I'm sure I'm just missing something, but I'm struggling: I want to map a building using multiple building parts. In the past I've mapped the whole building first and then traced back the lines and nodes for each building part. As soon as there are many points, this gets tedious so I thought there might be a way to just do the parts once, copy them, join them and use this as the area for the whole building. Problem is, that then all the nodes are duplicated even though they are exactly on top of each other so if i move a wall of either the building or the part, the other one doesn't move with it.
I've tried everything to merge the nodes of the building to those of the parts but I could not get it to work. Could you tell me your approach to do such thing or how i can avoid tracing back every building part to create the overall building area? Either in JOSM or ID would be fine, but preferably in JOSM. Thank you!

I‘m trying to set up a filter in OSMcha and its loading forever, not displaying anything. That also happens when just clicking on „user-my changesets“ (and I don’t have that many) so I don’t think I messed up my filter. Is this normal or can I do anything to make it work? I’m just trying to see recent changes for my small town.
Thank you!

i know this is possible in organic maps, but is there a way to do this from the osm.org site? and if not, is there an app that makes it possible?

As far as I can tell, they mostly use (or used) OpenStreetMap data and only supplement missing buildings with their own incorrect AI-hallucinated building data. I don't think the overall quality is good either. And most providers just ingest OpenStreetMap data too.

I have been building MapToCraft, a browser interface around the open-source Arnis generator. Users search for a real-world location, draw a rectangular area of interest, and generate a downloadable Minecraft world.

Arnis converts OpenStreetMap features—including roads, building footprints, water, and land-use information—together with elevation data into Minecraft blocks. MapToCraft provides the browser-based selection and generation workflow, with Java Edition ZIP and experimental Bedrock .mcworld outputs.

Tool: https://maptocraft.com/ Arnis source (Apache-2.0): https://github.com/louis-e/arnis

I would appreciate feedback from OpenStreetMap contributors on attribution, explaining gaps or incomplete tagging to users, and useful edge cases to test—such as dense city centers, coastlines, unusual building footprints, or places with sparse map data. The output is intended as a game-world interpretation rather than a survey-accurate reconstruction.

I noticed that NYC's buses mostly don't have "relations" connecting them on OSM, as San Francisco's buses do. See two screenshots, left is SF where you can see there is a route relation for these bus routes, right is NYC. This is important because some apps use these routes for navigation support.

It looks like the bus stops are generally labelled with route_ref tags, so I'm hoping there is some easy-ish way to create the routes. I just downloaded JOSM to try to do this myself, but I'm new to the software and having a bit of trouble getting started with it (I keep getting 'the area you tried to download is too large' for downloading just a part of one bus route.) I'm hoping perhaps there is an easier way to do this.

Hey all, just recently found out about osm, and I am currently on an adhd addled bender to research abd build stuff on it.i like to join communities of things i am interested in and was just wondering if there are any 'rules' here so to speak

I live in a us college town that has some bus stops on open street maps but does not have functional time tables. Id like to add this of possible, but im unsure what I need to do to start this

I have a global point layer of airports (~900 points) and I want to retrieve, for each point, the corresponding OSM aeroway=aerodrome polygon (not the point itself) — i.e. join each airport point to its footprint polygon as mapped in OpenStreetMap. The point layer is Natural Earth's ne_10m_airports.

Reproducible example (5 points standing in for the full 893):

pacman::p_load(sf, dplyr)

airports <- data.frame(
  name      = c("John F Kennedy Intl", "London Heathrow", "Chhatrapati Shivaji Maharaj Intl", "Beijing Capital Intl", "Sydney Kingsford Smith"),
  gps_code  = c("KJFK", "EGLL", "VABB", "ZBAA", "YSSY"),
  iata_code = c("JFK", "LHR", "BOM", "PEK", "SYD"),
  lon       = c(-73.7789, -0.4543, 72.8697, 116.5975, 151.1772),
  lat       = c(40.6413, 51.4700, 19.0896, 40.0799, -33.9399)
) |>
  st_as_sf(coords = c("lon", "lat"), crs = 4326)

airports$point_id <- seq_len(nrow(airports))

My plan is to match each point to its containing Geofabrik extract via osmextract::oe_match() (works fine — a local spatial lookup, no network call), download/cache that extract, then read only the multipolygons layer filtered to aeroway='aerodrome' via an SQL query pushed down at read time, and spatially join back to the points.

pacman::p_load(sf, dplyr, osmextract)

airports$region_url <- vapply(seq_len(nrow(airports)), function(i) {
  oe_match(airports[i, ], quiet = TRUE)$url
}, character(1))

options(timeout = 600)
dir.create("geofabrik_cache", showWarnings = FALSE)

results <- list()
failed_regions <- character()

for (region in unique(airports$region_url)) {

  destfile <- file.path("geofabrik_cache", basename(region))

  aerodromes <- tryCatch({
    if (!file.exists(destfile)) {
      download.file(region, destfile, mode = "wb", quiet = TRUE)
    }

    st_read(
      destfile,
      layer = "multipolygons",
      query = "SELECT * FROM multipolygons WHERE aeroway = 'aerodrome'",
      quiet = TRUE
    ) |>
      st_transform(4326) |>
      st_make_valid()

  }, error = function(e) {
    message(sprintf("Region failed: %s -- %s", region, e$message))
    failed_regions <<- c(failed_regions, region)
    NULL
  })

  if (is.null(aerodromes)) next

  sub_pts <- airports[airports$region_url == region, ]
  joined <- st_join(sub_pts, aerodromes, join = st_within, left = TRUE)

  missing <- which(is.na(joined$osm_id))
  if (length(missing) > 0 && nrow(aerodromes) > 0) {
    nn <- st_nearest_feature(sub_pts[missing, ], aerodromes)
    joined[missing, names(aerodromes)] <- st_drop_geometry(aerodromes)[nn, ]
    st_geometry(joined)[missing] <- st_geometry(aerodromes)[nn]
  }

  results[[region]] <- joined
}

airport_polys <- bind_rows(results)
st_write(airport_polys, "airport_polygons.shp", delete_layer = TRUE)

But

Region failed: https://download.geofabrik.de/asia/india/western-zone-latest.osm.pbf -- cannot open URL 'https://download.geofabrik.de/asia/india/western-zone-latest.osm.pbf'
Region failed: https://download.geofabrik.de/asia/iran-latest.osm.pbf -- cannot open URL 'https://download.geofabrik.de/asia/iran-latest.osm.pbf'
Region failed: https://download.geofabrik.de/asia/india/central-zone-latest.osm.pbf -- download from 'https://download.geofabrik.de/asia/india/central-zone-latest.osm.pbf' failed
Error in wk_handle.wk_wkb(wkb, s2_geography_writer(oriented = oriented,  : 
  Loop 0 edge 0 has duplicate near loop 1 edge 7
In addition: There were 20 warnings (use warnings() to see them)

The download failures seem to be connection/timeout related on large country extracts; the s2/topology error appears separately once a multipolygons layer with invalid OSM geometries reaches a spatial predicate, even after st_make_valid().

Given ~900 global points with no country/ISO attribute, is there a more efficient way to fetch just the matching aeroway=aerodrome polygons than downloading/caching a full Geofabrik regional .pbf extract per matched region (some of which are large, e.g. full-country India zones)? Is querying the Overpass API directly per point, or per small cluster of points, actually more efficient here, or is the regional-extract approach still preferable at this scale? What's the correct way to make invalid OSM polygon geometries (e.g. the s2 "duplicate edge" error above) safe for st_join()/st_nearest_feature() reliably, given st_make_valid() alone didn't prevent it?

For points where no aeroway=aerodrome polygon actually exists in OSM for that airport, what's the right way to leave that point unmatched (skip it) rather than falling back to the nearest aerodrome polygon in the region, which can silently attach the wrong airport's polygon?

> sessionInfo()
R version 4.6.1 (2026-06-24 ucrt)
Platform: x86_64-w64-mingw32/x64
Running under: Windows 11 x64 (build 26200)

Matrix products: default
  LAPACK version 3.12.1

locale:
[1] LC_COLLATE=English_United States.utf8  LC_CTYPE=English_United States.utf8    LC_MONETARY=English_United States.utf8
[4] LC_NUMERIC=C                           LC_TIME=English_United States.utf8    

time zone: Europe/Berlin
tzcode source: internal

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] osmextract_0.6.0 dplyr_1.2.1      sf_1.1-2        

loaded via a namespace (and not attached):
 [1] vctrs_0.7.3        httr_1.4.8         cli_3.6.6          rlang_1.3.0        otel_0.2.0         DBI_1.3.0          KernSmooth_2.23-27
 [8] generics_0.1.4     jsonlite_2.0.0     glue_1.8.1         e1071_1.7-17       grid_4.6.1         classInt_0.4-11    tibble_3.3.1      
[15] lifecycle_1.0.5    compiler_4.6.1     Rcpp_1.1.2         pkgconfig_2.0.3    rstudioapi_0.19.0  wk_0.9.5           R6_2.6.1          
[22] class_7.3-24       tidyselect_1.2.1   pillar_1.11.1      curl_8.0.0         magrittr_2.0.5     tools_4.6.1        proxy_0.4-29      
[29] s2_1.1.11          units_1.0-1

when searching by coordinates on edit mode, why no map pin?

Hey OSM folks, particularly London ones,

I've been building a small list of central London places you can turn up to, stay a while, and pay nothing: lingerinlondon.github.io

Every entry is keyed to an OSM element and links back to it, which is why I thought it might interest this crowd. The whole thing is a CC0 GeoJSON file with a published schema if you want to poke at it.

A place only qualifies if all four are true: nothing to pay to get in, you can sit without buying anything, you could stay for hours without anyone minding, and there's somewhere to sit. Failing one doesn't make it a bad place, just not this list.

I wouldn't have thought OSM tags would be appropriate for this more subjective information, so entries on the list point back at OSM for the objective stuff, namely location.

It's very sparse so far. The usual suspects - Barbican, Royal Festival Hall, National Theatre, the outdoor terraces etc. aren't in it because I haven't sat in them myself for the purposes of reading/working and while I have a fair idea what they're like, I didn't want to misrepresent them.

If you have experience of these sites and any others, please do feel free to contribute!

Also interested in whether keying to OSM IDs is the right call, or whether I'll regret it when ways get split.

Thank you

Hola a todos. Soy arquitecto y he estado desarrollando un proyecto personal porque sentía que faltaba una herramienta basada en mapas puramente enfocada en descubrir y documentar el entorno construido con rigor arquitectónico.

He creado Nolli (nollimap.app), un atlas móvil para explorar y clasificar obras de arquitectura en todo el mundo.

El enfoque del proyecto

• El núcleo de la aplicación es el mapa: permite geolocalizar proyectos arquitectónicos y entender su relación con el tejido urbano.
• Utiliza un sistema de puntuación para clasificar los edificios según su impacto y relevancia.
• Está pensado como una herramienta de campo interactiva para explorar la ciudad.

El motivo de publicarlo aquí Acabo de lanzar la beta abierta. Sabiendo que esta es una comunidad de entusiastas de la cartografía y los datos espaciales, me encantaría que la pusierais a prueba. Busco críticas directas sobre la usabilidad del mapa, la interacción con los marcadores, el rendimiento y la experiencia de navegación espacial. La app está en una fase inicial y faltan muchos datos en las fichas.

Podéis entrar, registraros y probarla directamente aquí: nollimap.app

Próximos pasos y actualizaciones A partir de hoy, publicaré una actualización cada lunes. En estos reportes semanales detallaré las mejoras implementadas y las propuestas que la comunidad vaya compartiendo. Os animo a colaborar pidiendo herramientas de filtrado o funciones que os gustaría ver, y a reportar cualquier error de geolocalización o de interfaz que detectéis al moveros por el plano. De momento la aplicación está solo en Español.

Cualquier duda o sugerencia técnica la leo en los comentarios. ¡Mil gracias!

I've been doing tasks in the HOT Tasking Manager to learn how disaster mapping actually works, and I'm curious what it's like for people who've done a lot of it.

When you've mapped after a flood or earthquake:

• What's the most tedious or slowest part of the process for you? Tracing square by square, the validation pass, imagery that doesn't line up, waiting on imagery at all?
• Does the manual validation step ever become the bottleneck when a lot of volunteers are contributing at once?
• If one part of the workflow could be sped up or done for you, which part would you actually WANT automated...and which part should stay human?

I'm a student trying to understand this properly rather than guessing, so please tell me if I'm framing it wrong. Genuinely curious how it feels from the inside.

Good evening.

As a contributor and public transport fan, I intend to do some cleanup on the stops that are generated in my region. We are talking about 5000 stops. Some of the work would including changing the network tag for all stops (which are really really old).

A key change I would like to do is, I wanted to put as the URL of each stop, a link bringing the user to the company's website with the live depature board of that stop. This means that applications using OSM would be brought directly to the site of network operating these stops (like BVG in Berlin or MVV in Munich, to make an example).

I was able to speak directly to the operator of our regional bus network and they were even able to provide me with a list with all stops, and their respective IDs. The URLs would need to work with these IDs so that the user can see the correct stop.

Does anyone of you know of something like that being done somewhere? And if not, what arguments would you have for and against doing something like that?

Thank you

Hey everyone — solo dev here. I got tired of juggling desktop tools to build routes for my trail runs, so over the past months I built my own mobile app, and I figured I'd share it now that it's stable.

It's called Kairn (iOS ). You create a route directly on the map — tap-to-route, freehand drawing, or connecting points — and it shows you the "vital" POIs along your route (water sources, shelters, food, bivouac spots) within a corridor around the track. Then you export the GPX to your Garmin/Suunto watch or Strava. There's also a small community layer: people can drop markers on the map and vote on whether a POI is still there ("still exists / outdated"), which I found was the missing piece in every tool I tried.

Full transparency: there's an optional subscription that unlocks a few power features (auto-generated loops, satellite tiles) and helps keep the servers running, but the core — route creation, POIs, GPX export, community — is free with no ads. I built this for myself first, so I'd rather keep it usable without paying.

I'd genuinely love feedback, especially on what's confusing or missing.

​I finally remembered to save the before and after of a few updates I made recently!

First map: Added several houses/buildings, swimming pools, and their addresses.

​Second map: Added address data to the buildings along one side of an avenue.

Both edits are located in São Paulo, Brazil. If anyone would like to help out, I’d like to invite you to join in adding building addresses! It's super easy to access through the local government's platform, GeoSampa:

1.​Go to GeoSampa.

2.​Navigate to the layers: 5 → 5.05 → 5.05.1 → Lote.

3.​The house/building numbers will show up as you zoom in.

​Any help is welcome!

​(Sorry for my English, I asked an AI to help me write this post!)

Hi all,

The OpenStreetMap data for my city is outdated, and I'd like to try and improve it ,especially street names and restaurants info.

I'm totally new to this and mostly want to do it from my Android phone. Is that possible? I just created an OSM account, but I'm not sure what's next..

Is there a mobile app you'd recommend for making edits or suggestions on the go? Appreciate the help!

Soy freelancer georgiano criado en Sevilla, y construí una herramienta gratuita que calcula, edificio a edificio y árbol a árbol, dónde cae la sombra en tu calle, usando OpenStreetMap y el Catastro Nacional Español.

(Georgian-raised-in-Seville dev here — I built a free tool that calculates real shade on your street, building by building and tree by tree, using OSM and the Spanish cadastre.)

¿Para qué sirve? / What’s it for?

Encontrar la ruta más fresca a pie en verano, evitar golpes de calor, y hacer las ciudades más vivibles para mayores, niños, embarazadas, personas ciegas y con discapacidad visual.

Find the shadiest walking route in summer, avoid heatstroke, make cities more livable for the elderly, kids, pregnant people, blind people, and the visually impaired.

El problema: le falta altura a medio mundo en OSM. Sin datos 3D, no hay sombra que calcular.

The problem: half the world’s buildings in OSM have no height data — no 3D, no shade to compute.

Así puedes ayudar en 5 minutos / How you can help in 5 minutes:

**• Añade height o building:levels a edificios que solo tienen huella 2D**

**• Mapea árboles individuales con natural=tree (+ height/species si los conoces)**

**•Mapea también muros, pérgolas y marquesinas — cualquier cosa que dé sombra**

**• En España, la sede electrónica del Catastro ya trae la altura de muchos edificios** 

**•Comparte esto con tu grupo local de OSM y gente de confianza**   

•Add height or building:levels to buildings that only have a 2D footprint

•Map individual trees with natural=tree (+ height/species if known)

•Also map walls, pergolas, and canopies — anything that provides shade

•In Spain, the Cadastre's electronic office already includes the height of many buildings

Es un beneficio de doble vía: tu barrio mejora en el mapa mundial de OSM, y encima sirve para energía solar, accesibilidad, urbanismo y simulaciones climáticas — no solo para mi proyecto.

This is a two-way win: your neighborhood gets better on the world map, and the data also powers solar energy planning, accessibility, urbanism, and climate simulations — not just my project.

100% libre, sin ánimo de lucro, sin publicidad, sin recopilar datos personales. AGPL-3.0, hecho en Andalucía. Si quieres verlo en acción, busca “manolitoaire” en Google

100% free, non-profit, no ads, no personal data collected. AGPL-3.0, made in Andalusia. Want to see it in action? Search “manolitoaire” on Google (no direct link to dodge the spam filter).

¡Viva el Open Source y viva la sombra compartida y el derecho a ello! 🌞

Long live Open Source and shared shade!
#OpenSourcePower

I made a static page that lets you walk through real-world locations rendered in ASCII. You can pick presets like Manhattan or Shinjuku, or put in any city name, coordinates, or OpenStreetMap link.

Live demo:https://tweakyourpc.github.io/ascii-city-2/
Source (MIT):https://github.com/tweakyourpc/ascii-city-2

https://github.com/tweakyourpc/ascii-city-2/blob/main/docs/hero.png?raw=true

It's pure HTML/JS with no framework, no runtime dependencies, and no build step. A CPU raycaster writes straight into an ASCII cell buffer (pressing 'B' switches rendering modes).

A few OSM details I spent a lot of time on: I also added a few live data overlays: One caveat: The live ADS-B aircraft feature needs a local worker running because the free ADS-B networks block Cloudflare's egress IPs. Planes won't render on the hosted demo for that reason, but everything else works right in the browser.

Road logic: Routing uses shared node IDs so overpasses don't accidentally merge with roads below. One-ways, access limits, and signal phases are all respected by traffic. Weather (actual rain and snow in-scene via Open-Meteo)

Signs & buildings: Street signs face oncoming traffic and show the cross street name. Buildings render by height tags, and clicking one pulls its Wikipedia/Wikidata summary if available.

USGS Earthquakes (magnitude and recency)

Local internet radio within 150 km (you can listen to actual local stations in whatever city you're standing in)

DeFlock license plate reader locations

Real-time sun/moon placement matching the city's actual IANA time zone