Honestly, I have been reading everybody’s diary entries and diving in and looking at all the different areas and detail and I forgot how I even got here! NO idea but I am very intrigued I do not know how much I will have to contribute but I’m determined to figure this all out! I’m fresh meat here amd have never heard of openstreetmap until I landed in the middle of Nigeria very far from home…safe travels and Merry Christmas from Michigan 🇺🇸💋

Love and Light Aphrodite888

I was doing some Unmapped Small Town USA work this evening, and realized that I had tagged a bunch of probable grain silos in other areas as buildings, specifically in Arbela, MO, and Granger, MO, so I’ve gone back in and corrected those to more accurately reflect their purpose. Apologies to Arbela and Granger!

Otherwise, Dover, KY showed up on Unmapped Small Town USA. There’s some great progress already, but still more to do, so I’m taking advantage of some holiday downtime to fill in more buildings.

Otherwise, I hope you have a lovely Christmas Eve, if that is your custom, and a lovely Christmas Day, if that is your custom. If not, I hope you have a very Merry Thursday. :)

নাগা বাজার রাজশাহী জেলার বাগমারা উপজেলার কাতিলা গ্রামের একটি গুরুত্বপূর্ণ বাজার। নাগা বাজার থেকে প্রায় ১৬০০ মিটার দূরে অবস্থিত কাতিলা সবুজ সংঘ হাই স্কুল ও কলেজ, যা স্থানীয় শিক্ষার্থীদের জন্য উচ্চ মাধ্যমিক ও কলেজ পর্যায়ের শিক্ষা প্রদান করে।

বাজার ও স্কুলের ঘনিষ্ঠ অবস্থান এলাকার শিক্ষার সাথে বাণিজ্যিক কার্যক্রমকে সংযুক্ত করে। এই দুই কেন্দ্রের ম্যাপে Node ও Area হিসেবে যোগ করা OSM ব্যবহারকারীদের জন্য এলাকাটিকে সহজে চিহ্নিত ও বোঝার সুযোগ তৈরি করে।

১৫ নং যোগীপাড়া ইউনিয়ন পরিষদ বাগমারা উপজেলার কাতিলা গ্রামের এলাকায় অবস্থিত। এটি নাগা বাজার থেকে প্রায় ১৫০০ মিটার দূরে অবস্থিত। ইউনিয়ন পরিষদ স্থানীয় প্রশাসনিক কার্যক্রমের কেন্দ্র হিসেবে কাজ করে। এখানে ইউনিয়নের বিভিন্ন সরকারি সেবা, নথি, পরিকল্পনা ও নাগরিক সেবা প্রদান করা হয়। নাগা বাজারের সাথে ঘনিষ্ঠ অবস্থানের কারণে এটি এলাকার মানুষের দৈনন্দিন জীবন ও বাণিজ্যিক কার্যক্রমের জন্য গুরুত্বপূর্ণ।

Suite à la découverte du projet “Surveillance under Surveillance” grâce à @apitux, je cartographie les systèmes de videoprotection et de videosurveillance dans le Haut-Mâconnais.

Pour voir le résultat (impressionnant) : suivre de lien.

Số nhà

It is both weird and cool to see the map of my community change in apps I use regularly. Before I started actively updating things in OSM I didn’t recognize all the places OSM is used.

Last November, I [Re]Introduced Ultra v3 which introduced a bunch of new features. Today, I’m happy to share what’s changed in Ultra over the past year.

Since my last update, I’ve implemented the following features in Ultra:

• Many new styling features enabled by continued MapLibre updates
• Sprite support updates
• A new Overpass/OSM XML&JSON-to-GeoJSON conversion library
• More basemap styles & style previews
• More export options
• Transforms
• More providers
• An “Open with Ultra” bookmarklet

🌍 MapLibre updates

In January of 2025, Ultra updated to the freshly released MapLibre v5, introducing globe support! View Example

Since then, further MapLibre changes have enabled a host of new styling features including:

• color-relief styling from raster DEM sources
• Data-driven line-dasharray support
• Improved font support
• New hillshade methods

📍 Sprites

I’ve added two sprite-related features to facilitate map styling:

SVG Support

You can now reference SVGs by URL in icon-image, just as you can reference PNGs by URL. This works well with inline data: URLs to create fill patterns:

View query on Ultra

Emojis

I’ve also added Noto Emojis to the list of sprites bundled with Ultra. Use the emoji: namespace and a short name from https://projects.iamcal.com/emoji-data/table.htm.

Here is an example query that renders each country with its flag:

View Example

🤖 osm2geojson-ultra

At some point, I found myself wanting support for Overpass-derived elements. This led to me forking osm2geojson-lite and creating osm2geojson-ultra. This replaces osmtogeojson in Ultra to convert Overpass responses to GeoJSON for use with MapLibre.

Here is a quick rundown of the differences between the three libraries:

For more details and how to use osm2geojson-ultra in your own JavaScript projects, see the GitHub Repo.

Using derived objects support, I was able to create this query for making transit maps with Ultra:

View query on Ultra

🎨 Styles

Stadia Maps has kindly offered their styles for use on Ultra, including those from Stamen Design.

I’ve also added a more visual style picker so you have an idea of what each style looks like without having to actually load it:

💾 Export options

The single-function download button has been replaced with an export dialog that also allows you to copy GeoJSON to your clipboard or export the created MapLibre style.json for use on other sites.

💫 JavaScript Transforms

For a long time, I’ve wanted to be able to use Turf.js to mutate the GeoJSON rendered by an Ultra query. I’m stoked to share that I’ve figured out a way to integrate that! You can now specify a transform YAML front-matter config param to run arbitrary JavaScript on your query’s results.

It must consist of the source code for a JavaScript module with a default export of a function that accepts a GeoJSON FeatureCollection (the query result) and returns one too.

For example, this is a transform that does nothing:

yaml transform: "export default data => data;"

But for a more interesting example, here is a query that renders the triangulated irregular network of a set of gunshot detectors and filters out edges that are too long:

View query on Ultra

To load 3rd party libraries, use a cloud JS Module CDN like esm.sh.

⚙️ More Providers

javascript

Since I’d built the JavaScript sandbox for transform support, I figured I should support “bring your own query provider” by implementing a JavaScript provider!

Similar to transforms, it must be a JS module that exports a function named source which returns a MapLibre Source.

Here is an example query I wrote this fall to find playgrounds along the route of my family’s first big roadtrip with our 1-year-old:

View query on Ultra

dsv

Ultra now also supports CSV&TSV powered by csv2geojson.

This powered a super early version of MapRVA’s Yesterdays project using a Google Sheet!

postpass

When Frederik Ramm announced Postpass, I was excited because the API returns GeoJSON and Ultra actually supported it out-of-the-box:

I have since added a new postpass provider that is configured by default to use the GeoFabrik instance of Postpass.

View Example

New BBox shortcut

Since Postpass is PostGIS and bboxes must be specified differently, I’ve introduced a new flexible way to express bounding boxes in Ultra queries. Like {{bbox}} it is wrapped in double curly braces, but inside those braces can be any combination of the letters w,n,e,&s which represent west, north, east, and south respectively. These will be replaced and comma-separated.

So for example, in a Postpass query, you can use geom && ST_MakeEnvelope({{wsen}},4326) to select features intersecting your map’s current bounding box.

For more unique ways of specifying the bbox, using just a single letter allows for any (lat/lon for now, no support for using a different CRS) format, such as QLever in this Example.

esri

I’ve also added a new query provider that supports vector Esri MapServer and FeatureServer layers powered by esri-dump.

View example query on Ultra

🔖 Open with Ultra

I’ve also built a bookmarklet to easily open resources using Ultra.

It features special support for:

• overpass-turbo.eu - Loads query & viewport from Overpass Turbo in Ultra
• QLever - Loads query & server from QLever in Ultra
• Sophox - Loads query & server from Sophox in Ultra
• geojson.io - Loads the GeoJSON from geojson.io as the query in Ultra
• Gists - Loads the current gist as the query in Ultra
• GitHub - Loads the githubusercontent.com URL for a file loaded in the web UI

For all other sites, it loads the URL as the query.

Ultra features some query providers which work well with this:

• osmWebsite - detects https://openstreetmap.org/[node|way|relation]/:id URLs and loads that object via the Overpass API
• osmWiki - detects https://wiki.openstreetmap.org/wiki/Key: and https://wiki.openstreetmap.org/wiki/Tag: URLs and loads that object with that tag or key via the Overpass API
• taginfo - detects https://taginfo.openstreetmap.org/key/ and https://taginfo.openstreetmap.org/tags/ URLs and loads that object with that tag or key via the Overpass API
• kml - detects https://www.google.com/maps/d (Google My Maps) URLs and loads that map via the KML export.

Install it here: https://overpass-ultra.us/docs/open-with-ultra/

⏭️ Next up: an Ultra workshop at Mapping USA

Want an hour long workshop on how to use Ultra? Sign up for Mapping USA!

As a principle, I’ve always tried to use open-source software over proprietary software for any of my digital needs. I’ve personally found open source to be both more accurate and more sensible to use than proprietary alternatives.

One of the very few aspects of my life that had still not adopted open source was maps. I always used both Waze and Google Maps for everything. But whenever I looked at the maps, it felt like something was missing. I looked around, checked the environment, and realized how much of my surroundings simply wasn’t reflected on the screen.

I wanted to fix it, but… Google Maps doesn’t allow you to just add things. And while Waze does have an editor, it’s extremely locked down for the average user. So, I looked up online alternatives.

I discovered OpenStreetMap two months ago, and I found myself in awe of the sheer amount of detail… Far more than Google Maps or Waze could offer. It just so happened that I was on a trip to Barcelona, and I was using CoMaps to navigate. Using CoMaps proved extremely reliable, especially for public transportation. I never missed a metro, I found all my destinations quickly, and it was very easy to get around.

Still riding the Barcelona high, I opened CoMaps back at home and was fairly shocked to see that my neighborhood didn’t exist at all… Where the heck is it?!

So, I got on my computer, logged into OpenStreetMap for the first time, and started using the iD editor. In just a few hours, the rough outline of my neighborhood was there.

Soon enough, I found myself mapping for hours. Even during lectures, I’d have an OSM tab open for casual mapping. Then it escalated. I started bringing my laptop everywhere I traveled to map things on the go. I began using StreetComplete to add missing metadata. I took pictures and videos. Then I started recording GPS traces. And now I’m even considering setting up a full LiDAR mapping mount for my car…

Now I sit at 16k contributions, with over 400 buildings added. My neighborhood is micro-mapped to hell, and I plan to continue this with the rest of my town.

OpenStreetMap is the best.

The grumpy old man returns.

• Приказ Министерства образования и культуры Калужской области от 27.08.2008 N 1506 “О выявленных объектах культурного наследия, расположенных на территории городского округа “Город Калуга” (вместе со “Сводным перечнем выявленных объектов культурного наследия, расположенных на территории городского округа “Город Калуга”)

OSMWrapped is a fun tool that visualizes your personal OpenStreetMap (OSM) mapping statistics — including edits made, countries mapped, and active mapping days.

Today I’m celebrating one full year of mapping every single day! 🎉🥳

Grateful for the OSM community and the joy of contributing, one edit at a time.

Cheers!

93/93

আজ আমি আমার স্থানীয় এলাকা নাগা বাজার OpenStreetMap–এ যুক্ত করেছি। এটি একটি গুরুত্বপূর্ণ স্থান, কারণ নাগা বাজারের আশেপাশের জনগণ দৈনন্দিন জীবনযাপনের জন্য এই স্থানটি ব্যবহার করে।

নাগা বাজারের বিশেষত্ব হলো এটি তিনটি গুরুত্বপূর্ণ সড়কের সংযোগস্থল। এই সড়কগুলো হলো:

নাগা বাজার – মুলিভিটা সড়ক

নাগা বাজার – বীরকুৎসা সড়ক

নাগা বাজার – ভবানিগঞ্জ সড়ক

এই তিনটি সড়ক এলাকার মানুষকে একে অপরের সাথে সহজেই সংযুক্ত করছে এবং স্থানীয় বাণিজ্য ও যোগাযোগে গুরুত্বপূর্ণ ভূমিকা পালন করে। আমি OpenStreetMap–এ নাগা বাজার যুক্ত করার সময় এ সমস্ত সড়ক ও এলাকাসহ বিস্তারিত তথ্য দিয়ে কাজ করেছি।

এটি আমার ব্যক্তিগত ডায়রিতে সংরক্ষণের জন্য একটি গুরুত্বপূর্ণ অর্জন। OpenStreetMap–এ স্থান যুক্ত করার মাধ্যমে স্থানীয়দের জন্য তথ্য সহজলভ্য হবে এবং ভবিষ্যতে মানচিত্র ব্যবহার ও রাস্তাপথ পরিকল্পনায় সহায়ক হবে।

নাগা বাজারের সঠিক স্থান, ল্যাটিটিউড ও লংগিটিউড, এবং সংযুক্ত সড়কগুলো OpenStreetMap–এ উল্লেখ করার মাধ্যমে স্থানটি আরও বেশি কার্যকরভাবে চিহ্নিত হয়েছে। এই কাজ আমার জন্য শিক্ষণীয় এবং এলাকার ডিজিটাল নথিপত্র তৈরিতে সহায়ক হয়েছে।

So, as it turns out, Mapmas is best-effort. ;)

I came down with something Thursday night, and I’m just now starting to feel sufficiently decent. I housed 3/8 of a pizza last night, which means my appetite is back. I mostly took it easy, but I did have a little energy to start tracing out a lot of Mechanicsburg, Virginia, United States, which was posted a few days ago on the Unmapped Small Town USA Mastodon account.

Appalachia is beautiful: rolling mountains, verdant woods, small houses and farms dotting the countryside. I’ve had the privilege of traveling through Virginia and West Virginia in the past, and it’s even more gorgeous in person. Lush tree coverage, though, does make it a little challenging to trace buildings when imagery is from spring/summer, so that was tough at times. I’ve noticed the houses in the region are also more likely to have tight corners, or a roof line that turns and then juts out a half meter or so, which can look like slight distortion on imagery, but is actually part of the geometry. I took some liberties, but I did my best!

I also struggled with finding independent sources for things like street names. It looks like Virginia state highways use the same numbers across the state, but are disjoint, and correspond to different local roads in different areas. So State Route 653 in Bland County, for example, is Osborne Drive in Mechanicsburg. This particular fact shows up in a VDOT report from 2017, I think (I’d need to source it again), which I believe is okay to use? I’m not entirely sure, though, so I left it for now. Copyright law is obnoxious.

Anyway, it’s nice to be able to sit and map from home when you can’t go outside. It was fun to spend some time in Mechanicsburg and get to know the area a bit.

Onward and mapward!

One OSM-related activity I spend lots of time on is micromapping recreational areas, such as parks. Manually detailing out areas is satisfying, but I’ve also been on the lookout for ways to put my programming skills to use.

A common pattern I noticed in these areas is representing a block of pitches or courts (such as tennis courts) as a single, abnormally large “tennis court”.

It’s a start, but obviously could use some refining. Each individual court could be represented by a separate area. While this probably needs no justifications, I’ll provide a few since I’d like to convince myself I’m working on improvements that might mean something to someone, rather than just creating data because it gives me dopamine:

• Independent courts allow for better querying: we can ask questions like “how many tennis courts are in my city?” and get an accurate answer.
• Some renderers (like openstreetmap.fr) render various courts with appropriate marking lines, allowing quick identification.

I used overpass turbo, some custom code, and Map Roulette to set up a pipeline to fix these “multi-pitch areas”. Here’s my workflow:

1. Query overpass for a raw list of pitches

Using a query like this, collect all the pitches (large or not) in the target area:

{{geocodeArea:Colorado}}->.searchArea;
way["leisure"="pitch"]["sport"="tennis"](area.searchArea);
foreach (way._(if:count_members() == 5); out geom;);

There are a lot of tennis courts in the United States^{[citation needed]}. To do the whole country, I had to break it up into regions and query each region separately. This is an area for future improvement; there’s probably a way to automate making a string of overpass queries.

You’ll probably notice this only collects areas that are quadrilaterals. It’s easiest to calculate the dimensions of those, so I’m starting there. More complicated areas can come later.

2. Filter down to unusually large areas

I can download all the areas from overpass as GeoJSON and write code on my computer to do whatever I want to it. In this case, that is calculating the dimensions of each area, and saving the ones that are some factor bigger than we’d expect to another GeoJSON file. You can peruse the relevant code here and here.

3. Upload filtered list to Map Roulette

Getting the actual courts drawn in requires human intervention, and Map Roulette is a great tool for that. I loaded the output file as a Map Roulette task. We’re currently 20% of the way through over 14,000 multi-pitch tennis courts in the US - click the link to help!

4. Make fixes on Map Roulette

Much better!

Related Work

I’ll be looking for other applications of this pipeline as time permits. The obvious one is to do this for other types of sports. We also completed another task to review “tennis courts” that, based on their sized, looked a lot more likely to be pickleball courts instead. Let me know if you have any other suggestions!

(Writing a short stub in case i forget it again)

Estonian mappers may have already noticed how this year Land Board’s imagery is still missing. Previously new orthophotos were captured in March-April, preliminary release was in May-June and TMS layers were available in OSM editors by around September, then this year there are no images.

Turns out on 31st of March 2025 someone filed a complaint to Chancellor of Justice, that their garden hose can be identified on the imagery. On 27th of November chancellor’s response was published and public broadcaster published few small news:

• EST: https://www.err.ee/1609869541/oiguskantsler-palub-kaaluda-kaardirakenduste-eraelulist-detailsust
• EST: https://www.err.ee/1609870686/maa-ja-ruumiamet-plaanib-geoportaali-andmeid-uldisemaks-muuta
• ENG: https://news.err.ee/1609869930/land-and-spatial-board-to-make-publicly-available-map-data-less-detailed
• Original source documents:
  • EST PDF: https://www.oiguskantsler.ee/sites/default/files/2025-11/Orto-%20ja%20kaldaerofotode%20avalikustamine.pdf
  • Sample images: https://adr.rik.ee/okk/dokument/18175002 (asice is basically zip file, you’d need digidoc4 to open it).
    • Mirror at Land Board’s registry: https://adr.envir.ee/et/document.html?id=8c7c0dd4-17c5-463b-a00c-57c6019ea8d8
  • Original complaint (restricted access): https://adr.rik.ee/okk/dokument/16914665
  • § 26 of constitution which according to chancellor prohibits aerial images: https://www.riigiteataja.ee/en/eli/ee/521052015001/consolide/current#para26

Why this matters to OSM?

At least 90% of OSM’s data originates from Land Board’s imagery, either through imports or via usual imagery tracing. Esri and Bing are also using using Land Board’s data for Estonia.

Most worrisome is how Google Maps is treated as etalon of privacy. If imagery is sharper than Google’s then therefore it violates someones privacy. Media gave another spin, claiming the planes flying 270km/h at 3km altitude can capture readable images of cars’ license plates.

PS. I filed request to see new imagery. No plates were visible, and despite using new better camera, imagery quality was at same level as before, except contrast was higher than before.

Today, i wear a T-shirt printed with Medan’s road network, based on OpenStreetMap data.

Every time i glanced down at those tangled lines, a quiet curiosity crept in. I kept wondering who mapped this exact line segment I’m looking at right now, which contributor traced it, corrected it, or patiently aligned it to reality. It’s a strange and comforting thought, carrying a small piece of someone else’s mapping work on fabric, a reminder that this map is made of countless individual moments of care.

11/12/2025-17/12/2025

Mapping campaigns

• A collaborative mapping campaign is being coordinated by the Virtual Institute for Sustainable Development, IVIDES DATA, and the Social Project Management Centre of the Federal University of São Francisco Valley. The goal is to map the 18 productive rural villages in the government program titled ‘Population Resettlement Programme of the São Francisco Integration Project’, implemented by the Ministry of Integration and Regional Development of the Federal Government of Brazil. A general tagging scheme for mapping rural villages on OpenStreetMap has been developed and is available at Zenodo.org. The campaign documentation is available on the OSM Wiki, and you are welcome to participate.

Community

• GeoCompas shared their 2025 mapping activities, such as participating in national mapathons across Colombia, Mexico, Honduras, Ecuador, and Peru.
• Frederica Gaspari published about her 9 years of OSM contributions, using the OSM Wrapped tool (we reported earlier).
• 00-sq has completely mapped the Cetățuia hamlet in Luncavița, Tulcea, Romania.
• Jwheare has analysed how slipways are tagged along the southeast coast of Scotland.
• PizzaTreeIsland has started mapping roof:colour tags on buildings in OpenStreetMap and has built a custom-made tool that uses a neural network to automatically predict the correct roof colour tag from aerial imagery.
• MapRVA has developed Yesterdays, an interactive web map that allows users to explore thousands of historic photographs of Richmond, Virginia.

OpenStreetMap Foundation

• Courtney Williamson announced the recipients of the 2025 OpenStreetMap Engineering Working Group Microgrant Programme.

Local chapter news

• Katja Haferkorn reported ► that the FOSSGIS community held its online networking meeting on 20 December, drawing more than 20 participants for a discussion focused on the use of AI in geospatial data analysis. The next session is set for 15 April 2026.

Education

• Dr Victor Ndubuisi Sunday reported on the AFRIGIST Alumni International Network Online Training Workshop on ‘OpenStreetMap: From Global Action to Local Impact – Leveraging Open Map Data for the Sustainable Development Goals’, which was held on 15 and 16 December.

OSM research

• Christian Mikovits and Thomas Öberseder have published the ‘Land and Sea Use and Change Maps’ report with the results of a study about large wind power installations in the EU (onshore and offshore). They used and validated OSM data on power wind turbines’ geo-locations. The research is part of ‘Wind in My Backyard’, a programme funded by the European Union to stimulate the adoption of wind power as a renewable energy source. You can access the results and other files of the project in the Zenodo repository.
• HeiGIT reported that Andorful and others have published a paper on transparency and trust in collaborative mapping. The research aimed to expose the vulnerabilities and risks associated with the current approach to integrating AI-assisted road recognition data into OSM by examining how these integration practices affect the reliability of crowdsourced mapping platforms and the integrity of their datasets.

Maps

• wydow tooted about the uMap Territoire Numérique Libre for France, created by Adullact (a collective of open data producers) in 2023 and updated this month. The uMap shows the entities that belong to France Numérique Libre .

OSM in action

• ^[1] Tilikan Indonesia has developed ‘Pantau Bencana Banjir Aceh & Sumatra’, an OpenStreetMap-based interactive map dashboard to monitor current disaster mitigation efforts for the recent Sumatra floods and landslides.
• Hans Hack has built an interactive map that lets you explore how much public space is taken up by car parking and how that compares to green and play areas, across all of Berlin, offering insight into how the city allocates its shared space.
• HeiGIT reported that they are developing dynamic routing to support humanitarian response by integrating real-time, mission-specific information from organisations and local communities directly into route calculations.

Software

• HeiGIT reported that they have released a new version of hiBike for the Climate Action Navigator, which adds two new indicators (Greenness and Detour Factors) to the pre-existing (Bikeable Path Categories, Dooring Risk, Path Smoothness, and Surface Types) ones. They have also extended the summary statistics to provide more actionable information for stakeholders.
• simsee has developed a Chrome plugin that makes it easy to copy the current Mapillary image ID and traffic sign data as OSM tag to be used in iD or JOSM.
• Jonas von Ruette, Bernat Polvillo and Marcio Cataldi shared about SALUS, a wildfire data viewer which was developed in the research project ‘SALUS Wildfire Risk Solutions’, funded by the European Union, to visualise simulated wildfire propagation probability maps and extracted infrastructure data from OpenStreetMap. The data viewer was developed in Python with the libraries Dash and Plotly and based on an example from the Dash gallery.
• Trufi Association’s Volunteer of the Month for December is influencer-geek Max Weber, who volunteers his expertise to improve Trufi’s open-source public transport code.

Programming

• Farshid Hakimy has developed adressSuche, an open-source geocoding API for German addresses, built from Esri Deutschland and OpenStreetMap data sources.

Releases

• Melani Eckle-Elze published about the release of the version 2.1 of Sketch Map Tool, which has introduced advanced algorithms for improved sketch detection, enabling more accurate interpretation of hand-drawn elements such as roads, rivers, and landmarks.

Other “geo” things

• Mario Petzold, of Golem.de, reported that the European Space Agency’s Ariane 6 rocket has successfully delivered two new navigation satellites into medium Earth orbit.
• HeiGIT recapped the ‘Global Digital Health’ Research Alumni Project Week 2025 that brought together international researchers and local experts to discuss advancements in global digital health. HeiGIT joined the discussion on this growing topic and shared its tools and research in geo-informatics applications to global health.
• Lauren Leek has published about restaurant recommendations biased by geo-applications in an interesting blog post: ‘How Google Maps quietly allocates survival across London’s restaurants – and how I built a dashboard to see through it’.
• A group of journalism students, from the Axel Springer Academy for Journalism and Technology, have analysed AIS data (the automatic identification system that broadcasts ship positions) to detect anomalous vessel movement patterns that may be linked to recent drone swarm incidents in Europe.

Upcoming Events

Country	Where	Venue	What	When
	Stainach-Pürgg	Online	19. Österreichischer OSM-Stammtisch (online)	2025-12-18
			UN Mappers Mappy Hour	2025-12-19
	Mumbai	Khodadad Circle, Dadar	5th OSM Mumbai Mapping Party – Dadar	2025-12-19
			OSM World Mappy Hour	2025-12-19
	Potsdam	Luisenplatz, Potsdamer Weihnachtsmarkt	Potsdamer Mappertreffen	2025-12-19
	Bengaluru	Basaveshwara Nagar	OSM Bengaluru Mapping Party	2025-12-20
		MAP Mercator museum	OpenStreetMap Belgium at the MAP-Mercator museum	2025-12-20
	Kalyani Nagar	TomTom, Shanti One, Ramwadi, Pune	Indoor Mapping Party @ TomTom Pune	2025-12-20
		Cinestar Fulda	Jahresabschlussmapping	2025-12-21
			Missing Maps : Mapathon en ligne – CartONG [fr]	2025-12-22
	Stadtgebiet Bremen	Online und im Hackerspace Bremen	Bremer Mappertreffen	2025-12-22
	Siliguri	Panitanki More	11th OpenStreetMap West Bengal Mapping Party	2025-12-27
		MAP Mercator museum	OpenStreetMap Belgium at the MAP-Mercator museum	2025-12-27
	New Delhi	online	OSM India×TomTom Online Mapathon	2025-12-28
		MAP Mercator museum	OpenStreetMap Belgium at the MAP-Mercator museum	2026-01-03
	Braunschweig	Stratum0	Braunschweiger Mappertreffen im Stratum0 Hackerspace	2026-01-03
	नई दिल्ली	Jitsi Meet (online)	OSM India – Monthly Online Mapathon	2026-01-04

Note:
If you like to see your event here, please put it into the OSM calendar. Only data which is there, will appear in weeklyOSM.

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

তারিখ: 21.12.2025 স্থান: Naga Bazar, Bagmara, Rajshahi

আজ আমি OpenStreetMap (OSM)-এ “Naga Bazar–Bhobanigonj Road” যুক্ত করেছি। এই সড়কটি নাগা বাজার থেকে ভোবানীগঞ্জ পর্যন্ত বিস্তৃত এবং এলাকার মানুষজন দৈনন্দিন চলাচল, বাজারে যাতায়াত এবং কৃষি পণ্য পরিবহনের জন্য ব্যবহার করে।

আমি সড়কটি OSM-এ যোগ করার সময় ঠিক নাম, অবস্থান এবং রাস্তার ধরন উল্লেখ করেছি। এছাড়া, Description বক্সে সংক্ষিপ্তভাবে লিখেছি সড়কের গুরুত্ব এবং স্থানীয় ব্যবহার। Changeset comment-এ উল্লেখ করেছি যে এটি স্থানীয় সংযোগ রাস্তা।

এই কাজটি করতে গিয়ে বুঝতে পারলাম যে OSM-এ স্থান সংযোজন শুধু মানচিত্রে দেখানোর জন্য নয়, বরং তথ্যকে ডিজিটালভাবে সংরক্ষণ ও বিশ্বের সাথে সংযুক্ত করার একটি মাধ্যম।

আমি আশা করি ভবিষ্যতে আরও রাস্তা, বাজার এবং স্থানীয় এলাকা OSM-এ যোগ করে আমার এলাকার তথ্যসমৃদ্ধ মানচিত্র তৈরি করতে পারব।

Ces derniers jours, j’ai tenté de compléter et de mettre à jour les hôtels à Genève.

Point de départ

Il y a environ 150 hôtels dans le canton de Genève, voire plus ou moins selon les critères. En plus des hôtels traditionnels, divers services proposent un ou plusieurs studios/appartements meublés dans le même immeuble. D’autres servent à fournir des logements temporaires sociaux ou destinés à des institutions (CERN, université, etc.). HVS mentionne 97 hôtels avec 8100 chambres pour Q1 2025.

Modèle et tags

En suivant les indications de wiki.openstreetmap.org/wiki/Tag:tourism=hotel, le tag tourism=hotel figure en principe sur l’immeuble. S’il y avait été construit comme hôtel, on trouve également building=hotel même si l’immeuble n’est plus utilisé à cette fin. Si l’hôtel comprend plusieurs immeubles, il y a une relation pour l’hôtel. Le minimum est que l’information se trouve sur un “node”. C’est aussi le cas quand le même immeuble abrit plusieurs hôtels.

Pour un hôtel, j’ai essayé d’ajouter au moins les tags suivants: name, addr:street, addr:housenumber, addr:city, addr:postcode.

stars= est renseigné pour les 4/5 étoiles. rooms= pourrait être intéressant à spécifier d’avantage. “internet_access” me semble désuet et “payment” pas intéressant. Idéalement, on trouverait la marque dans brand=, l’opérateur local ou global dans operator= et le propriétaire dans owner=. Parfois ça se confond ou ça dépend du même. Pour des immeubles avec un architecte connu, il peut y avoir également architect=, construction_date=, etc.

Vérification, références possibles

Au-delà d’une vérification sur place, https://reg.app.ge.ch donne une base plutôt complète, mais son interface est difficile à utiliser. J’y ai remarqué qu’une erreur. Dans OSM, on pourrait reprendre leur référence avec ref:CH-GE:REG=. L’entreprise y mentionnée est l’ operator= , voire le owner= .

https://www.geneve.com/en/plan-stay/where-to-stay/find-your-hotel se veut assez complet. Les “stars=” devraient également s’y trouver. HotellerieSuisse fournirait également une base, peut-être la même.

https://tel.search.ch est curieusement lacunaire. Leur carte inclut également un hôtel de police.

Accor.com donne probablement aussi une bonne couverture de base (par nombre d’établissements, mais les Threskiornithidae sont difficiles à suivre). D’autres marques et opérateurs avec plusieurs incluent Manotel, Rey, Fassbind (×2), Marriott, SV Hotel, Nash, IHG, IHA, SEGH, Hamlet, Sophos Hotels, Longemalle, Midi-Ambassador, Dousse et VisionApartments.

Mises à jour

• J’ai créé des tags pour environ 15 hôtels et tenté de dessiner un immeuble. Certains de ces hôtels sont récents (Hood, Pratik, Intercity), d’autres moins (Rousseau, Calvy, Marmont, Hôtel de Genève, Comédie, d’Allèves, Hauts-de-Rive, etc.). J’ai mis le Floatinn dans le port.
• Il y avait ca. 3 qui avaient été fermés entretemps, parfois depuis des années (signalés par “disused:tourism=hotel” ou simplement “building=hotel” et/ou “old_name=” sans “tourism=hotel”; ou amenity=restaurant si cette activité continue). Certains figurent encore dans divers services de réservation, mais ne donnent pas de chambres disponibles lorsque l’on saisit des dates.
• Les hôtels actuellement fermés qui devraient (re-)ouvrir (p.e. Richemond depuis 2020, Fairmont jusqu’en 2027, Strasbourg-Univers) sont signalés par disused=yes et une annotation.
• Ceux qui ont changé de nom ont leur ancien nom sous old_name= (p.e. Aida, Kaufmann, Rio, Chantilly, Bellevue, Lutetia, Rivoli, Berne, Rhône, Touring-Balance, Penta, Windsor, Etap, Le Grenil, Carmen, Sofitel, Natel 😉, ..). Le vieux site de Cranchi et des références similaires aident à les renseigner. Beaucoup sont également dans le site sur l’architecture genevoise (geneve-archi.ch). On y trouve également certaines marques qui ont changé de site.

Suite possible

Il doit y avoir encore quelques hôtels à rajouter et des éléments “=hotel” dans OSM avec peu de tags que l’on devrait vérifier. J’y ai trouvé au moins un élément qui n’était jamais un hôtel.

KelaFuti, dora_explorateuz, vatlark, p4b0r4 et d’autres ont également mis à jour ces informations en 2024/2025.

(Please provide feedback in English, French or other languages.)

Добрий день! Я новий редагувач мапи Openstreetmap frimtears🪪 Редагувати я почав 13 грудня 2025 року!📅 Описання моїх змін✏️: -Додавання будівель🏠 -Додавання дерев та лавочок🌳 -Додавання магазинів🛒 -Додавання вулиць🏘️ -Додавання тротуарів та пішодних доріжок🚶

А тепер до виправленнь✏️: -Виправлення тегів🪧 -Виправлення проблем з будівлями, доріжками, зонами та парковками!

Якщо вам не подобаються мої зміни пишіть мені на ту зміну яка не сподобалась.

Wikidata
Openstreetmap Weg
OSM.wikidata.link
Artikel op ONH Wandelaars op de Spaarndammerdijk, 1826. Beeld: beeldbank Noord-Hollands Archief.

Irpavi 2 South Route

The city of La Paz, Bolivia, has the Puma Katari public transportation service, which covers the 9 macro districts and is currently deployed through 10 routes. Since its launch, this service has been a great promise, offering benefits such as preferential treatment for people with disabilities, children and the elderly, in addition to allowing the transport of bicycles in the front compartments of the buses, thus encouraging the use of this means of transportation. ecological. We are often traveling to different places in the city to carry out our field work. We know that some visitors or even people who know about this transportation service face difficulties because they do not know which route to take or where the stops are, especially when trying to reach peripheral areas.

We have had the experience of looking for a PumaKatari stop and, when trying to find it, the navigator pointed us to a location that, upon arrival, we discovered was no longer in use. This made us wonder: how reliable is the information we are using? As connoisseurs of OpenStreetMap (OSM), we decided to investigate if the PumaKatari information was updated on this platform. Upon further investigation we found that the information available in OSM of this area presents inaccuracies in some data and a lack of updated data on routes and vehicle stops of the PumaKatari municipal transport As of November 2023, it could be seen that on the OpenStreetMap platform. Of the 10 PumaKatari routes, only 5 are mapped in OSM, that is, barely 50%. And of the 603 stops that exist, only 288 are registered (48%), and many of these are incomplete or imprecise. It was also noted that very few pedestrian routes (sidewalks) and bicycle routes are mapped, in some sections, in a disconnected manner. It seems that the mappings have been done in isolation, without clear coordination. so it is a project worth undertaking to make the lives of all of us who move around La Paz easier.

Through an investigation in the pages of the mayor’s office, we identified a reliable source that details the routes taken by this transportation system. We downloaded the information available on the mayor’s Mobility Planning Unit page and compared it with the information available on OSM.

Area to be mapped

To address this problem, the Irpavi II South route was selected as a pilot area for mapping and updating in OpenStreetMap. The map shows the round trip route as well as the area covered by the mapping. During the process, PumaKatari stops were downloaded from OSM, but it was noted that some were not recognized due to lack of uniformity in editing. The black dots represent these stops, while the orange dots indicate the stops downloaded from the City Hall platform. This highlights the need to update OSM to accurately reflect all stops on the Irpavi II South route, ensuring the integrity of public transport information.

Purpose

This project not only seeks to update and add information in OpenStreetMap, but also to correct the lack of standardization observed. We will map pedestrian and cycling routes close to those of PumaKatari to provide safe infrastructure and encourage cycling. Additionally, the project will encourage community participation in the use of sustainable transportation and will train YouthMappers-UMSA youth in mapping and updating data. In a meeting to present the project to the mayor’s office, we were informed about an application that already included stops and routes, although some of us were not aware of its existence. We saw that outside of this application, the information is not updated and available in other browsers. With the aim of contributing positively to the city that has welcomed us, we hope that our initiative will help improve the distribution of transportation information in the community. To strengthen our project, we contacted Trufi Association, who have extensive experience in developing mobile applications for urban transportation and in route mapping in OpenStreetMap. During a visit to the department of Cochabamba, they welcomed us and They kindly shared their experiences with us. They also provided us with a course with the necessary tools, which helped us improve our implementation of this project.

Methodology

1. Photogrammetric Survey The first phase of this project consisted of carrying out the photogrammetric survey of the Irpavi II South and PumaKatari route using a UAV aircraft, as well as carrying out the corresponding photogrammetric processing. First, we used a drone to capture aerial images of the PumaKatari’s Irpavi 2 South route and process them to ensure they were accurate. These images were uploaded to OpenAerialMap

2. Data Collection: IRPAVI II Route In the second stage, we collected data in the field using the StreetComplete application to identify the type of road surface, verify if it had sidewalks and lighting, and generate notes for filling out data at each of the stops. In addition, the presence or absence of sidewalks could also be recorded in the data collected with StreetComplete. Using the Mapillary app, we captured the round trip, documenting both the left and right sides of the road. 3. Remote Mapping With the aerial images already published in OpenAerialMap, two projects were created on the TeachOSM Tasking Manager platform, taking advantage of the advantage of being able to directly link the aerial photographs that we uploaded to OpenAerialMap in Tasking Manager. The first project focused exclusively on mapping roads and stops, while the second focused on mapping houses, buildings and infrastructure, in order to make the most of the images captured by the drone. To begin the work, it was necessary to carry out training in which the purpose of the project was shared.

Finally, we trained the YouthMappers-UMSA community to accurately map routes and stops on OpenStreetMap, including nearby walking and cycling routes. For mapping routes and stops, we add essential information such as the cost of the service, the operator, the type of payment and the schedules. We also record the type of road surface, which varies along the route. As for the stops, we note if they have seats, trash cans, umbrellas and if they have lighting. Additionally, we document the number of lanes and their direction. By mapping pedestrian paths and sidewalks, we were able to identify several important aspects, such as whether they had raised or lowered curbs, whether the pedestrian crossing was marked or not, and whether there were pedestrian paths. In remote places on the outskirts, we even notice the absence of sidewalks. This mapping is very important to guarantee accessibility, especially for wheelchair users, and to evaluate the accessibility of establishments. Although the initial objective was to map bike lanes, the route selected for mapping does not have a complete bike lane circuit. However, there are small sections of cycle paths that are only enabled on weekends. Considering the importance of this means of transportation, we generated a proposal for a cycle path circuit. Our colleagues who live in this area helped us prepare it, taking into account two ways that could be considered for its implementation.

Getting into Risk Mapping

During the development of this project, in March of this year, the Irpavi and Arumthaya rivers overflowed due to the rainy season. This event occurred very close to the area selected for mapping. Therefore, we could not be indifferent to this situation. We carry out a mapping of risk labels. Adele Birkenes and Rory Nealon provided us with the necessary guidelines for adding flood vulnerability information to OpenStreetMap, telling us what tags we could use to note that a stretch of street has been damaged. With the support of Dr. Yuri Sandoval, Rodolfo Vargas and the members of the chapter, verification of the field work for data collection in the affected area was carried out. The collapse of streets, landslides, dragging of material and the increase in the flow of rivers were observed, which affected local roads and homes built near the tributaries. Taking this into account, the nearby homes that were already mapped, along with the georeferencing of the field work we carried out, allowed us to add the necessary labels.

Conclusions

Mapping routes is crucial for both the local community and visitors. Delving deeper into mapping roads and sidewalks, especially for people with disabilities, and mapping hazards, was an unexpected but indispensable added value. This approach allowed us to better understand its importance and provided valuable guidelines for future projects.

It has given us a clear picture and excellent guidelines to move forward. The satisfaction of having generated a detailed database of the identified stops and having developed a clearer methodology to structure the process motivates us to continue with the next routes. Being part of the projects selected by Latin American MicroGrants has been a wonderful experience. We were able to appreciate the diversity of approaches in open access mapping and share our work at the YouthMappers presentation at Cafecito. We learned about other incredible projects in the region and reinforced our interest in continuing to map. It motivates us to continue with more projects that contribute to improving our city and inspire more young people to learn about these tools and discover how they can become agents of change.

Acknowledgments

Special thanks to:

• To the regional ambassadors youthmappers 2024, who provided us with suggestions at every stage. Thank you for giving us the opportunity to launch this project and for supporting us through each phase.

• Having an insight into the work that Trufi Association does in Cochabamba was very important. Through knowledge of their methodology and the use of open data, we were able to significantly improve our efforts.

• To our collaborator, Rodolfo Vargas (member of OSM Bolivia), for his constant updates on OSM tools; his trust and generosity were essential to the project.