02/04/2026-08/04/2026

Mapping

• Comments on the following proposal have been requested:
  • Deprecate railway=narrow_gauge
• The following proposals are up for a vote:
  • man_made=cable_landing_station, to standardise the mapping of submarine cable landing station locations in OpenStreetMap. The tag is intended to more accurately help map this important infrastructure for international data connections (voting until 14 April 2026).
  • aerodrome:classification=*, to classify aerodromes more precisely according to their use and significance (e.g. international, regional, or local) (voting until 16 April 2026).

Community

• SeverinGeo, one of the French editors on weeklyOSM, has started a subjective review of weeklyOSM on Mastodon threads in French, English, and Portuguese, highlighting relevant information or extending articles with commentary.
• Pieter Vander Vennet provided an overview of the reviews made using MapComplete (2026 edition). Most reviews are located in Europe and focus on categories such as food, shops, and leisure activities.
• Engelbert Modo published , on LinkedIn, about a new initiative titled ‘CityMAPPER Externship 2026’, which aims to develop local capacity on mapping with OpenStreetMap and using open data, with initial focus on urban mapping in Cameroon. This initiative is a pilot project of the UN Mappers, a programme of the United Nations Global Service Centre, and has the sponsorship of the companies IVIDES DATA and TomTom, and the NGOs Humanitarian OpenStreetMap Team, GeOsm Family, and Geospatial Girls and Kids. You can read a prospectus of the UN Mappers Chapters Programme, the umbrella of the local initiatives.
• JDL09Organic, in a diary entry, presented a collection of Android apps for mobile mapping, including StreetComplete, Every Door, and MapComplete. The post provides a practical overview of their use cases and differences for efficient mapping on the go.
• juminet provided an overview of mapping photovoltaic installations in Wallonia and explains the correct usage of tags such as power=plant and power=generator. The analysis identifies several thousand mapped installations while highlighting gaps, especially in smaller setups.
• mbuege shared his experience capturing 360° imagery for Panoramax and has created a wiki page with tips on equipment and workflows. The guide is intended to be expanded and improved collaboratively by the community.
• watson reported ► on the discovery of a previously unmapped island in the Weddell Sea, which is now being discussed and mapped in OpenStreetMap. The community is debating the correct representation and positioning, as the feature is gradually added to maps and datasets.

Events

• Around 100 students at Brigham Young University took part in a mapathon to contribute OpenStreetMap data for humanitarian purposes. During the event, more than 13,000 features were mapped, mainly in regions such as South Africa and Myanmar.
• The organisers of State of the Map 2026 in Paris have opened their call for presentations, workshops, and panels, with a submission deadline of 27 April 2026. Contributions are invited across topics such as mapping, software development, community, and data analysis.
• Manuel is offering ► a workshop on the JOSM editor at the Graz Linux Days 2026 on Saturday 2 May, which will teach beginner and advanced users how to edit OpenStreetMap data. While using practical examples and exercises, the participants will learn how to work efficiently and error-free with the editor.

OSM research

• HeiGIT and the Federal Agency for Cartography and Geodesy have investigated how OSM data quality affects routing outcomes. Thirty city-to-city routes were computed across several countries and benchmarked against Google Maps, Bing, Apple Maps, and Graphhopper using two criteria: distance and travel time.

Maps

• ^[1] L_J_R presented, via their OSM user diary, Strado, a web map that scores neighbourhoods across 50 European cities using OpenStreetMap data. Based on around 78 million POIs, it uses an H3 grid to analyse liveability and activity. There is also a city dashboard where you can browse all cities with their neighbourhood rankings.
• Frederik Ramm reported that Geofabrik now provides GeoPackage files alongside shapefiles, combining multiple layers into a single file. The datasets have also been expanded with new content such as administrative boundaries, protected areas, and additional POIs previously only available in paid datasets.
• Users can explore the application built using python-maps-vis that visualises river basins and watersheds across North and South America on an interactive map.

OSM in action

• Carlos Carrasco, the developer behind NIMBY Rails, a game with a railway design simulator that allows users to plan and build railway networks on real-world geography, has announced a shift away from the proprietary file format in favour of open standards, specifically Protomaps PMTiles and MapLibre MLT. The change is intended to make it easier for players to generate their own in-game map files.
• The OSRM project noticed that both OSRM and the OpenStreetMap project are properly credited in the Tesla Model Y owner’s manual.

Open Data

• HeiGIT introduced OpenAccessLens, a platform analysing global accessibility to healthcare and education based on OpenStreetMap and openrouteservice. The open dataset is intended to support research, humanitarian work, and policy-making.

Software

• Craig announced that Wandrer, an OpenStreetMap-data-based exploration game, now has ‘100% routing’ tools which lets you create in one go a route covering every road in an area.
• Tobias Knerr introduced, on the OSM Community forum, the OSM2World Object Viewer, a viewer that allows inspection of individual OSM objects in 3D, such as buildings, highways, waterslides, German traffic signs, and more than 200 other types of OSM objects. It fully supports Simple 3D Buildings, fetches up-to-date data on demand, and even enables local tag edits with instant visual feedback.
• The project OpenCourseMaps has introduced a web-based editor designed specifically for mapping golf courses in OpenStreetMap, thus reducing the complexity of doing this in a general purpose editor. It aims to engage golfers in detailed mapping of features such as fairways, greens, and bunkers while ensuring correct OSM tagging and geometry. The YouTube video explains how to map with the editor.
• Michael Reichert presented Wamy (an acronym for ‘Where are my ways’), a prototype of a web map which reconstructs and maps the ways deleted from OpenStreetMap in Germany, Austria, and Switzerland. It displays geometries of ways removed since 12 September 2012 (when OpenStreetMap changed its licence to the Open Data Commons Open Database Licence). It is helping to reveal changes in the dataset and potential conflicts around path usage. You can read more in the ‘About’ section.

Programming

• Sander de Snaijer presented ‘Map Gesture Controls’, browser-native hand gesture controls for OpenLayers, powered by MediaPipe and without a backend. A JavaScript library enables gesture-based interactions for web maps and the project enhances map usability with more intuitive controls, especially for touch and trackpad input. The source is available from the GitHub project map-gesture-controls, under a MIT licence.
• Marcos Dione described, in his OSM user diary, a small Python 3 script that scans a local osm2pgsql database for rare and likely wrong tag values and opens the affected objects in the editor for manual review. The approach deliberately targets the long tail of uncommon errors, so corrections can be made directly and in a controlled way. The errors include typos, street names instead of type, and some others.
• Ralph Straumann described on Spatialists – geospatial news, a demo workflow by Riccardo Klinger, which converts OpenStreetMap street network data into vector tiles using GDAL/OGR and integrates them into ArcGIS Enterprise. The pipeline runs on Kubernetes in the ArcGIS Notebook Server. You can read the tutorial on LinkedIn.
• The new iD tagging schema release v6.16.0 includes 34 new icons, 4 new presets (shop=piercing, amenity=kitchen, natural=arete, advertising=sign), new matching fields in various presets, fixes of bad text, avoidance of iD issues, and more.
• Tom Hodson outlined his experience of compiling and running a local copy of the Overpass API on a Mac.

Releases

• Kevin Ratzel introduced Map2Go, a new OpenStreetMap editor for iOS, designed to simplify on-site data collection through suggestions and favourites. The app is currently in early beta and available for testing via TestFlight.
• The OSM-based web map Cartes.app is now available in English (in addition to the original French version), as announced by maelito2000 in the OSM Community forum. Further translations are planned, while current performance issues are caused by the overloaded Overpass instances.
• The DBeaver Community Release 26.0.2 has fixed the ‘access blocked’ error in Spatial Viewer when loading OpenStreetMap tiles and provided other improvements. It is now using a local web server and your firewall might ask you to accept the connection to this server. DBeaver is a free, open-source database management tool which connects to PostgreSQL/PostGIS and other geospatial (and non-geospatial) databases, including MariaDB, DuckDB, MySQL, and SQL Server.
• Zeke Farwell announced that the josm-strava-heatmap version 6 updates the extension to work with Strava’s current heatmap site and cookie requirements for imagery access. Unfortunately this means support for iD editor had to be removed, but you can use the julcnx/strava-heatmap-extension instead, which was designed to be used with iD.
• Rphyrin announced the release of Altilunium LocationPad v26.4.6, introducing several features aimed at addressing personal pain points encountered in the past. This lightweight web app has its focus on mapping, labelling, and revisiting meaningful places on an OpenStreetMap-based map. Designed for quick place logging, personal mapping, and spatial note-taking without accounts. The source is available on GitHub.
• Tracestrack has introduced Tracesmap, a new iOS app for recording and uploading GNSS traces to OpenStreetMap. The app supports multiple map styles and aims to contribute to improving OSM data quality.
• Pablo Brasero reported on the OSM Community forum (in posts [1] and [2]) about the multiple updates to the OpenStreetMap.org website made in March 2026, including UI refinements, better small-screen layouts, and upgrade of iD to version 2.39.5. They have also introduced anti-abuse measures such as Cloudflare Turnstile on sign up and laid groundwork for a future notification system.
• Zkir released version 2.0 of their UrbanEye3D, a JOSM plugin, which significantly improves 3D rendering of OSM data directly within the editor. New features include a 2D ground layer, tree visualisation, and improved background processing for large datasets.

Did you know that …

• … there is a special offer for AI companies: in exchange for a modest donation to the OpenStreetMap project, the donor company will receive a direct download link to OSM data in a machine-friendly format. For a larger donation, the OpenStreetMap Ops Team will provide the full history data via a fresh weekly torrent download, under the ODbL licence.

OSM in the media

• Arshak Ahamed wrote about how the delivery company they work for in Oman has replaced Google Maps with OSM-based services, in order to stop paying $8,000 a month.
• In a blog post, PeopleForBikes described how mapathons help update bicycle infrastructure in OpenStreetMap and improve the accuracy of their City Ratings. Around 60 participants from North America have learned how to use iD and JOSM to map bike lanes, speed limits, and key destinations.

Other “geo” things

• Jet Lag: The Game is a travel competition video series by Wendover Productions channel. Every season is built around a game format that is tailored to its filming location, while taking into account regional geography and available modes of transportation. The challenges vary widely, including tasks such as claiming territories across countries or continents, circumnavigating the globe by air, playing large-scale tag, racing between a country’s northernmost and southernmost points, and staging cross-country games of hide-and-seek, among others.
• Jake Godin reported that the access to open source visuals of the current Iran conflict, which has spread to many parts of the Middle East, continues to be sporadic. In past conflicts satellite imagery has provided a vital overview of potential damage to infrastructure, but nowadays imagery from commercial providers is becoming increasingly restricted and expensive. After the war in Gaza (began in 2023), Bellingcat introduced a free tool authored by University College London lecturer and Bellingcat contributor, Ollie Ballinger, that was able to estimate the number of damaged buildings in a given area. Bellingcat is now introducing an updated version of the open source tool, the Iran Conflict Damage Proxy Map, focused on destruction in Iran and the wider Gulf region, which can be freely accessed.

Upcoming Events

Country	Where	Venue	What	When
	Berlin	Wikimedia e.V. Tempelhofer Ufer 23-24,10963 Berlin	OSM Hackweekend Berlin-Brandenburg 04/2026	2026-04-11 – 2026-04-12
		Armadale Park Cafe	Social Mapping Sunday: Armadale Train Station	2026-04-12
	Milano		Editathon e mapathon alla Milano Marathon 2026	2026-04-12
	Antwerpen		Camera’s in kaart brengen	2026-04-12
	København	Cafe Bevar’s	OSMmapperCPH	2026-04-12
	Meerut	Haldiram’s, Garh Road, Meerut	OSM Delhi Mapping Party No.28 (Meerut)	2026-04-12
			Missing Maps : Mapathon en ligne – CartONG [fr]	2026-04-13
	Grenoble	La Turbine	Atelier d’avril 2026 du groupe local de Grenoble	2026-04-13
	臺北市	MozSpace Taipei	OpenStreetMap x Wikidata Taipei #87	2026-04-13
	Salt Lake City	Woodbine Food Hall	OSM Utah Monthly Map Night	2026-04-14
		Online	Mappy Hour OSM España	2026-04-14
	München	Echardinger Einkehr	Münchner OSM-Treffen	2026-04-14
	Hamburg	Online (Link s. Wiki)	Hamburger Mappertreffen	2026-04-14
		Oloron Sainte Marie	Une cartopartie dédiée à la mobilité durable dans les Montagnes Béarnaises	2026-04-15
		Oloron-Sainte-Marie – La Friche	Cartopartie à Oloron-Sainte-Marie – Projet SYSTOUR	2026-04-15
		MJC de Vienne	Rencontre des contributeurs de Vienne (38)	2026-04-15
			Online Mapathon von ÄRZTE OHNE GRENZEN	2026-04-15
	Karlsruhe	Chiang Mai	Stammtisch Karlsruhe	2026-04-15
	Freiburg im Breisgau	CCCFR, Adlerstr. 12a, Freiburg (Grethergelände)	OSM-Treffen Freiburg/Brsg.	2026-04-16
			OSMF Engineering Working Group meeting	2026-04-17
	Potsdam	Kellermann	Potsdamer Mappertreffen	2026-04-17
		Golem, Avane, Empoli	Mapping Day ad Empoli	2026-04-18
		Dijital Bilgi Derneği	OSM-TR Meet-Up – OSM League Pit-Stop	2026-04-18
	Chennai Corporation		Mapping Party @ Chennai	2026-04-19
	Liège	ULiège-RISE	Understanding the OpenStreetMap ecosystem	2026-04-20
			Missing Maps London: (Online) Mid-Month Mapathon [eng]	2026-04-21
	Lyon	Tubà	Réunion du groupe local de Lyon	2026-04-21
	Chemnitz	Kaffeesatz, Chemnitz	OSM-Stammtisch Chemnitz	2026-04-21
	Derby	The Brunswick, Railway Terrace, Derby	East Midlands pub meet-up	2026-04-21
	Bonn	Dotty’s	199. OSM-Stammtisch Bonn	2026-04-21
	City of London	The Globe pub, Moorgate	London pub meet-up	2026-04-21
		Online	Lüneburger Mappertreffen (online)	2026-04-21
	Richmond	Richmond, VA USA	Capital One TPM Summit Global Mapathon	2026-04-23
	Bratislava	Prírodovedecká fakulta UK Bratislava	Missing Maps mapathon Bratislava #13	2026-04-23
	Richmond	Virtual	MapRVA Virtual Map & Yap with LaToya Gray-Sparks, VA DHR	2026-04-23
	Tours	Étape 84	Rencontre locale Touraine	2026-04-23
	Catania	Verso Coffice	Modifichiamo Wiki e OSM insieme!	2026-04-23
	Rapperswil-Jona	OST RJ See-Gebäude 6, Rapperswil (SG)	18. Mapathon & Mapping Party Rapperswil 2026	2026-04-24
		Pinneberg	Hamburger Mapping-Spaziergang (in Pinneberg)	2026-04-25
	Mumbai		OSM Mumbai Mapping Party No.9 (Central Line)	2026-04-25
			B of A – EC AM’s Mapathon -Global Service Month	2026-04-27
	Brno	Kamenice 753/5, Brno, Kamenice 753/5, Brno	Dubnový Missing Maps mapathon na Ústavu botaniky a zoologie	2026-04-27
			Missing Maps : Mapathon en ligne – CartONG [fr]	2026-04-27

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 MatthiasMatthias, Raquel IVIDES DATA, Strubbl, Andrew Davidson, barefootstache, derFred, izen57, mcliquid, s8321414.
We welcome link suggestions for the next issue via this form and look forward to your contributions.

The problem

I’ve been creating and serving web-based maps such as this one for some time. That’s based on raster tiles, and an osm2pgsql database is used to store the data that the tiles are created from, on demand as a request to view a tile is made.

For various reasons I wanted to also create a similar map using vector tiles. With vector tiles what is sent to the client (such as a web browser) is not lots of small pictures that the client stitches together, but instead larger chunks of data, still geographically separated. The client then creates the map itself based on the style that it has been told to show the data in, combined with the data itself.

I’d noticed that the vector maps that I was displaying were sometimes slow to load, especially at some lower zoom levels such as vector zoom 8. Note that vector zoom levels are one less than raster zoom levels, so vector 8 is raster 9.

This diary entry describes what I did to mitigate the problem (mostly over a year ago now - it’s taken me a while to get around to writing this!).

For info, also see similar work elsewhere, such as in OpenHistoricalMap.

The schema and the style

Often with OSM raster tile styles, what is in the osm2pgsql database is a selection of raw OSM keys, and the map style then chooses which of those to show. My raster style wasn’t really like that; it made significant use of lua scripts (called both on initial database load and on all subsequent updates) to convert OSM data into a state in the database in which it was easy to display.

This approach transferred really well to vector tiles. I documented the schema, and much of the code is actually shared between raster and vector. Once an OSM item has been transformed the raster code adds it to a database and the vector code creates vector tiles.

Vector tiles

The individual vector tiles can be seen in debug here. As you zoom in you’ll see that the squares get smaller, as far as vector zoom 14. Those are the highest zoom vector tiles created and things displayed at zoom levels > 14 are actually stored in zoom 14 tiles but only displayed later.

I’m creating vector tiles with tilemaker. That creates a big “.mbtiles” file which I copy to a directory under a web server.

/var/www/html/vector/sve01: (29 GiB available)
drwxr-xr-x 2 root root       4096 Mar 14 17:31 .
drwxr-xr-x 4 root root       4096 Mar 28 01:04 ..
-rw-r--r-- 1 root root 6203834368 Apr 10 01:58 tilemaker_sve01.mbtiles

I’m using Apache as a web server and I’m using a module mod_mbtiles to allow individual vector tiles to be extracted from that and sent to a client. It would make no sense to send (in this case) 6GB of Britain and Ireland data to a client that only wants to show a map of a small part of Lincolnshire.

Why are things sometimes slow?

A large vector tile has to be extracted from the large .mbtiles file, and sent to the client. The larger this is, the longer it will take, due to network speed issues among others.

There’s also an impact on the client - it potentially has to chew through a large amount of data to get to the data that it wants to display.

I tested various scenarios - fast vs slow clients, small vs large MapLibre .json styles (based on the same Schema) and omitting data from tiles to make them just smaller. Of all of those, the most important factor was the size of the vector tiles themselves, so the challenge became “how can I minimise vector tile size at certin low zoom levels”.

I initially looked at vector zoom 8, because it was quite slow, and was also used as a landing page zoom

Looking at Apache logs

An example entry in Apache’s access.log file looks like this:

anipaddress - - [11/Apr/2026:00:36:36 +0100] "GET /sve01/7/63/41.pbf HTTP/1.1" 200 1016621 "https://map.atownsend.org.uk/vector/index.html" "Mozilla/5.0 (X11; Linux x86_64; rv:140.0) Gecko/20100101 Firefox/140.0"

Here the path to the vector tile can be clearly seen. The “200” is the code for “yes that request was served successfully”, and the “1016621” is the size of the data returned. The browser had requested https://map.atownsend.org.uk/vector/index_svwd01.html#7/51.407/0.178 , and that zoom 7 tile contains most of southern England.

In terms of tile size, what I saw before any optimization in March 2025 was this:

zoom  a big example tile
0     19490
1     19076
2     8468
3     5442
4     69416
5     108941
6     735912
7     810916
8     1455666
9     2065707
10    1060757
11    562848
12    532770
13    343290
14    190211

The various parts of the problem

Clearly I needed to reduce the amount of data contained in a zoom 8 tile, but how? Why was it so big in the first place?

The vector style contains X because someone might want to show it.

I had originally thought of the schema as being one that could support multiple styles. There were a couple of places where I was writing things into tiles because I thought that I (or some other consumer) might want to create something to show it later. This was the same approach as I’d used for the raster tiles database - there information is stored in the database to track changes to certain objects but isn’t used for display.

In order to reduce vector tile size I removed places where I’d done this on vector.

All X is displayed at zoom Y

This was the standard approach I’d used for raster tiles (inherited from early OSM Carto versions). The cost on raster wasn’t especially noticeable, because on raster it only affected render time, and if an old tile existed that was always sent to the user first (or, if zooming in, an overzoomed lower-zoom tile). Where previous tiles existed users weren’t faced with blank space, and the CPU effort to generate a new tile was on the server, not on their device.

On vector, the architecture means that this is no longer true. A large and complicated vector tile has a direct impact on the client, and the user waiting for a map has to wait while their client creates a map from it.

A challenge is that some features may be either very large or very small. If you look here you can see that some natural parks / nature reserves are large enough to be worth showing at the zoom level (but many aren’t), and similarly some lakes are large enough the show (mainly in Ireland) but that the smaller English and Welsh lakes aren’t.

In the code, the water logic can be seen here. That then calls set_way_area_name_and_fill_minzoom_sea to decide which vector tiles to actually write details to. That in turn honours sqkm values for point features representing “large woolly areas” by using set_sqkm_name_minzoom.

If you zoom in here you’ll see initially just Irish lakes, then the largest Welsh and English ones, and eventually the smallest.

This approach allows some previously unshown large features to appear. Fir example, the large military area off Essex has been added to vector at relatively low cost (there are few of that size) but did not appear on raster.

Finding out how many of X of size Y there are

I have a rendering database for use for raster tiles for the same map style, and it can be useful for queries like this:

gis=> select osm_id,name,way_area from planet_osm_polygon where "natural" = 'water' order by way_area desc;

The top values are as expected:

   osm_id   |                              name                              |   way_area    
------------+----------------------------------------------------------------+---------------
   -1121118 | Lough Neagh                                                    |   1.13296e+09
    -189915 | Lough Corrib - Loch Coirib                                     | 4.6095802e+08
     -12889 | Lough Derg                                                     |   3.21772e+08

and if we look at it the other way around:

gis=> select osm_id,name,way_area from planet_osm_polygon where "natural" = 'water' and name!='' order by way_area asc;

   osm_id   |                              name                              |   way_area    
------------+----------------------------------------------------------------+---------------
 1303491300 | Porthmadog Harbour                                             |      0.010894
  304781034 | Rainwater Collection Butt                                      |       1.12869
  304780098 | Rainwater Collection Butt                                      |       1.12869
  304781037 | Rainwater Collection Butt                                      |       1.12869
  304781038 | Rainwater Collection Butt                                      |       1.12869
  304781033 | Rainwater Collection Butt                                      |       1.12869
  304781035 | Rainwater Collection Butt                                      |       1.12869
  304781036 | Rainwater Collection Butt                                      |       1.12869
  969325744 | Well                                                           |       1.62326
 1449480418 | Ditch of Bert                                                  |       1.67907
  728196775 | 130                                                            |       1.98514

For info, the first of those seems to be a bit of extreme “tagging for the renderer”. The “Rainwater Collection Butts” are “reservoirs”(!) on some allotments and “Ditch of Bert” is a school pond.

The raster database “way_area” is not the same value as Tilemaker’s vector one, but it is still useful.

Results of this optimisation

Before, the largest vector zoom 8 tile was 1455666. Afterwards, it was reduced to 729085, around 50% of the previous size. Success!

A worked example (in 2026)

In order to come up with more data for this diary entry, I wrote a simple script to analyse Apache logs and report on the largest tile at each zoom level. I then loaded only “Greater London” locally, in order to create a baseline to test against. Tile sizes were:

129951    6
281487    7
389658    8
2115753   9
1881853  10
3541994  11
1686270  12
802204   13
492326   14

Note that some low zoom tiles show much more than just the loaded area and so are artificially smaller; but the same date will be used for subsequent tests meaning that differences are relevant,

One obvious difference is the jump in size at vector zoom 11. That corresponds to where buildings are first drawn. To see if that is coincidence, let’s move buildings to vector zoom 12 as a test:

129719   6
282138   7
390274   8
2117479  9
1884428  10
880557   11
1686348  12
802561   13
492375   14

So that’s a big difference, and not a coincidence.

Next, how to look at building sizes? Let’s load Greater London into a raster database and have a look at way_area there. Here are some examples:

   osm_id   |                                         name                                         | way_area
------------+--------------------------------------------------------------------------------------+----------
   18926167 | Dagenham Engine Plant                                                                |   463567
   -1895281 | The O2                                                                               |   218893
  200652378 | Brent Cross Shopping Centre                                                          |   110867
  357278392 | Sainsbury's                                                                          |  49090.2
  227053396 | Wanis Cash and Carry                                                                 |  25921.4
   30327519 | Barking Bus Garage                                                                   |  12756.5

Using MapLibre debug it’s easy to see the vector way_area corresponding to these places - zoom in until the label is shown, and way_area is an attribute of the label in the style.

I want to include the largest buildings only in zoom 11 vector tiles, more at z12 and z13, and everything at z14. I experimented with values until I was happy with both the reduction in tile size and the visual results. The logic I ended up with was this:

if ( passedt.way_area > 5000 ) then
    MinZoom( 11 )
else
    if ( passedt.way_area > 2500 ) then
        MinZoom( 12 )
    else
        if ( passedt.way_area > 1250 ) then
            MinZoom( 13 )
        else
            MinZoom( 14 )
        end
    end
end

and the results?

129588    6
281145    7
389723    8
2115639   9
1882556  10  100%
898182   11   25%
726818   12   43%
552760   13   69%
492121   14  100%

That’s a significant reduction in tile size. Arguably zooms 11 and 12 are more usable because they’re not cluttered with lots of very small buildings

What next?

Clearly there’s more work to do, both regards to “tile size” and legibility. Zooms 9 and 10 are pretty crowded in London and the tertiary colour (which first appears there) really doesn’t work, especially over some types of landuse.

The Beginning – Discovering JOSM..

I never imagined my mapping journey would reach this point in time. I would like to share with you my experience, which carried both doubts and excitement for my team and me—the thrill of learning Java OpenStreetMap (JOSM) and climbing the staircases that led to building victories in the Africa Map Cup 2026 Tournament. My name is Alvin Andrew Barugahara, also known as AlvinB (OSM name), a student from a mapping community in Uganda called Spatial Mappers at Ndejje University. I had always heard of JOSM and its simplicity in mapping OSM tasks. Back then, I was just a beginner mapper using iD editor, which was the default platform. It wasn’t bad, but it required constant internet access and had a small working window with few shortcuts, making mapping slow. My captain, Aikiriza Justus (OSM name), had a vision of teaching us how to use JOSM and become “advanced mappers.” He guided and pushed us beyond our limits through various Google meetings, preparing us for the Africa Map Cup 2026, which began on 7th February 2026. “Stay tuned for the next part of my Africa Map Cup journey…”

Solar Farms

Looking into getting a gist for where there are solar farm setups both on land and in water (lakes , ponds ) etc

So the John Muir Way has been open since the 21st of April. This long distance route is a Coast to Coast route between Helensburgh in the West—from where John Muir set off to the United States where he inspired the conservation movement and the creation of its national parks—to Dunbar on the East Coast where he was born and grew up.

We’ve covered most of the route in OpenStreetMap for a while. But until recently we’ve had a tiny gap missing. I was trying to figure out getting over to do it when I saw Martin McMahon had filled it in with a 9-mile walk between train stations—great effort!

twitter: to map that gap took 2 trains 1 to Helensburgh a 9 miles walk then train from Balloch. Great day

So with some not insignificant effort, we now have the complete route mapped. These can easily be seen by looking at a raw view of either the walking route or the cycling route on OpenStreetMap.

But where OSM comes into its own is the ability to actually do things with the data, so to kick things off I’ve created a set of GPX files of the route. These contain the full walking or cycling route and are suitable to be loaded into your GPS or phone app as aids to navigating the route.

• john_muir_way_cycling.gpx
• john_muir_way_walking.gpx

Map wise, as always I’m disappointed to see the otherwise very nice John Muir Way website using Google Maps rather than an OpenStreetMap based map:

There are also tools such as Relation Analyser. Interestingly this shows cycling distance as 206km and the walking distance as 213km while the route is officially 215 km (I guess they rounded up).

So almost as often as I post, I rewrite the site. This time I have switched it to Octopress. This is the 3rd blogging engine, I’ve used

I don’t get enough hits to justify the performance need of a static site, but it has the advantage of being one less wordpress site to maintain, and for me writting posts using markdown in vim is a definite win.

I have also taken the oportunity to switch to a small cluster I’ve setup using ByteMark’s BigV

Also a change, the code for this site is all on github. The commit history provides a nice history of the work and changes I’ve made to the standard Octopress site. This is largely in area’s of the category handling, and removing the banner. I may base some future posts on this.

Below I will outline improvements for data interoperability regarding Wilderness Study Areas in the United States: https://en.wikipedia.org/wiki/Wilderness_study_area

OpenStreetMap tagging:

• Main article: osm.wiki/United_States/Public_lands#Guidelines_for_tagging_conservation_areas)

Wikidata identifiers:

• Instance of: Wilderness study area
• Authority: BLM/USFS/etc.
• Inception
• Coordinates
• Described by source
• Area
• Official website
• Recreation.gov Gateway
• OSM Relation

Wikimedia Commons

• Wikidata Infobox template: {{Wikidata Infobox

  qid=}}

• Images
• Locator Maps
• PDFs of wilderness plan/study documents

A few days ago, I asked the community about converting general GIS polygons into OSM multipolygon relations. I’ve searched online but haven’t found a workflow that fits my needs. Specifically, I am looking for a way to handle three different levels of administrative boundaries where adjacent areas share a single boundary line connected via a relation.

My question on the OSM forum is still awaiting a solution: Link

However, someone from my local community mentioned that what I’m looking for is “topology.” While that is a broad GIS term, they clarified that TopoJSON is a specific format designed for this. There are many converters available to turn GeoJSON into TopoJSON.

Interestingly, I found that someone opened a ticket for a TopoJSON converter in JOSM back in 2020, but it hasn’t received a response yet: Link

I’m planning to update and expand the administrative boundaries for Bali in OSM. I’ve already prepared the multipolygons for admin_level 5, 6, and 7 using single shared ways for efficiency. By leveraging Google Sheets, I’ve also compiled a comprehensive list of Wikidata, Wikipedia links, and multilingual names to better serve Bali’s international profile.

However, the conflation process is proving to be a challenge. The existing data is quite a “nightmare” to clean up; many roads and waterways are currently shared with administrative relations, and landuse or natural features are glued to the boundaries. Time to start untangling!

O víkendu jsem se vydal na malý výlet vlakem. Nastoupil jsem do vozu GW Train, který mne vezl až do Horní Plané u Lipna. Jedu s tímto dopravcem poprvé a je to všechno v pohodě. Těším se na vycházku a výstup na rozhlednu Dobrá voda.

Posadím se a hned si všimnu, že na stěně vozu je uchycena široká obrazovka infopanelu. Ukazuje aktuální stanici a v druhé části obrazovky je vyobrazena mapa s pohybujícím se bodem na trati.

Vlak projíždějící Českým Krumlovem, foto Aktron, CC BY-SA 4.0

Ani nemusím jít blíž, abych rozeznal, že ta mapa je OpenStreetMap a že mě toto malé objevení udělalo radost. Je to jedna z mnoha praktických použití mapy, která nemusí být jen na počítači, nebo v mobilu.

Při výletu po Horní Plané si všímám dalších nových detailů a zajímavostí ve městě. Horní Planou jsem před časem mapoval. Teď si ji konečně prohlížím naživo.

Večer když dojedu domů se vracím k mapě a doplňuji několik drobností, které ještě na mapě nejsou. Těším se že toto léto uvidím spoustu takových míst.

Memetakan batas administrasi di Indonesia bisa jadi cukup rumit, terutama saat menghadapi nama wilayah yang serupa. Berikut adalah alur kerja (workflow) sederhana saya dalam menyiapkan data tersebut:

1. Sumber Data

Pertama, unduh data spasial resmi dari Peta Rupa Bumi oleh Badan Informasi Geospasial (BIG). Data ini berfungsi sebagai sumber geometri utama.

2. Ekstraksi Titik Lokasi (Place Nodes)

Karena data sumber berbentuk poligon, saya menggunakan QGIS untuk mengekstrak titik tengah (centroid). Titik-titik ini penting untuk membuat tag place=* yang mewakili pusat dari tiap wilayah administrasi.

3. Pentingnya Kode Kemendagri

Poligon tersebut mencakup kode referensi Kemendagri. Kode ini sangat vital untuk:

• Konflasi: Memastikan data cocok dengan set data lainnya.

• Identifikasi: Banyak desa (admin_level 7 atau 8) memiliki nama yang sama. Kode ini membantu membedakannya dalam satu Kabupaten atau Provinsi.

4. Pengayaan Metadata

Menggunakan alat spreadsheet dan teknik konflasi, saya mencocokkan data untuk menambahkan:

• Tag wikidata dan wikipedia.

• Nama dalam berbagai bahasa (name:en, dsb).

5. Pengolahan Geometri

Sesuai dengan praktik terbaik (best practices) di OSM, saya mengubah poligon menjadi garis terpisah (polylines).

• Hal ini memungkinkan wilayah yang bertetangga untuk berbagi satu garis batas yang sama melalui relasi multipolygon.

• Setelah dikonversi, saya mengekspor hasilnya dalam format .geojson.

6. Pengetagan Akhir (Final Tagging)

Terakhir, saya menggunakan titik lokasi (place nodes) yang telah diekstrak sebelumnya untuk menyalin dan menempelkan tag yang relevan ke dalam relasi multipolygon baru di editor OSM.

Mapping administrative boundaries in Indonesia can tricky especially when dealing with overlapping names. Here is my simplified workflow for preparing this data:

1. Data Sourcing

First, download the official spatial data from Peta Rupa Bumi by Badan Informasi Geospasial. This serves as the primary geometry source.

2. Extracting Place Nodes

Since the source data is in polygon format, I use QGIS to extract the centroids (points). These points are essential for creating the place=* tags that represent the center of each administrative area.

3. The Importance of Kemendagri Codes

The polygons include Kemendagri reference codes. These are vital for:

• Conflation: Ensuring data matches across different sets.

• Identification: Many villages (admin_level 7 or 8) share the same name. The code helps distinguish them within a Regency or Province.

4. Enriching Metadata

Using spreadsheet tools and conflation techniques, I cross-reference the data to add:

• wikidata and wikipedia tags.

• Multilingual names (name:en, etc.).

5. Geometry Processing

To follow OSM best practices, I convert the polygons into independent ways (polylines).

• This allows adjacent areas to share a single boundary line via a multipolygon relation.

• Once converted, I export the result as a .geojson file.

6. Final Tagging

Finally, I use the previously extracted place nodes to quickly copy and paste the relevant tags into the new multipolygon relations in my OSM editor.

Comme ailleurs dans le monde, les installations photovoltaïques se multiplient en Belgique. En 2022, 68 ans après les débuts du photovoltaïque, la capacité mondiale en panneaux photovoltaïques atteignait son premier TW. Il n’aura fallu que 2 ans pour que 1 TW supplémentaire soit ajouté en termes de capacité mondiale en 2024. Et le rythme s’accélère encore.

En Belgique, d’après electricitymaps, il y aurait une capacité installée de 11.5 GW, soit environ 1 kW par habitant, une puissance à peu près équivalente à la charge électrique moyenne du pays. Toutefois, difficile de trouver des chiffres précis, à jour et encore moins la répartition spatiale de ces installations.

Récemment, je vois passer l’info que l’équipe du géoportail wallon travaille justement sur un inventaires des installations photovoltaïques au sol. Du coup, j’en ai profité cette semaine de faire un tour des centrales solaires de Wallonie (la moitié sud de la Belgique) enregistrées dans OSM, en vérifiant les données et les complétant. J’ai même découvert et ajouté quelques centrales photovoltaïques.

Mais comment les ajouter dans OSM ?

Il y a une très grande diversité d’installation photovoltaïques: depuis le panneau isolé sur un balcon ou la toiture d’une maison, jusqu’à la centrale solaire photovoltaïque de plusieurs MW, composé de milliers de panneaux. Dans OSM, on distingue d’une part les centrales solaires et d’autre part les panneaux solaires. Les centrales solaires photovoltaïques sont constituées d’un ensemble de panneaux, tandis que les petites installations sont composés uniquement de panneaux.

Dans OSM, on ajoute une centrale solaire avec les tags “power=plant” + “plant:source=solar” + “plant:method=photovoltaic” + “plant:output:electricity=*” (voir le wiki osm.wiki/Tag%3Aplant%3Asource%3Dsolar). On dessine généralement une surface qui englobe les panneaux, qui sont plus ou moins espacés selon les cas, et uniquement pour les “grosses” installations.

Pour les panneaux solaires (ou ensemble de panneaux), on utilise les tags “power=generator” + “generator:source”=”solar” + “generator:method”=”photovoltaic” + “generator:output:electricity=*” (voir osm.wiki/Tag%3Agenerator%3Asource%3Dsolar). On peut y ajouter le tag (redondant mais bon)”generator:type=solar_photovoltaic_panel” ou encore le nombre de panneaux (“generator:solar:modules=*”) et le type de montage/localisation (location=*). L’éditeur JOSM facilite énormément l’ajout des panneaux, surtout dans les centrales solaires, en copiant-collant les panneaux d’un bloc à l’autre.

À partir de quand considérer qu’un ensemble de panneaux est une centrale solaire? D’après le wiki, à partir d’une installation de 1 MW (à peu près 1600 panneaux de 600W!), mais dans les faits, des installations de moindre puissance sont caractérisées comme des centrales solaires en Belgique (“power=plant”).

Combien de centrales et panneaux en Wallonie?

En attendant l’inventaire du géoportail wallon, voilà un aperçu de la situation dans OpenStreetMap en Wallonie.

• Centrales solaires: On en compte 41 avec cette requête. Après analyse dans QGIS, leur surface cumulée est de 203 ha, la plus grande faisant 37 ha. La plupart sont complétées par une cartographie détaillée des ensembles de panneaux.

• Panneaux solaires (ou plutôt ensemble de panneaux): à la fois représentés par une surface ou par un point, on en compte à peu près 7200 en Wallonie, couvrant une surface totale de 196 ha (requête). Attention, ce nombre est en-dessous de la réalité, puisqu’une petite partie seulement du territoire est cartographié en ce qui concerne les panneaux des installations résidentielles, en fonction de l’activité des contributeurs locaux.

• Panneaux solaires au sol (en excluant ceux présent sur les batiments): 1992, sur une surface de 133 ha. Ce sont les grandes installations et des installations moyennes, mais très variables, entre les 2-3 panneaux mis dans un jardin résidentiel, et les centaines de panneaux d’une installation industrielle (qui pourrait être caractérisé comme une centrale).

• Panneaux solaires dans les centrales: 1115 objets couvrant 95 ha (à peu près la moitié de la surface des centrales, principalement parce qu’il manque la cartographie détaillée des panneaux dans certaines grandes centrales très récentes)

• Deux ensembles de panneaux seulement sont indiqués comme flottant sur l’eau (tags “location”=’overwater’ ou “floating”=’yes’).

• Enfin, un truc amusant, il existe aussi un tag pour les tracker solaires, des installations capables de suivre la course du soleil en suivant sa direction et son inclinaison. Un très bon moyen de maximiser le rendement des panneaux. On en compte une quarantaine seulement, un nombre probablement sous-évalué.

Pour information, un des meilleurs rendus cartographique de ces installations est l’application openinframap, avec notamment une carte de chaleur (heatmap) des installations photovoltaïques.

N’hésitez pas à compléter les installations photovoltaïques près de chez vous.

Happy mapping,

Люди, кто пишет в дневниках: вот, я стал картографом,..мне это всё понравилось,…ура ура ура… Большая просьба: не превращайте только карты в игру для развлечений! Не вносите правки и не присваивайте имён, если вы Лично не проводили исследования в данном районе! Надеюсь что большинство прочитавших всё-таки поймут меня.

Es macht besonders Spaß, draußen an der frischen Luft zu kartieren. Gerade jetzt, wo es wieder wärmer wird, ist das durchaus eine angenehme Art zu mappen. Doch das wäre ohne bestimmte Tools gar nicht möglich. Da dein Smartphone selbstverständlich um einiges kleiner als ein PC-Bildschirm ist, ist es wichtig, die richtigen Tools auf dem Handy zu haben, um den Überblick zu behalten und effizient arbeiten zu können. Doch welche Apps eignen sich für dich? Und überhaupt: Welche Apps gibt es da eigentlich?

1. Einsteigerfreundlich, schön und einfach: StreetComplete

Um StreetComplete kommst du nicht drumrum. Es ist einfach zu bedienen, schön gestaltet und vor allem gamifiziert. Und genau dieser zugrunde liegende spielerische Ansatz macht die App so gut. Statt die Tags manuell für Objekte einzutragen, sucht die App nach fehlenden Tags, die du dann durch die Beantwortung einer Frage hinzufügen kannst. Zudem gibt es Abzeichen, Statistiken und Rankings, die dich motivieren weiterzumachen. Meiner Meinung nach macht die App aber auch ohne diese schon süchtig genug …

2. Da geht noch mehr: SCEE (StreetComplete Expert Edition)

SCEE ist prinzipiell eine abgewandelte Version von StreetComplete. Ihr Ziel ist es, die App auch für dich als etwas fortgeschritteneren Mapper zugänglich zu machen. So lassen sich Tags anzeigen und bearbeiten, mehr Fragen zu spezielleren Tags aktivieren und diese sogar leicht modifizieren. Ich persönlich nutze dieses Tool hauptsächlich, da es für mich den besten Kompromiss zwischen Übersichtlichkeit bzw. schönem Design und tieferem Mapping bietet. Wichtig zu wissen: Du findest diese Version meist nicht im Play Store, sondern musst sie über F-Droid oder GitHub beziehen.

3. Anwender und Beitragender zugleich: OsmAnd

OsmAnd ist eine der größten OSM-basierten Kartenapps überhaupt und bietet Unmengen an Features und eine unheimliche Anpassbarkeit. So hast du auch die Möglichkeit, OpenStreetMap-Bearbeitungen direkt in der App vorzunehmen. Meiner Ansicht nach eignen sich diese Bearbeitungsmöglichkeiten aber primär für kurze, kleine Fehler in der Karte, die dir während der normalen Nutzung der App auffallen. Es ist eher ein nettes Feature, aber nennenswert, gerade deswegen, weil du einen Editor direkt in der App hast, die du eventuell sowieso schon nutzt. Denk nur daran, dein OSM-Konto in den Einstellungen zu verknüpfen, damit der Upload klappt.

4. Das absolute Monster: Vespucci

Vespucci ist wohl die umfangreichste Option überhaupt. Die App ist nun schon 17 Jahre alt und hat so ziemlich alles, was du brauchst, um OSM-Bearbeitungen jeglicher Art vorzunehmen – quasi der JOSM für die Hosentasche. Ich nutze es vor allem, weil es anders als SCEE und andere Tools die Möglichkeit bietet, Linien und Polygone zu erstellen. Dies ist praktisch, wenn du mal eine lange Sitzbank als Linie oder einen größeren Fahrradparkplatz als Fläche eintragen möchtest. Es sei jedoch gesagt, dass es eine gewisse Einarbeitungszeit erfordert und für dich eventuell nicht ganz so intuitiv ist, da man hier auch leichter mal versehentlich bestehende Daten verschieben kann.

5. Ein angenehmer Mittelweg: Every Door

Every Door ist wieder etwas übersichtlicher. Hier arbeitest du in vier Kategorien: Dinge, Orte, Häuser und Notizen. In der oberen Bildschirmhälfte befindet sich dann die Karte mit – je nach aktiver Kategorie – farblichen Markierungen oder Zahlen, die in der unteren Bildschirmhälfte definiert werden. Besonders stark ist die App beim Erfassen von Ladenöffnungszeiten oder Mikromapping wie Mülleimern und Bänken. Durch das Tippen auf ein bestimmtes Objekt gelangst du dann in einen grafisch ansprechend und verständlich gestalteten Tag-Editor, der aber auch zu einer Listenansicht umgeschaltet werden kann. Ich persönlich nutze die App nicht sehr oft, da mir der Workflow in SCEE besser gefällt. Es stellt aber eine gute Alternative dar, wenn du mit SCEE nicht zufrieden bist.

6. Mappe, was dich interessiert: MapComplete

Es handelt sich erneut um eine App, die grafisch ansprechend und einsteigerfreundlich gestaltet ist. Beim Start der Anwendung wählst du zunächst eine Themenkarte aus, bei der du je nach Thema nur bestimmte Objekte bearbeitest und hinzufügst. Beim Anklicken eines POIs werden dir ähnlich wie in StreetComplete bzw. SCEE Fragen zu fehlenden Tags angezeigt. Ich persönlich finde das Konzept und die Idee sehr schön, gerade auch deswegen, weil du eigene Themenkarten erstellen kannst. Leider basiert die Android-App aber auf WebView, was die App ganz schön verlangsamt. Ein kleiner Tipp: Falls sie bei dir auch hakt, nutze sie einfach direkt im Webbrowser deines Handys und erstelle dir eine Verknüpfung auf dem Homescreen – das läuft oft flüssiger.

7. Eine simple Ergänzung: OSMfocus Reborn

Wenn du einen schnellen Blick auf alle Tags eines Objektes werfen willst, kannst du einfach schnell OSMfocus Reborn öffnen, damit siehst du direkt alle Tags von den Objekten in deiner Nähe ohne einen einzigen Klick. Wenn dir die Ansicht nicht reicht, hast du aber auch die Möglichkeit, auf ein bestimmtes Objekt zu tippen, um alle Tags in voller Länge zu sehen.

Mit diesen Tools steht deinem mobilen Mapping mit einem Android-Smartphone nichts mehr im Weg. Probiere gerne alle Tools mal durch, ich bin mir sicher, dass du bei mindestens einer hängen bleibst. Bei Fragen, Ergänzungen oder Korrekturen schreibe bitte gerne einen Kommentar.

Viel Spaß beim Kartieren!

We’ve recently added GeoPackage (gpkg) files to the download server, in addition to the shape files we’re already offering. This seems to be a popular addition; over half of the previous shape file download traffic has already migrated to the newer GeoPackage format – combining all layers in a single file, GeoPackage is more convenient than the old shape format.

But there’s more: We have updated the layer structure in the shape and GeoPackage files to include more data. You can review the details in our format specification PDF; the most important news is that the free data sets now contain an administrative area layer which was previously only available in the paid data sets*.

We’ve also added a protected areas layer and many POIs, but taken great care not to upset things too much so that people shouldn’t have to re-tool their processing chains built for previous versions of our shape files. Enjoy!

(*) Note that OSM doesn’t have a hierarchy of admin levels (i.e. city X is in county Y is in state Z) by default, and neither are boundaries clipped along the coastline. Administrative area shape files that have these extra features are available from us commercially.

🗺️ Entry 1 — Setting up JOSM & Plugins

Mapping Banjë, Albania

I started mapping the Banjë region in Albania by setting up my editing environment in JOSM.

⚙️ Setup

I configured JOSM with a set of plugins to support structured mapping and validation:

• utilsplugin2 – general productivity tools
• reltoolbox – relation and multipolygon editing
• waydownloader – working with connected geometries
• merge-overlap – cleaning overlapping features
• Relation Validation Plugin – checking data consistency
• FastDraw – faster geometry digitizing

I also explored additional plugins like contour-related tools for terrain-based mapping.

🗺️ Mapping Context

The focus area is Banjë (central Albania) — a landscape with: - Complex terrain (valleys, rivers, slopes)
- Mixed land use (forests, agriculture, settlements)
- Incomplete or inconsistent OSM coverage

🌱 Initial Observations

• Landuse classification is often fragmented or overlapping
• Boundaries between forest, farmland, and settlements are not always clear
• Many features require clean multipolygon structures
• Validation tools already highlight conflicts in relations

🎯 Next Steps

• Clean and structure landuse polygons (forest, farmland, residential)
• Resolve relation conflicts and validation errors
• Improve consistency of tagging using presets
• Start refining settlement structures and road connectivity

เลขที่ 93/324 ถนนสุขุมวิท แขวงบางจาก เขตพระโขนง กรุงเทพมหานคร 10260

So, I’ve been using Altilunium LocationPad for several of my personal projects until now. But recently, I encountered several problems.

I dabble with multiple projects at once, but this app saves everything in a single database. I want this app to be able to create several separate “canvases”, so I can manage several of my projects at once, without mixing them with other projects.

For each canvas, the data is also exportable to JSON (and can be imported back too).

And, for a better “presentation view”, I made a shortcut (Ctrl + .) to temporarily hide/show all the UI elements, focusing on maps and markers.

And sometimes, I also want to directly copy a certain marker’s coordinates. From now on, when we click a marker, the raw coordinates are also shown.

v26.4.6 : This update introduces a more flexible workspace system by allowing users to create, edit, delete, and switch between multiple “canvas” environments. Each canvas now operates with its own independent database, making it easier to separate and manage different datasets or projects. The canvas manager behavior has also been refined. When the Ctrl + . shortcut is triggered, the canvas manager will now be properly hidden to ensure a cleaner interface and avoid visual clutter during use. Interaction with markers has been improved as well. Clicking on a marker will now display its precise coordinates, providing clearer spatial information directly within the interface. Finally, data portability has been expanded. Each canvas now includes an “Export to JSON” option, allowing users to easily back up or share their data. In addition, a new “Import from JSON” feature enables users to load a JSON file into a newly created canvas, simplifying data transfer and reuse across environments.

[English] BetterIME is a JOSM plugin that automatically manages Chinese IME state based on focus context, preventing IME from intercepting keyboard shortcuts while editing the map. GitHub: https://github.com/nj-yzf/josm-BetterIME

问题背景

使用中文输入法编辑 OpenStreetMap 时，JOSM 的快捷键（如 S 选择、A 添加节点、W 提高路径精度等）经常被输入法拦截，导致快捷键失效。每次都要手动切换输入法，非常影响编辑效率。

为此我开发了 BetterIME 插件，让 JOSM 根据当前操作场景自动控制输入法状态。

功能介绍

插件将输入法控制分为三种场景：

自动切换至中文输入法： - 编辑 name、name:zh、name:zh-Hans、name:zh-Hant、alt_name、operator 标签时 - 打开 F3「搜索预设组合」对话框时

默认英文，可手动切换： - 其他文本输入框（如 Ctrl+F 查找、其他标签编辑等）

禁用输入法（快捷键正常工作）： - 地图视图、工具栏等非文本组件，Shift/Ctrl+Space 也无法意外切换至中文

此外，插件还释放了 Ctrl+Space 快捷键（JOSM 默认绑定为「搜索菜单项」），让它回归系统输入法切换功能。

首选项设置

通过 编辑 → 首选项 (F12) 打开 BetterIME 设置页，可以：

• 启用/禁用自动输入法切换（总开关）
• 启用/禁用 F3 搜索预设对话框中的中文输入法
• 启用/禁用基于标签键的自动检测
• 自定义触发中文输入法的标签键列表（支持添加、删除、重置）

所有设置即时生效，无需重启 JOSM。

安装方式

方式一：JOSM 内置插件管理器 1. 打开 编辑 → 首选项 → 插件 2. 搜索 BetterIME 3. 勾选启用，重启 JOSM

方式二：手动安装 1. 从 GitHub Releases 页面下载 BetterIME.jar：https://github.com/nj-yzf/josm-BetterIME/releases 2. 将 JAR 文件复制到 JOSM 插件目录（Windows: %APPDATA%\JOSM\plugins\） 3. 在 编辑 → 首选项 → 插件 中勾选启用，重启 JOSM

兼容性

• JOSM 19555 及以上版本
• Java 11 及以上
• 目前仅在 Windows 上测试过，macOS 和 Linux 上的输入法框架不同，可能无法正常工作，欢迎反馈测试结果

反馈

如果遇到问题或有功能建议，欢迎在 GitHub 提交 Issue：https://github.com/nj-yzf/josm-BetterIME/issues

许可证：GPL-2.0-or-later（与 JOSM 一致）

26/03/2026-01/04/2026

About us

• We made a mistake last week regarding the proposed safari service road tag. The proposed service=safari tag is to be used in combination with a highway=service tag.

Mapping

• Comments are requested on this proposal:
  • highway=service + service=safari to map dedicated service roads in safari parks.
• The following proposals are up for a vote:
  • man_made=cable_landing_station, to standardise the mapping of submarine cable landing station locations in OpenStreetMap. The tag is intended to help map this important infrastructure for international data connections more accurately (voting until 14 April 2026).
  • aerodrome:classification=*, to classify aerodromes more precisely according to their use and significance (e.g. international, regional or local) (voting until 16 April 2026).

Mapping campaigns

• The new UK Quarterly Project for Q2 2026 focuses on mapping and improving address data in OpenStreetMap. The Wiki page provides ideas, datasets, tools, and resources to support contributors.

Community

• Raquel Dezidério Souto published in her OSM user diary about a new partnership between the Virtual Institute for Sustainable Development – IVIDES.org®, the IVIDES DATA® IT consulting, and the State University of Campinas (UNICAMP, São Paulo, Brazil), which aims to develop a collaborative micromapping effort with OpenStreetMap and uMap, envolving three communities that were severely affected by the major disaster that occurred in 2023, on the Southern Coast of São Paulo.
• assanges has analysed Taiwan’s OpenStreetMap phone‑number data, highlighting inconsistent separators, missing or malformed country codes, and proposed normalising all numbers to the E.123 format for consistency reasons.
• Anne-Karoline Distel explained how they started mapping ‘hogbacks’, medieval grave markers from the 10th to 12th century, in OpenStreetMap using the tag historic=hogback. These rare objects, mainly found in northern England, are intended to be more easily identifiable through dedicated tagging.
• ^[1] Koreller shared a diary post highlighting some of the lesser-known features and keyboard shortcuts in JOSM, including parallel drawing, precise angle construction, and transferring object history. The collection demonstrates how plugins and shortcuts can enable more efficient and accurate mapping workflows.
• Marcus Jaschen, developer of bikerouter.de, talked about the development and functionalities of his BRouter-based route planner in the bike podcast Antritt.
• Christian Quest presented a proof of concept that uses Geocalib to automatically correct tilted 360° images, such as those captured by helmet-mounted cameras, and apply corrections to entire sequences. The bot has already processed tens of thousands of images, applying heuristics to propagate corrections from individual fixes to larger image sets.
• rphyrin reported on his experience of attending the OpenStreetMap Local Chapters and Communities Congress 2026, providing a resume of the questions and answers (Q&A) posed by the organisers during the meeting.
• Christoph Hormann has extended his Musaicum project, which uses high-resolution satellite data to create detailed mosaics, to include Greenland.

OpenStreetMap Foundation

• Minh Nguyễn informed mappers that the operations team has installed the DiscussionTools extension. This extension adds a number of little features to make discussions on the wiki talk pages more intuitive. The extension has releases for both the version of MediaWiki used by the OSMF, and for the latest version of MediaWiki.

Local chapter news

• The OpenStreetMap US has launched a story map competition – the State of the Map US Narrative Map Competition, inviting the global community to create map-based storytelling projects. Participants are encouraged to submit narrative-driven maps, with selected entries showcased at the State of the Map US 2026.
• The Associació Catalana de l’OpenStreetMap has applied to become an official Local Chapter of the OSM Foundation and has opened a public discussion on the OSM Community forum. Due to overlapping areas of interest, feedback is especially requested from existing Local Chapters in Spain, France, and Italy.

Events

• The organisers of the Graz Linux Days 2026 have published their full programme, featuring talks and workshops on open source and free software. The event takes place in Graz (Austria) on 10 and 11 April and will include several sessions related to OpenStreetMap and geodata.
• The University of Zaragoza is hosting a humanitarian mapathon on Tuesday 7 April in collaboration with Médecins Sans Frontières, OpenStreetMap Spain, and local mapping groups. The event will take place both in person and online as part of the regular ‘MappyHour’ sessions.
• The programme for the State of the Map US 2026 has been published. The event will be held in Madison, Wisconsin from 11 to 13 June. There is a great line-up this year with 80+ presentations covering a breadth of topics from motivating mappers, to open POI’s, to safeguarding America’s open infrastructure data, and much more.

OSM research

• A Scientific Reports study explored integrating OpenStreetMap with satellite and environmental data in a unified deep learning framework for urban analysis. OSM serves as a key geospatial layer supporting tasks such as land-use mapping, building extraction, and traffic modelling.
• HeiGIT reported that they conducted a controlled experiment to measure how humans modify AI-generated road geometries at the atomic level by using both independent and cross redundancy mapping.

Maps

• The platform Blitzortung provides an interactive map showing lightning strikes worldwide in near real time. The data comes from a non-commercial global network of around 1,800 volunteer-operated detection stations and is visualised on maps including OpenStreetMap-based layers.
• The Climate Action Navigator and Heal apps, maintained by HeiGIT, help cities assess how well urban environments support walking under hot conditions and other evaluations related to the climate change and extreme weather conditions.
• The platform Electricity Maps provides an interactive map displaying the current electricity mix, carbon intensity, and energy flows for countries in near real time. It allows users to explore where electricity comes from and how emissions and renewable shares evolve throughout the day.

OSM in action

• Steven Reid has programmed an interactive 3D visualisation of the earth directly in the browser. Users can explore global geodata and switch between different visualisations, using OpenStreetMap as one of the data sources.

Open Data

• The Instituto Geográfico Nacional – IGN (Spain) has released ► two PMTiles files for mobile app, which are available for download and using under the licence CC-BY 4.0.
• Quincy Morgan posted on LinkedIn that Pinhead, a collection of .SVG map icons, is available freely on Wikimedia and can be used in projects documented on Wikipedia or Wikidata. Pinhead is also now available in the QGIS map icons collection.

Software

• Evan Applegate posted about the experience of generating web maps with OpenFreeMap, after following a tutorial on PMTiles, created by Ben Welsh, a data journalist and editor based in New York.
• Alexandre Cavaleri’s pull request has been merged, meaning a long-distance inline skating profile will be available in brouter-web with the upcoming version 1.7.9. The profile is specifically tuned to strongly prefer smooth asphalt and avoid unpaved surfaces, based on real-world long-distance skating data.
• EoGIS, a web mapping platform maintained by Vatalysteau SAS, is now fully operational and Yann Justeau wrote ► about the micromapping, its challenges and opportunities, and some difficulties related to cartographic activities developed by small public administrations.
• Crosstalk Solutions has unveiled Project Nomad, a system designed, amongst other things, for offline navigation based on OpenStreetMap data. The project combines local routing and mapping components to enable navigation without an internet connection, for example in remote areas or emergency situations.
• François Lacombe presented the Gespot , a Web map which is aimed at mapping light poles and electric infrastructure, at Rencontres OpenStreetMap and territoires, held in Brest on 24 March. This initiative has a partnership with OSM-Fr and the source code is available on GitHub.
• While experimenting with ways to speed up Layercake builds (a collection of thematic OpenStreetMap data extracts in cloud-native formats) Jake Low has developed a DuckDB extension for reading OpenStreetMap .PBF files.

Programming

• Astrid Emde reported that the Community Sprint at FOSSGIS 2026 resulted in multiple contributions to open-source projects, including a pull request for Mapbender and work on the QGIS Qt6 update. The sprint also provided newcomers with an opportunity to ask questions and actively participate in development.
• Ivovic’s BetterBike-Turns aims to improve turn instructions in bicycle routing and make them more intuitive. It uses OpenStreetMap data to generate more realistic and cyclist-friendly navigation guidance.

Releases

• Marcus Jaschen has released version 2026.7 of Bikerouter, introducing a completely rebuilt elevation profile chart. The new implementation adds multiple features and improves the visibility of highlighted route segments in analysis mode.
• The CoMaps team released version 2026.03.23-5, including updated OpenStreetMap data along with improvements to speed limit handling, road shields, and multilingual display. The update also enhanced navigation and UI on Android and iOS and added new map features.
• Alexis Lecanu (aka ravenfeld) has released version 1.20.1 of the Baba app, mainly featuring bug fixes, including improvements to photo display and GeoVisio link parsing. This update also included numerous dependency upgrades such as MapLibre, Kotlin, and various Android components.

Did you know that …

• … the OpenStreetMap Foundation names its servers after dragons? It is inspired by the phrase ‘here be dragons’, a medieval practice of putting illustrations of dragons on uncharted areas of maps where potential dangers were thought to exist.

OSM in the media

• CHIP reported ► on the Ping Pong Map based on OpenStreetMap and other data.
• Hasi Jain discussed the power of big tech in the 21st century, related to the cartography of regions of the globe and its impact on the citizenship.
• In its latest episode , the French podcast Projets Libres gave the floor to two representatives of the French Fédération des Pros d’OSM (FPOSM). The guests, Florian Lainez (CEO of junglebus) and Marina Petkova (co-owner of dynartio), presented the actions, values and members of this association of OpenStreetMap professionals as well as the dynamics surrounding OSM.

Other “geo” things

• Heise reports that Android is introducing a 24-hour delay as a security requirement for sideloaded apps. The delay will not apply again after switching devices. This may affect OSM-related apps, which are often distributed outside official app stores such as via GitHub or F-Droid.
• The Bibliothèque Nationale de France has just opened ► the exhibition ‘Imaginary Maps: Inventing Worlds’, with more than 200 historical maps and works drawn from mythical, literary, television, and video game universes on display throughout the exhibition, ranging from medieval parchments to maps of Middle-earth, from Thomas More’s Utopia to the realms of Final Fantasy. It is an invitation to journey to the boundaries of reality and fiction, which implicitly questions how we interpret, understand, and shape our own world. The catalogue has been published ►. The Dossier de presse is also available freely.
• Thomas Weibel has developed Isoswiss, a pixel-art styled isometric map of Switzerland.
• Several media outlets have reported on North Oaks (Minnesota), a US city absent from Google Street View since 2008, after authorities threatened legal action over street-level imagery captured on private roads. The unique situation stems from all streets being privately owned; a filmmaker recently attempted to map the area using a drone, sparking debate about privacy and the limits of digital mapping (we reported earlier).
• Big Think explored star forts, which were developed from the 15th century onwards in response to cannon warfare. They were designed with geometric bastions to eliminate defensive blind spots. This design dominated European military architecture for centuries and can still be seen in the layout of many cities today, although it later became obsolete due to advances in weapon technology.
• In a NASA article the SWOT satellite is shown to be able to derive detailed maps of the seafloor from measurements of ocean surface height. Subtle variations in sea surface elevation caused by gravity differences above underwater features allow scientists to detect previously unknown structures such as seamounts and abyssal hills.
• The Los Angeles Times reported that an El Segundo resident was arrested after installing unauthorised stop signs at a neighbourhood intersection. He took this step after months of unsuccessful attempts to get city officials to address his safety concerns, claiming the intersection had become dangerous for children and that he had witnessed several near-collisions involving them. This situation raises questions about OpenStreetMap’s ‘map what’s on the ground’ principle, as signs physically present may not always be officially authorised.
• Quarticle outlined the transition from traditional GIS systems to modern real-time routing platforms. The article explains how contemporary architectures combine dynamic data, APIs, and scalable infrastructure to support applications such as navigation and logistics.
• Yandex described how its new storage and indexing methods for map tiles enables handling up to 80,000 requests per second from a single server. This approach simplifies infrastructure by avoiding backend rendering and leverages object storage, such as S3, to deliver multiple map variants at scale.

Upcoming Events

Country	Where	Venue	What	When
	नई दिल्ली	Jitsi Meet (online)	OSM India – Monthly Online Mapathon	2026-04-04
	Tucson	Wave Archive	A Synesthete’s Atlas: Cartographic Improvisations between Eric Theise, Jeffrey Gordon Evans, Hannah Joyce, and Steev Hise	2026-04-04
	Lucknow	Café Coffee Day, Hazratganj	OSM Lucknow Mapping Party No.3	2026-04-05
	Zaragoza	Facultad de Filosofía y Letras (Unizar) & online	Mapatón humanitario	2026-04-07
	Salzburg	Bewohnerservice Elisabeth-Vorstadt	OSM-Treffpunkt	2026-04-07
	Richmond	Shockoe Hill Cemetery	Shockoe Hill Cemetery mapping with MapRVA	2026-04-07
	Dublin	Online	Easter 2026 Map n Chat	2026-04-07
			Missing Maps London: (Online) Mapathon [eng]	2026-04-07
			iD Community Chat	2026-04-08
	Essen	Verkehrs- und Umweltzentrum	Essen OSM-Treffen	2026-04-08
	Oslo	Royal Gastropub	OSM-Vår-pils	2026-04-09
	Albuquerque	Guild Cinema	A Synesthete’s Atlas: Cartographic Improvisations between Eric Theise, Kenneth Cornell, and Clifford Grindstaff	2026-04-09
	Berlin	Restaurant Split	214. OSM-Stammtisch Berlin-Brandenburg	2026-04-10
	Zürich	Bitwäscherei Zürich	186. OSM-Stammtisch Zürich	2026-04-10
	Paris	MSF France (Paris 19e), France	MSF-CARTONG: Nuit de la Géographie	2026-04-10
	Berlin	Wikimedia e.V. Tempelhofer Ufer 23-24,10963 Berlin	OSM Hackweekend Berlin-Brandenburg 04/2026	2026-04-11 – 2026-04-12
	Braunschweig	Stratum 0	Braunschweiger Mappertreffen im Stratum 0 Hackerspace	2026-04-11
		Armadale Park Cafe	Social Mapping Sunday: Armadale Train Station	2026-04-12
	Milano		Editathon e mapathon alla Milano Marathon 2026	2026-04-12
	Antwerpen		Camera’s in kaart brengen	2026-04-12
	København	Cafe Bevar’s	OSMmapperCPH	2026-04-12
	Meerut	Haldiram’s, Garh Road, Meerut	OSM Delhi Mapping Party No.28 (Meerut)	2026-04-12
			Missing Maps : Mapathon en ligne – CartONG [fr]	2026-04-13
	臺北市	MozSpace Taipei	OpenStreetMap x Wikidata Taipei #87	2026-04-13
	München	Echardinger Einkehr	Münchner OSM-Treffen	2026-04-14
		Oloron-Sainte-Marie – La Friche	Cartopartie à Oloron-Sainte-Marie – Projet SYSTOUR	2026-04-15
		Oloron Sainte Marie	Une cartopartie dédiée à la mobilité durable dans les Montagnes Béarnaises	2026-04-15
		MJC de Vienne	Rencontre des contributeurs de Vienne (38)	2026-04-15
	Karlsruhe	Chiang Mai	Stammtisch Karlsruhe	2026-04-15
			Online Mapathon von ÄRZTE OHNE GRENZEN	2026-04-15
	Freiburg im Breisgau	CCCFR, Adlerstr. 12a, Freiburg (Grethergelände)	OSM-Treffen Freiburg/Brsg.	2026-04-16
		Golem, Avane, Empoli	Mapping Day ad Empoli	2026-04-18
		Dijital Bilgi Derneği	OSM-TR Meet-Up – OSM League Pit-Stop	2026-04-18
	Chennai Corporation		Mapping Party @ Chennai	2026-04-19

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 MatthiasMatthias, Raquel IVIDES DATA, Strubbl, Andrew Davidson, barefootstache, derFred, izen57, mcliquid.
We welcome link suggestions for the next issue via this form and look forward to your contributions.

I was recently reading Demographic deposit, dividend and debt by Sonalde Desai. Following the Standard Operating Procedure, I looked up this Sonalde person and turns out she is a researcher at a research institute in Delhi called National Council of Applied Economic Research. The work of this organization felt interesting to me, so I had to pause my studies and see its location on OpenStreetMap.

Nothing. Looks like the place hasn’t been mapped yet. I searched for 11, Indraprastha Estate since that was mentioned on their contact page and this time I did find an object. A person called “n’garh” had added the address back in July 2014 and I am so glad that I was quickly able to push a changeset (#180878526). Another win for address mapping!

This post was first released on my website with 💜 under CC BY-NC-SA 4.0.

Hey everyone,

the new version of UrbanEye3D, namely 2.0.0, is out!

This is a major update for the plugin. It’s been a lot of work and took about 2.5 months, but I’m confident it makes the 3D view significantly more useful and enjoyable to work with.

For those who haven’t heard of UrbanEye3D before: it’s a JOSM plugin that renders a 3D world from OpenStreetMap data directly inside JOSM. This lets you preview objects in 3D before uploading your changes to the OSM database.

What’s New

1. 2D Ground Plane

Buildings no longer float. The ground surface is displayed with “flat” objects - roads, lawns, rivers, and lakes. This flat layer is rendered based on downloaded OSM data using a custom MapCSS style. Alternatively, a satellite background can be enabled, as before.

2. Trees

Now natural=tree shows up as a 3D object.
- Height is taken from the height tag. If height tag is missing, the circumference tag is used to estimate height.
- Two tree textures are included: broadleaved and needleleaved (based on the leaf_type tag).
- More textures could be added for various species/genus – if you’re good with graphics, feel free to contribute!

3. Whole Multipolygons

Missing members of multipolygons and building relations can be downloaded automatically. Without this, the map often looked broken – like buildings cut in half or water spilling everywhere. The Building relation, which seemed completely useless, turned out to be good for something.

You can turn it off in the plugin preferences if multipolygons in your area are too large.

4. Background Processing

The UI no longer freezes when you load a large area. Everything is calculated in the background. It still takes time to render a big area, but at least JOSM stays responsive.

Contribute

This is a one‑person project, so any help is welcome:

• Textures for more tree species. See some details here.
• MapCSS improvements for the 2D layer. See here.
• If you spot some bugs, please let me know.

Check the GitHub repository if you’d like to help out.

Download

The plugin is available via the JOSM preferences (search for UrbanEye3D).

Enjoy!