren, mit dem eine Karte im SVG Format erstellt und anschließend in Inkscape mit dem Ink/Stitch Plugin in eine Datei für die Stickmaschine umgewandelt wird.

Entstanden ist ein Prototyp: osm.tillb.de/stitching (github.com/Tillbtn/osm2stitch)

• Konfigurator:
  • Ausschnitt, Format und Maßstab wählen
  • Stil, Farben und Stickkonfiguration anpassen
  • Downloadformate für verschiedene Stickmaschinen und als SVG zur möglichen Nachbearbeitung
• Umsetzung:
  • OSM Daten für das gewählte Gebiet per Postpass laden
  • Straßen verbinden, Gebäudeblöcke zu einfacheren Geometrien zusammenfassen
  • Pfadberechnung für die Stickreihenfolge
  • Erstellung der Stickdatei mit der Ink/Stitch CLI und pyembroidery

Nächste Schritte: Einen Testausschnitt sticken und mit den Parametern experimentieren.

Oliver: Routing in der Obstbaumkarte

In die Obstbaumkarte wurde ein Routing integriert. Weitere spezielle Routingprofile folgen.

Mlvln: ÖPNV Karte in QGIS

Experimente in QGIS für eine OSM Public Transport Karte:

Alex: Straßenraumkarte

In diesem Jahr habe ich die Prozessierung der Straßenraumkarte auf einen “modernen” Stand erneuert und viele Verbesserungen im Rendering umgesetzt. Eine Testversion für den Berliner Innenstadtring ist bereits online, die finale Veröffentlichung samt Blogartikel folgt demnächst.

Auf dem Hackweekend habe ich ein paar Fixes und Verbesserungen umgesetzt, da ich von anderen Teilnehmenden einiges Feedback bekommen habe. Insbesondere habe ich damit begonnen, das Rendering von Straßen und Wegen auf ein neues, konsequent flächenbasiertes System umzustellen. Das vereinfacht die Darstellung von Oberflächenattributen und reduziert Artefakte, zum Beispiel an den Enden und Übergängen von Wegen. Außerdem habe ich eine Überarbeitung des Stylings für Straßen und Wege angestoßen, um Wegeart (Straßen, Zufahrten, Wege) und Oberflächen (einige Varianten von befestigten und unbefestigten Oberflächen) besser unterscheiden zu können. Coming soon…

Nebenbei wie immer über verschiedene OSM Themen von Tagging Fragen bis KI Entwicklung gequatscht.

cyton: LiDAR Scans puzzlen

Unvollständiges Puzzle aus LiDAR Scans, global ausgerichtet:

• Scaniverse Export: glb, via LocalSend
• Jeweils zwei Dateien in CloudCompare aneinander schieben (Y-Achse beim Drehen beibehalten), die 4×4 Matrix der Operation kopieren und zusammen mit den Dateinamen notieren
• Ein Python Skript liest die relativen Operationen zwischen den Dateipaaren ein, speist sie in ein mit dem open3d Paket kompatibles Modell ein, lässt eine genauere Ausrichtung berechnen und speichert alle in ein globales Koordinatensystem verschobenen Modelle einzeln als obj

Alle Modelle gleichzeitig in CloudCompare anzuzeigen, ist für meinen alten Laptop schon sehr grenzwertig machbar.

Wolfram: BBBike Extract Service und Mapillary Takeout

BBBike Extract Service

Mit dem BBBike Extract Service lassen sich OpenStreetMap Daten für beliebige, auf einer Karte ausgewählte Gebiete herunterladen. Die Daten stehen in mehr als 20 Formaten zur Verfügung, unter anderem für Garmin Geräte, Smartphone Apps und GIS Software. Während des Hackweekends habe ich an einem neuen responsiven Design gearbeitet, das die Nutzung des Dienstes auf Smartphones und Tablets erleichtert. Außerdem habe ich Spanisch, Arabisch und Chinesisch als weitere Sprachen hinzugefügt. Damit ist der Dienst nun in sieben Sprachen verfügbar.

Der BBBike Extract Service auf dem Smartphone mit chinesischer Benutzeroberfläche

Mapillary Takeout

Mit dem Tool mapillary_takeout kann man die Fotos, die man zu Mapillary hochgeladen hat, als Backup herunterladen.

Leider funktioniert das Tool seit der Umstellung der Mapillary API von v3 auf v4 (2021) nicht mehr. Ich habe das Python Skript an die neue API angepasst und damit mehr als 10.000 Fotos mit voller DSL Bandbreite (30 MByte/s) heruntergeladen.

Die Fotos kommen in Originalgröße, aber verpixelt. GPS Position, Aufnahmezeit, Blickrichtung und Kamera schreibt das Skript wieder als EXIF in die Dateien. Das neue Skript wird in den nächsten Tagen veröffentlicht.

Panoramax Instanz für Berlin und Brandenburg

Wir haben über eine Panoramax Instanz für Berlin und Brandenburg diskutiert. Panoramax ist eine freie Alternative zu Mapillary und Google Street View.

Dabei ging es um rechtliche Risiken, die benötigte Hardware und darum, dass jemand die Initiative ergreift und es einfach mal macht. Leider hat aktuell niemand Zeit. Wenn du Interesse hast, melde dich einfach auf der Berliner OSM Mailingliste.

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

This mapping was a while ago. This is also a diary entry repost, I figured out how to display GIF-files. I was using imgur before this, where all GIFs you upload are converted to mp4 automatically so I can’t display it in the diary. Imgur is also full of ads. I assume most people don’t use adblockers, even with adblockers the UI distracts from your file. I’ll go back through my imgur links on OSM and reddit and link them instead to images on my little github page.

OSM LATAM 2026 México 🇲🇽 — Day 3: Beyond the Map!

And just like that, we reached the final day of OSM LATAM 2026 México! 🚀

What an incredible journey these three days have been. Day 3 brought another packed schedule of inspiring talks, practical experiences, new ideas, and, above all, more opportunities to connect with the amazing people behind OpenStreetMap.

🔗 Event website: https://www.osmlatam.org/sotm/2026-en/

📅 Full schedule: https://pretalx.cienciaenmexico.com/sotmlatam2026/schedule/

🌎 Learning from the global community

The day featured keynote talks from the Humanitarian OpenStreetMap Team (HOT) and OpenStreetMap US (OSM-US), alongside a rich program of presentations and discussions.

Throughout the day, we enjoyed a wide variety of talks covering practically everything OSM: mapping, routing, tagging, data quality, community engagement, and much more.

We also learned about MapRoulette challenges for local governments, an interesting way to encourage collaborative mapping and help improve geographic data in areas of particular interest.

❤️ Mapping with and for communities

Perhaps the most meaningful part of the day was hearing about projects that put communities at the center of mapping.

Teams shared their experiences working with vulnerable communities across Latin America, showing how OpenStreetMap can help local governments make informed decisions and prioritize actions where they are needed most.

Another inspiring project introduced elementary school children to mapping through playful activities, using playdough and stickers on top of OSM maps.

Particularly remarkable, these initiatives reached remote communities, some hours away by car from the nearest place with telecommunications access!

These experiences highlight something truly important: OpenStreetMap is not just about collecting geographic data; whether working with local governments, vulnerable populations, or children discovering mapping for the first time, its impact goes far beyond the map itself.

🧭 Taking mapping into the streets!

We also had an exciting hands-on mapping activity using Sketch Map Tool and ChatMap, adding even more tools to our mapping toolkit!

We headed out to the streets surrounding the main event venue, combining paper-based mapping with photography and on-the-ground observations.

It was a great opportunity to explore different ways of collecting local knowledge, documenting our surroundings, and bringing real-world observations into OpenStreetMap.

Sometimes the best way to understand a place is simply to walk through it, observe, ask questions, and listen to the people who know it best.

🌱 Beyond the Map

Throughout these three days, one thought kept becoming clearer to me:

The real treasure of OpenStreetMap is its communities. They are its backbone, its driving force, and its greatest strength.

We have amazing technologies, innovative tools, sophisticated data processing, routing engines, imagery platforms, and countless ways to improve the map.

But none of it would mean nearly as much without the people behind it.

People who volunteer their time, share their knowledge, organize mapping activities, teach others, build tools, collaborate with institutions, and work alongside communities that need better geographic information.

The map is the result, but the community is what makes it possible.

And perhaps that is what Beyond the Map really means: recognizing that our contributions can create value that extends far beyond geographic data, helping people become more connected, informed, represented, and empowered.

🚀 The Journey Continues!

There was certainly a little sadness when the event finally came to an end. It is always difficult to say goodbye after sharing such an enriching experience with so many wonderful people.

But I’m sure everyone is taking something valuable home. I know I am — I learned a ton!

Some of us discovered new tools, others gained new perspectives, many made new friends, and perhaps some even started building partnerships that will lead to future projects and collaborations.

Another heartfelt THANK YOU to all the organizers, sponsors, allies, speakers, volunteers, local governments, venue staff, and every attendee who contributed to making OSM LATAM 2026 México such a memorable experience.

Three days of learning, sharing, mapping, and connecting — but the work and the adventure continue!

Beyond the Map. Beyond the Data. Together, we make a difference. 🗺️❤️

 #OpenStreetMap #OSMLATAM #OSMLATAM2026 #HOT #OSM-US #OpenData #MappingTogether #BeyondTheMap

Apps baru mapku mengunakan map ini terima kasih semua kerana berkongsi

OSM LATAM 2026 México 🇲🇽 — Day 2: Transmute the Map!

Day 2 of OSM LATAM 2026 México brought us another incredible day of learning, collaboration, and community!

🔗 Event website: https://www.osmlatam.org/sotm/2026-en/

📅 Full schedule: https://pretalx.cienciaenmexico.com/sotmlatam2026/schedule/

As every great adventure, the day had its ups and downs. We ended up with two breaks instead of one, but what could have been a downside turned into another opportunity to meet fellow mappers, exchange ideas, and strengthen the connections that make our community so special.

🌎 Collaboration over competition

One of the highlights was hearing keynote talks from sponsors HERE and Overture Maps, learning more about who they are, how they work, and how they collaborate with OpenStreetMap to improve geospatial data.

Sometimes, companies working in the mapping world can be perceived as rivals to OSM. But today’s conversations remind us that the geospatial ecosystem is much bigger than any single project or organization. There are meaningful ways to collaborate, share knowledge, and support open data. Different approaches can complement one another, and the entire community can benefit.

We also had a special talk from Daniela Waltersdorfer, an OpenStreetMap Foundation (OSMF) Board Director, about the Foundation’s role in the OSM ecosystem.

A particularly important takeaway was that the OSMF’s mission is to support OpenStreetMap, not control it. The Foundation helps keep our community healthy and growing while providing the organizational and technological backbone needed to sustain the project for the long term. The map belongs to its community, and that distinction matters!

🗺️ Mapping that makes a difference

Throughout the day, we enjoyed amazing talks exploring how mapping helps local communities, how public transport mapping can improve mobility, and why open geospatial data matters.

We also heard about the production, processing, and analysis of data, between OpenStreetMap and local governments. These exchanges are particularly valuable because they help bridge the gap between community-driven mapping and public institutions, opening opportunities to put geographic information to practical use.

Every road mapped, every bus stop and public transport station added, every building documented, and every dataset made accessible can help someone understand their surroundings and make better decisions.

And this brings us to a thought that stayed with me throughout the day:

What if mapping is a way of transmuting the map — and, in turn, allowing the map to transmute communities into better versions of themselves?

We transform observations into data, data into knowledge, and knowledge into opportunities for action. As the map becomes more complete and useful, it can help communities become more connected, informed, accessible, and resilient.

Transmute the map. Transform the community. ❤️

🤝 A milestone for the Colombian OSM community!

Another wonderful piece of news was the official signing of the Local Chapter Agreement between the OpenStreetMap Foundation and the Asociación de Cartografía Colaborativa de Colombia (AC3).

Following its acceptance in March 2026, this agreement formally recognizes AC3 as an official Local Chapter of the OSM Foundation.

A huge congratulations to AC3 and the entire Colombian OpenStreetMap community, and a big thank-you to the OSMF for continuing to support the growth and organization of our global community!

Local Chapters help strengthen the connections between the global project and the people building it on the ground. This is a fantastic milestone for Colombia and an inspiring example for the wider Latin American OSM community. 🇨🇴🎉

🔥 SotM Latam 2027 is starting to take shape!

During the General Assembly of the OSM Latam Community, we started looking ahead to the next chapter of our regional gathering.

The next State of the Map Latam is already beginning to take shape! SotM Latam 2027 is cooking! 🔥

There is something exciting about knowing that while we celebrate what our community has accomplished today, people are already working to create the next opportunity for us to meet, learn, and build together.

🏛️ Closing the day with history and culture

To wrap up the day, we enjoyed a guided cultural walking tour around Templo Mayor, right in the heart of historic downtown Mexico City.

After a full day discussing maps, technology, communities, and the future of open geospatial data, it was a wonderful way to reconnect with the history and culture of the place hosting us. The city itself became another layer of the experience — a reminder that every map represents places filled with history, identity, and human stories.

A huge thank-you to everyone who made Day 2 so enriching: the speakers, sponsors, organizers, volunteers, fellow mappers, and everyone who shared their knowledge and enthusiasm.

We are not just creating a map. We are building connections, empowering communities, and opening doors to new possibilities.

Transmute the map. Transform the world. 🗺️❤️

Looking forward to another day of learning, mapping, and growing together at OSM LATAM 2026 México!

 #OpenStreetMap #OSMLATAM #OSMLATAM2026 #OpenData #MappingTogether #TransmuteTheMap