OpenStreetMap
Arbuckle is a small community of about 3500 people in southern Colusa County. My husband and I stop through there a few times a year as we head north. It has gas stations and a fantastic Mexican restaurant on 5th street.
So it seemed like a good place to focus on mapping. I have about 100 homes left on the north west corner of the community. I started the project in January on business trip to Chico.
While browsing Taginfo I got curious how many elements have at least one key described on the Wiki and how big share of all keys the described ones make up. Therefore, I decided to check it out.
The analysis consisted of the following parts:
CREATE TABLE elements AS SELECT kind, id, tags FROM ST_READOSM('planet-latest.osm.pbf');;CREATE TABLE elements_keys AS SELECT kind, id, UNNEST(map_keys(tags)) FROM elements;;These are queries I provided to DuckDB:
| Result | Query |
|---|---|
| number of all elements | SELECT COUNT(*) FROM elements; |
| number of tagged elements | SELECT COUNT(*) FROM elements WHERE tags IS NOT NULL; |
| number of elements with key(s) described on the Wiki | SELECT COUNT(*) FROM (SELECT DISTINCT kind, id FROM elements_keys WHERE "key" IN (SELECT "key" FROM 'keys_wiki.csv' WHERE in_wiki)); |
| number of all keys | SELECT COUNT(*) FROM (SELECT DISTINCT "key" FROM elements_keys); |
| number of keys described on the Wiki | SELECT COUNT(*) from (SELECT DISTINCT "key" FROM elements_keys WHERE "key" IN (SELECT "key" FROM 'keys_wiki.csv' WHERE in_wiki)); |
I got the following results:
Teaser/screenshot from UrbanEye3D development version. Sport grounds with markings.
Can you identify the sports? ;)
Resolution could be higher, of course.
I often need to create a single GPX file from multiple related but different GPX files from Garmin and Wikiloc. My use case is finding route recommendations for running based on GPX files. I try to get a single GPX file so I do not have to juggle multiple files during the run. Original GPX files are also noisy, so the added advantage is having a precise path to navigate instead of dealing with GPX noise.
I start by putting all downloaded GPX files into a single directory and plotting them on the map. This step allows me to see them in relation to each other and spot any outliers early. I then simplify each GPX file to reduce the number of points and match them to OSM ways. I filter the points to make them evenly spaced. Finally, I use the OSRM trip service to create a single combined GPX file, or fall back to the minimal number of split files if they cannot be merged into a single file. I plot the resulting GPX files and simplify them to reduce the point count. Now I can sync them to Garmin and use them as a kind of basemap on a device that does not support basemaps.
Of course, this only works when I know the area in advance, can find enough existing route recommendations, and there is a reasonably complete OSM map. The current pipeline is error-prone and I find myself tweaking it to make it work with any specific set of GPX files. You can try it yourself and view the complete code on GitHub: https://github.com/evgeniyarbatov/gpx-courses
Short version:
Recently, I wrote a script that could help with OSM DB data replication using osm2pgsql by filtering .osc files with a specific .poly. It doesn’t limit to a specific continent or country, it can be used with any custom PBF (e.g. a specific city), so it doesn’t need to use .fr replication, it uses planet.osm.org directly (which also could be changed).
It’s inspired by the trim_osc.py script by Zverik, but rewritten from scratch with tests, because the script unfortunately didn’t work for me (maybe I did something wrong).
It’s not a very typical thing, so I’m not sure if it will be useful for anyone, but if someone would like try to self-host a regional OSM DB with replication, I recommend to at least checking it.
More details in the repo: osm-replication-osc-poly-filter
Longer version:
A few months ago, I was looking for an alternative for public Overpass instances (due to overloaded servers) for my projects.
I read SomeoneElse’s diary about self-hosting Overpass instance. But it seems over-complicated to me. I also read many times that there are random issues with reliability and it’s time-consuming to maintain it (not sure how true it is).
I decided that I want to switch to something else for my projects. Something more low-level with greater control of data and more likely self-hosted to avoid such problems. Instead of OverpassQL. I switched to SQL with a PostGIS DB. There are no a lot of choices here, so I chose osm2pgsql.
Osm2pgsql is quite advanced tool, which I really recommend at least reading about it – it may require some time to learn it, but it’s worth to seeing some features like --output=flex, which allows
to defining custom table schemas in Lua scripts with tags/geometry columns which works when importing and appending (replicating) data. It can be adjusted and optimized per project.
SORTA operates MetroNow, a microtransit service covering four zones in Hamilton County: Blue Ash/Montgomery, Springdale/Sharonville, Northgate/Mt. Healthy, and Forest Park/Pleasant Run. The service is powered by Via Transportation, whose routing engine consumes OpenStreetMap as its base map layer.
I am a daily MetroNow rider. A persistent routing failure at my address led me to inspect the OSM data that Via’s routing engine depends on. What I found on one street turned into a zone-wide audit. The results are significant enough that I want to share them with the local OSM community and ask for help.
A residential street in the Blue Ash zone carries two defects from the TIGER/Line 2008 Census import. Both carry tiger:reviewed=no. No human has verified this data since import.
False oneway=yes tag on a two-way residential dead-end street. The false one-way tag makes the routing engine calculate entry with no legal exit. The engine marks the street as unreachable. Drivers get redirected to a neighboring street. Riders get circuitous routes that bypass the correct address entirely.
Disconnected node gap at a cross-street intersection. Two ways representing the same street do not share a node. The routing graph treats the street as two separate, disconnected segments.
For a transit-dependent rider with mobility limitations, a routing failure is not an inconvenience. It is a service denial.
I ran the following Overpass query across the Blue Ash/Montgomery zone:
[out:json][timeout:90];
way["highway"]["tiger:reviewed"="no"]
(39.16,-84.44,39.24,-84.33);
out tags;
Results:
After I got some experience with hosting OpenStreetMap tiles during the revival of Openptmap, I wanted to dig deeper into the topic in order to firstly migrate Openptmap to the new flex output so that it can receive incremental updates, and secondly to be able to host some additional overlays.
I found that the only widely used way to host tiles is overv/openstreetmap-tile-server. On the first look, it is really easy to use. It takes care of importing and updating the OSM database and of rendering and serving the tiles. On the second look however, there are some major challenges and problems with it:
I was looking for a house and decided to use OSM to help me find the optimal location. I had several fixed conditions: I knew my office location and I was looking for a condo close to a primary school. I used OSM to extract all schools and residential buildings. As there were many residential buildings, I used DBSCAN to find clusters and pick one representative building per cluster. To reduce the number of routes to compute, I used the OSRM table service to filter schools and houses within 5 km of each other. Then I ran the OSRM route service on triplets of (home, school, office). I saved the route polylines and locations into a CSV file, then created a KML file based on it and imported it into Google My Maps for visualizing the results. The resulting map is useful for getting a first impression of possible places to live. I am getting quite a few schools and houses to choose from, but I still find it valuable to have a view of the entire city that does not depend on what I happened to find first.
I’d like to announce the release of a new Docker container instance for Overpass.
I’ve been running Overpass locally for a couple of years and have dealt with some reliability issues by improving the shell scripts that drive database updates.
I’ve been sharing those shell scripts with people but I wanted a better way to distribute them. So, I put some effort into cleaning up the scripts (with some significant improvements – see below!) and packaged them in a container build.
There’s already the excellent wiktorn/overpass-api which does a great job of setting up a local Overpass instance. If that looks good to you, you should definitely use it!
For my own use, I wanted something with all the improvements to stability and reliability that I had rolled into the shell scripts, but that would stay true to the original Overpass source code and that would expose all the same configuration options as if it were running on bare metal. I also wanted all the operational support that I already had locally, like configurable area generation intervals and periodic database backups.
Then, given the issues with the performance of public Overpass servers, and the efforts to limit large-scale usage, it seems that having more Overpass servers can only help the community.
First, the database update process is much more robust. When things go wrong during Overpass database updates, the database files can be corrupted. And when that happens you have to start over with a fresh database, either from a backup or from a fresh download. That can mean many hours of downtime.
The shell scripts for database updates have been improved to shut down as gracefully under controlled circumstances and to handle uncontrolled shutdowns as safely as possible.
The Virtual Institute for Sustainable Development – IVIDES.org® and the company IVIDES DATA® are offering a partnership opportunity to update and translate the content of their complete course into English (can be US-EN OR UK-EN) and Spanish (ES).
Conditions:
Both individuals and organisations are eligible to apply. However, organisations must be duly registered in their country in order to receive the funds;
Expected duration of the work: two months (June and July 2026);
Applicants must be citizens from an English- or Spanish-speaking country.
In return, the company offers:
Permanent promotion of the partner’s brand (and/or the name of the person responsible for the translation) on the course page and in all related materials, such as advertisements and others.
The full translation into each language will be rewarded with US$ 200. Complete PDF file: Raquel Dezidério Souto. (2025). Curso de capacitação em mapeamento com OpenStreetMap - Curso completo. Rio de Janeiro: IVIDES DATA, 2025. https://doi.org/10.5281/zenodo.17428748
If you’re interested in taking part, please send an email to:
ivides [at] ivides.org
with the details below. The deadline for registration is 8th May 2026. Let’s go!
Your CV (and/or a letter of intent);
Proof of identity (or national organisation registration document) AND
Your OSM username (full URL).
IVIDES DATA® is a small IT consultancy firm based in Rio de Janeiro (Brazil). We are fully registered in Brazil (CNPJ 56.127.866/0001-12) and can negotiate/operate worldwide.
Here’s what’s changed in the UrbanEye3D plugin over the past week.
We’ve got translations for several more languages: Indonesian, French, and Cornish.
Translations into Spanish and Portuguese as well as into Volapük and Esperanto would be greatly appreciated. Just in case you would like to do that, the pot file can be found here.
I was interested in finding walkable areas in a city I had never visited before. After using OpenClaw bot to summarize my JSON files, I thought I could do the same for OSM-based metrics.
I started by generating an OSM extract with a 5km radius from my hotel. I then extracted the geometry and tags for every way, park, building, and tourist attraction in this area. I normalized the raw data into a handful of generic classes like “Food & Café” and “Nature / Quiet.”
I then assigned each way and point of interest to an H3 hexagon. I calculated aggregate metrics for each hexagon, like the length of roads and the area taken up by parks and water. Then I simply fed the metrics for the hexagon to Ollama with Mistral Nemo, asking it to generate a short one-sentence vibe of a place based on the collected metrics and label it as positive, negative, or mixed.
To visualize the results, I created a KML file and imported it into Google My Maps. I had to iterate on the LLM prompts, as there are a lot of fields in the generated JSON and the LLM struggles to interpret what the numbers mean.
I also discovered a number of bugs in how I calculate features per H3 hexagon, but I eventually arrived at a reasonable overlay showing how walkable each area is. It’s not perfect — partly because OSM data is incomplete for the area I picked, and partly because I need to make my prompts more specific.
The recommendations are generic, but they add an extra dimension to the map. I think this is really exciting because you can create any perspective you like on OSM data with your own overlays for driving, finding a house, or finding a place to eat.
At the suggestion of a friend, I decided to install StreetComlete and give OpenStreetMaps a try. I’ll be adding data as walk and bike and hike around the area.
From February 21th to April 23th I spend 192 extra hours on iD and iD tagging schema, thanks to funding from OpenStreetMap Foundation. This grant is now complete and I want to report on progress made thanks to it.
And I want to also thank for other help:
Here is list of pull requests and issues that were processed during that time, with very limited commentary. I will post also report on forums with more commentary and without detailed listing of issues and PRs.
I want to mention also that substantial design and review work was spend on schema builder to unblock its release. Work on including relation structure knowledge into tagging schema[1][2] took hours, but is not listed below as this PRs are not yet merged. Though it is getting closer now that blocker was resolved.
Disclaimer: I took these notes while working and looked over for mistakes before publishing (fixing some), but I have not tripple checked everything. If you see a mistake, please let me know.
I’m currently in England and have been focusing much of my mapping on improving coverage and detail across the UK. This includes refining road classifications, updating POIs, checking alignments, and making sure tagging stays consistent with current conventions. I try to ground edits in available imagery, local knowledge where possible, and existing community practices.
Alongside that, I’ve been contributing to mapping efforts in parts of Africa. In many of these areas, even small additions like connecting road networks, adding missing settlements, or improving basic infrastructure data can make a meaningful difference for map usability. I’ve been working through tasks such as validating road geometry, adding surface and access tags where appropriate, and helping expand coverage in places that are still relatively under-mapped.
I’m also interested in maintaining data quality over time, not just adding new features. That means reviewing older edits, resolving inconsistencies, and occasionally revisiting areas as better imagery or information becomes available. Consistency in tagging and structure is something I try to pay attention to, especially when working across different regions with varying mapping styles.
Going forward, I’ll continue contributing where I can, both locally in the UK and in regions that benefit from additional mapping support. (i only got into mapping cuz i was bored as i cant play video games… for some reason)
(Made by chatgpt which is why it sound awkward, i just told it my info and it made this) thank u to all who actually read these…
I am quite new and becuz i am unable to play any games i spend some free time doing this mapping ‘game’ as I first thought years ago and then I made account and learned about how to do OSM properly and efficiently and I think it’s good to learn some tech thing.
I map places in UK and also Africa where it is more important to navigate around, and there is large areas of undermapping. (anyway this is useless but whatever its just introduction..
hi
If you’ve been surveying the OpenStreetMap (OSM) map notes in Indonesia, you’ve likely encountered a wave of “spam” or irrelevant notes. These aren’t usually malicious; rather, they are often misplaced private memos from third-party mobile applications that use OSM tiles.
Users often mistake the “Add a Note” feature for a personal notepad or a private “Save Location” tool. Some of these notes are even remnants of data synced from apps nearly a decade ago.
Why is this happening? Many apps integrate OSM. Users see a “Notes” button and assume it’s a private diary for their travels.
This list of spam keywords is not exhaustive. I will continue to update this diary entry as new patterns emerge from the Indonesian mapping community.
Jika Anda melihat catatan peta OpenStreetMap (OSM) di Indonesia, kemungkinan besar Anda akan menemukan “spam” atau catatan yang tidak relevan. Memo tersebut sering kali merupakan memo pribadi yang salah tempat dari aplikasi seluler pihak ketiga yang menggunakan tile OSM.
Pengguna sering salah mengira fitur “Tambahkan Catatan” sebagai catatan pribadi atau fitur “Simpan Lokasi” pribadi. Beberapa catatan ini bahkan merupakan sisa data yang disinkronkan dari aplikasi hampir satu dekade lalu.
Mengapa ini terjadi? Banyak aplikasi mengintegrasikan OSM. Pengguna melihat tombol “Catatan” dan menganggapnya sebagai buku harian pribadi untuk perjalanan mereka.
Daftar kata kunci spam ini tidak lengkap. Saya akan terus memperbarui catatan harian ini seiring munculnya pola-pola baru dari komunitas pemetaan Indonesia.
I have been completely inactive for over a year but I’m trying to pick myself up and keep mapping. I’m very rusty due to the fact that I’ve been inactive but i believe I’ll improve in due time!
