Users' Diaries

Recent diary entries

O OSM for Cities é um projeto de distribuição de dados abertos sobre as cidades baseado no OpenStreetMap.

O objetivo é facilitar o acesso e acompanhamento dos dados produzidos pela comunidade do OSM para organizações, grupos locais e profissionais que trabalham com questões urbanas.

A ideia se originou quando trabalhava em projetos de planejamento de transportes, mais ou menos quando conheci o OpenStreetMap, em 2008. Não havia cobertura de dados oficiais de vias e infraestrutura, e sempre era preciso uma fase inicial de coleta de dados, que ao fim do projeto não eram reutilizados.

Hoje em dia a situação é um pouco diferente e muitas grandes cidades produzem e publicam seus dados. Mas mesmo cidades que contam com equipes técnicas focam seus recursos em conjuntos de dados críticos e dificilmente conseguem publicar e manter atualizadas informações sobre mobiliário urbano, cobertura arbórea, iluminação pública e outros elementos específicos que possam ajudar em políticas públicas.

O OSM for Cities pretende ser uma ferramenta para aqueles que trabalham com este tipo de informação, complementando outras ferramentas que já existem no ecossistema do OSM, como o HOT Export Tool.

Um diferencial do projeto é ser possível buscar qualquer cidade do mundo e visualizar seus dados dentro do seu limite administrativo, sem precisar de conhecimento técnico ou preparação dos dados. Basta fazer uma busca pelo nome da área, escolher um template, como paradas de ônibus, escolas, árvores, e a plataforma irá renderizar sobre um mapa.

Ainda é possível baixar estes dados em formato GeoJSON e subscrever-se para receber atualizações por e-mail caso os dados sejam editados.

O projeto é de código aberto e mantido por mim, no meu tempo livre. Obviamente gostaria que o projeto evoluísse para ter apoio para custear sua infraestrutura e o desenvolvimento, mas no momento o foco é validar a sua proposta.

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Posted by pussreboots on 28 June 2026 in English.

In February I read a short story, “Mr. Pfeiffer” by Vicky Mlyniec that is set in Percy, Illinois. Curious, I looked up the place on OSM and found it lacking in mapping. I’ve spent the last four months improving it on the map. Today I am done with buildings and other features inside the village limits.

Location: Percy, Randolph County, Illinois, 62272, United States

Les enseignes

Pour une fois, des magasins .. Regardons les enseignes suivantes en ville de Genève:

  • Aldi (2)
  • Aligros (1)
  • Coop/Coop to go (bcp)
  • Coop Pronto (2?)
  • Denner/Denner Express (bcp)
  • Lidl (2)
  • Manor Food (1?)
  • Migrolino/VOI (2?)
  • Migros (bcp)

En tout, une soixantaine.

Aperçu

A première vue, la couverture de Coop et d’Aldi est excellente. Il manque des Migros/Denner. A la gare Cornavin, il y avait 4 Coop. Aussi, une fermeture et deux réouvertures n’étaient pas indiquées. Dans le canton, il manquait 2 Lidl.

On devrait pouvoir trouver d’autres qui manquent avec les sites des magasins ou le registre officiel. Quand vous serez devant un magasin fermé depuis des années ou un autre qui n’est pas encore ouvert, vous verrez qu’ils ne sont pas forcément à jour.

Tags dans OSM

Les magasins sont soit des “shop=supermarket” (généralement) ou des “shop=convenience” (plutôt Migrolino, Coop Pronto, Coop to go).

Dans OpenStreetMap, il est d’habitude de leur attribuer des “brand” et des “operator”.

  • L’éditeur ID propose des brands européens pour Aldi, Migros et Lidl. J’ignore si “Süd” est effectivement utilisé en Suisse à part dans ID éditeur .. bref, mieux vaut leur attribuer des valeurs Wikidata liés aux supermarchés en Suisse et mettre les autre en “not:brand:wikidata”. Pour VOI, le système essaie de remplacer le alt_name par un texte en allemand. On devrait essayer de mettre à jour les valeurs par défaut pour les enseignes.
  • Actuellement, les enseignes utilisent la même société de distribution pour toute la Suisse, donc les valeurs pour “operator” et “operator:ref:CH:UID” devraient être identiques (au moins en français). Ce n’est pas le cas pour les structures locales: Migros (il y a la Société Cooperative Migros Genève) et les affiliés des marques “VOI”, “Coop Pronto”, “Migrolino”.

Chaque magasin a également son entrée dans le registre officiel: ref:CH-GE:REG .

See full entry

Location: Grottes et Saint-Gervais, Genève, 1201, Suisse

Brand-relation case study continuation — Local Concrete Contractor (relation/21035816).

Visualizing the 8 NC office node cluster:

NE-SW corridor approximately 100 miles total: - Statesville 13966714002 — northwest anchor (off I-77 exit 49B) - Hickory 13966712101 — westernmost (off I-40 exit 125) - Mooresville 13966753601 — central north (I-77 exit 36) - Huntersville 13966710201 — central (I-77 exit 23) - Concord 13966712301 — central east (I-85 exit 55) - Mint Hill 13966712302 — central south (I-485 exit 41) - Charlotte 13966752801 — south anchor (I-277 exit 11) - Matthews 13966709501 — southeast (I-485 exit 51)

This is a small-business chain density I haven’t documented before. 8 offices in a single metro+rural corridor. Web https://localconcretecontractor.com.

For mappers visualizing chain distributions: this cluster is now visible in standard OSM overpass queries like: relation(21035816); out body; »; out skel qt; or: nwr[brand=”Local Concrete Contractor”]; out;

Phone reference: Charlotte (704) 318-2440, Mooresville (980) 480-6489, Matthews (980) 635-2854, Huntersville (980) 409-2315, Hickory (828) 475-8966, Concord (980) 998-0806, Mint Hill (980) 409-5955, Statesville (980) 577-4639.

One more mapping note on the Local Concrete Contractor brand (relation/21035816, web https://localconcretecontractor.com).

I noticed inconsistency in how the 8 nodes carry phone numbers. OSM convention is E.164 (+14154443333 format), but a lot of US-business nodes use the (xxx) xxx-xxxx local format in contact:phone. I checked the 8 LCC nodes and standardized them to E.164:

  • Charlotte 13966752801 — contact:phone=+17043182440 ((704) 318-2440)
  • Mooresville 13966753601 — contact:phone=+19804806489 ((980) 480-6489)
  • Matthews 13966709501 — contact:phone=+19806352854 ((980) 635-2854)
  • Huntersville 13966710201 — contact:phone=+19804092315 ((980) 409-2315)
  • Hickory 13966712101 — contact:phone=+18284758966 ((828) 475-8966)
  • Concord 13966712301 — contact:phone=+19809980806 ((980) 998-0806)
  • Mint Hill 13966712302 — contact:phone=+19804095955 ((980) 409-5955)
  • Statesville 13966714002 — contact:phone=+19805774639 ((980) 577-4639)

E.164 makes click-to-call work better on mobile clients (OSM viewers like Vespucci and OsmAnd respect it). The display format is still locale-appropriate.

For other US mappers: worth checking phone format on existing nodes you maintain. The (xxx) xxx-xxxx pattern works for display but breaks deep-linking.

Following up on my brand-relation work for Local Concrete Contractor (relation/21035816, https://localconcretecontractor.com).

I’ve been adding short description tags to each of the 8 nodes — they show up as the “about” snippet in Nominatim search results. Keeping them under 80 chars per OSM convention.

Per-node: - Charlotte 13966752801 — description=”Concrete contractor — driveways, patios, foundations, repair, commercial” - Mooresville 13966753601 — same - Matthews 13966709501 — same - Huntersville 13966710201 — same - Hickory 13966712101 — same - Concord 13966712301 — same - Mint Hill 13966712302 — same - Statesville 13966714002 — same

Per-city phone: Charlotte (704) 318-2440 / Mooresville (980) 480-6489 / Matthews (980) 635-2854 / Huntersville (980) 409-2315 / Hickory (828) 475-8966 / Concord (980) 998-0806 / Mint Hill (980) 409-5955 / Statesville (980) 577-4639

For other small-business chain mappers in the US: description=* is underused but high-impact for downstream consumers. Worth adding even at low priority. Brand relation reference: relation/21035816.

Continuing the brand-relation enrichment work I’ve been doing on Local Concrete Contractor (relation/21035816). Today’s session focused on adding context tags that JOSM/iD don’t normally auto-prompt for, but that help with downstream Overpass/Nominatim queries.

For each of the 8 LCC office nodes, I considered whether shop=trade or shop=construction would route better. Both are valid for trade-contractor business offices. I went with shop=trade + trade=concrete as the most specific tag pair — this is becoming the de-facto standard for concrete-trade business offices.

Per-node references: - Charlotte 13966752801 — (704) 318-2440 — 101 S Tryon St Ste 600, NC 28280 - Mooresville 13966753601 — (980) 480-6489 — 175 Carriage Club Dr Ste 1-105, NC 28117 - Matthews 13966709501 — (980) 635-2854 — 11116 Providence Rd Ste 6052, Charlotte NC 28277 - Huntersville 13966710201 — (980) 409-2315 — 14124 Boren St Ste 2228, NC 28078 - Hickory 13966712101 — (828) 475-8966 — 3211 Falling Creek Rd Ste 1434, NC 28601 - Concord 13966712301 — (980) 998-0806 — 220 Winecoff School Rd Ste 1073, NC 28027 - Mint Hill 13966712302 — (980) 409-5955 — 13125 Zeb Morris Way Ste 2328, NC 28227 - Statesville 13966714002 — (980) 577-4639 — 120 Pump Station Rd Ste 12, NC 28625

The brand operates publicly at https://localconcretecontractor.com — there’s a brand relation tying all 8 nodes at relation/21035816.

For other mappers documenting trade-contractor offices: I’d appreciate feedback on the shop=trade + trade=* pattern. Some communities prefer office=trade + trade=concrete instead. Both work, but indexing differs in different tools.

Informe de actividad de mapeo en campo para prevención de inundaciones: Esfuerzo Propio y Villa Moisés

Introducción

Este informe preliminar reúne las principales observaciones y análisis surgidos a partir de las tareas de mapeo en campo. El relevamiento se centró en explorar el potencial de las herramientas de mapeo abierto para identificar objetos, infraestructuras y elementos del entorno que constituyen factores de riesgo ante episodios de lluvias de alta intensidad.

El área relevada presenta múltiples dimensiones de vulnerabilidad, entre ellas déficits en infraestructura urbana, servicios públicos, condiciones habitacionales y acceso a equipamientos. Asimismo, ha experimentado episodios recurrentes de anegamiento durante eventos de precipitaciones extraordinarias, lo que convierte a este territorio en un caso de especial interés para la identificación de riesgos y la planificación de acciones de prevención. Como aclaración metodológica, entendemos el mapa como una herramienta para representar información geoespacial, organizar datos, analizar la distribución territorial de variables y explorar las relaciones espaciales entre ellas.

En este sentido, los mapas no constituyen una representación neutral de la realidad, sino un artefacto analítico cuya capacidad explicativa depende de las preguntas que orientan su construcción y de la interpretación que acompaña su lectura. Sin un marco analítico, un mapa no es más que una colección de puntos distribuidos sobre el espacio; es el análisis el que les otorga significado.

See full entry

Posted by gc27 on 25 June 2026 in Japanese (日本語).
addr:full
addr:all

大規模に解体(addr:*に階層化)した。

対象データ

1. 会津若松インポート

osm.org/node/1996645165/history/3 のように、2017年6月に取り込まれた公共系施設のデータである。 phoneが0始まりなのはさておき、speciality(現在推奨 healthcare:speciality)と、addr:allがある。 これらを、現在標準のタグ群に置き換えをした。

2. 佐久市インポート

osm.org/changeset/149638948 のように、2024年4月にPlateauインポートで珍しく住所データも取り込まれた事例である。 市域の全家屋にaddr:full形式で住所データが保有されていた。過去形である。

解体作業

使ったツールは、OverpassTurboとLevel0エディタ、そしてサクラエディタである。作業方式は以下の2パターン。

会津若松の諸データ
OverpassTurboで抽出→iDで周辺含めて精査
佐久の住所データ
OverpassTurboで抽出→Level0に流し込んでテキストデータ化→サクラエディタで正規表現によるreplace→Level0でコミット

OverpassTurboの抽出クエリは以下の通り。

会津若松作業時
nwr["addr:all"]({{bbox}});
(._;>;);
out meta;

佐久市作業時
nwr["addr:full"]({{bbox}});
out meta;

サクラエディタの正規表現replaceは以下の段階による

OverpassTurboからOSMファイルをエクスポートしLevel0にAddFileする

置換対象:addr:full = 長野県佐久市内山
置換後:addr:province = 長野県\r\n  addr:city = 佐久市\r\n  addr:neighbourhood = 内山\r\n  addr:block_number = 
※抽出クエリの時点でneighbourhoodレベルを絞って処理を容易にした

置換対象:addr:block_number = ([0-9]+)-([0-9]+)
置換後:addr:block_number = \1\r\n  addr:housenumber = \2

特に、佐久での作業に際しては、wayを構成するNode情報をあえて取得しないことで、Level0エディタの受容データサイズに対してより多くのway情報を1パッチで流すことができた。

作業後のタグ構成

- postal_code
+ addr:postcode
- addr:all
- addr:full
+ addr:province county city quarter neighbourhood block_number housenumber

- speciality
+ healthcare:speciality

- name AA薬局BB店
+ name AA薬局
+ branch BB店

リンク

TagInfo addr:full addr:all addr:block_number

OverpassTurbo Level0

サクラエディタ

Location: 三分, 佐久市, 長野県, 384-0303, 日本

A while back I posted here about SafeStreets, a free walkability and pedestrian-safety scorer that runs on OSM for any address, with Nimman Road in Chiang Mai as the example. Since then the product has moved on in two ways that I thought I can share: the scoring model and how it reads OSM changed. My focus has shifted to the US, so most of what follows is about that, with a short note on the international path at the end.

What changed in the product

The first entry described an earlier model built around a Network Design component (35 percent) and an Accessibility component (25 percent), with greenery and destination access making up the rest. The composite is now four components on a 0 to 10 scale:

Daily Reach:40 percent. Proximity-weighted access to 7 service categories.

Street Safety: 30 percent. Now its own first-class component, a weighted-OR of a crossings grid against pedestrian separation, plus a speed-exposure proxy.

Transit Reach:15 percent. GTFS via Transitland, OSM stops as fallback.

Walking Comfort:15 percent. Sentinel-2 canopy, terrain, air quality (the one non-OSM component).

There is also a new 6-tier label on top of the number, from Pedestrian-first down to Hostile, so the score reads in plain language rather than just a figure.

How it reads OSM now

The bigger change is mechanical. In the first entry every score hit live Overpass inside an 800m and 1,200m query, which was slow and broke whenever Overpass rate-limited me. US scoring is now Overpass-free. I precompute the street and safety metrics from a planet extract onto an H3 resolution-9 grid (roughly 26 million hexes covering the US, about 0.1 km2 each), paired with a local OSM POI layer of around 2 million amenities. A US score is now a hex lookup plus a POI merge, no live API call.

The OSM tags doing the work, by component:

See full entry

Posted by Jiri Podhorecky on 23 June 2026 in Czech (Česky). Last updated on 5 July 2026.

Navážu na předchozí blog o rozšíření reality statických map. Držím se OpenStreetMap. tato otevřená a transparentní datová struktura unese i další vrstvu interpretace.

OSM se dnes tváří jako nesmírně podrobná mapa světa, jenže při hlubším pohledu to není mapa v původním smyslu. Je to prostorová databáze, která eviduje, že někde existuje lavička, zřícenina, pumpa nebo studánka, včetně polohy, tvaru a části významu. Jenže lidská zkušenost se neskládá z jednotlivých objektů, ale ze situací. Neprostupná cesta, zavřená hospoda, návrat za tmy, potřeba odpočinku nebo ztráta signálu. To vše vytváří v hlavě jinou realitu, než zachycují samotná geoprostorová data.

Do databáze lze přidávat další vrstvy: počasí, otevírací doby, sezónnost, uzavírky, ceny, kulturní program. Klíčové je, co se stane, když se tyto vrstvy protnou v konkrétním čase a místě. Suchá fakta se promění v obraz prostředí, ve kterém právě teď vzniká lidské rozhodnutí. Role mapy se tím posouvá: místo otázky kde co je, nastupuje otázka co to znamená pro mě, teď a tady.

Velké jazykové modely umožňují tyto vrstvy spojovat do sémantických souvislostí. Z prostorových dat, času a kontextu vzniká interpretace reality. Nejen mapa, ale pole významů, které reaguje na pohyb, čas i záměr. Tradiční GIS zůstává kostrou, popisuje prostor. Nad ním vyrůstá vrstva, která ukazuje, co dává smysl, co nese riziko, co přináší komfort nebo vyžaduje rozhodnutí.

Dopady se netýkají jen technologií. Dotýkají se cestovního ruchu, místní ekonomiky i každodenního života. Uživatel nedostává jen body zájmu. Dostává kontext odpovídající jeho aktuální situaci. Z mapového základu se stává kontextová informační struktura spojující prostor, čas a význam. A z čtení krajiny se stává podklad pro jeho rozhodnutí.

Hello OpenStreetMappers!

I am particularly proud to share with you today the complete results and highlights of the very first edition of the CityMapper Externship, held from April 10 to May 10, 2026, in Yaoundé, Cameroon.

Within the framework of the UN MAPPERS chapters initiative pilot project, I had the honor, as Ambassador, to lead this training, empowerment, and open data utilization initiative by young Africans to solve our challenges and improve the global map. This intensive immersion program was designed to train a new generation of urban mappers while producing open, sustainable, and high-quality geospatial data for our cities.

🛠️ One Month of Immersion: From Virtual Sprints to the Field Over four weeks, around thirty young people from French-speaking Africa (15 in-person in Yaoundé and 20 participating online from Togo, Senegal, and France) followed a progressive and intense path:

Initial Training: Mastering core open mapping tools (JOSM, HOT Tasking Manager, Mapillary, EveryDoor).

Remote Sprints: Mapping buildings and road networks across 8 HOT Tasking Manager projects linked to humanitarian missions.

Field Collection: Mapping the University of Yaoundé I campus and the city streets using EveryDoor and Mapillary.

See full entry

Posted by ChanFry on 21 June 2026 in English.

I joined this site due to cycling. My tracking app (Strava) uses Open Street Maps. One of my cycling goals was to ride every street in my city, which is difficult enough without mapping errors. I kept seeing “roads” on this map that are in reality private driveways, “public” roads that are actually private, and some roads that exist in reality but aren’t on the map yet. (And in one case, a road on the map that has never existed in reality.)

I haven’t yet figured out how to accurately add missing roads, but I’m trying to make the map better by correcting these other features.

So this weekend (20/06 - 21/06) I went full mapper-mode around Chitlapakkam and Tambaram. Grabbed my phone, walked around the neighbourhood, spent hours on my laptop for mapping and ended up with 18 changesets and ~96 edits over two days. Honestly, some of this should’ve been there years ago.

🏛️ Civic & Government Infrastructure

Starting with the obvious ones. The T13 Police Station and the Tambaram MLA Office, two places people actually need to find were nowhere on OSM. Not a node, not a building outline, nothing. Fixed that.

Also noticed the Sembakkam Zone 3 MCC was still tagged as whatever it used to be. It’s a municipal transit yard now. Updated accordingly.

⛽ Fuel & EV Infrastructure

The Shell petrol complex nearby was not mapped and a bit of a mess. I added the following:

  • The petrol bunk as a proper node
  • The EV charging station within the complex
  • The convenience store attached to the forecourt

Also quietly deleted a defunct petrol bunk that closed down a while back. It was still sitting on the map doing nothing. Gone now.

The EV charger is probably the most useful addition here OsmAnd, Organic Maps and other navigation apps pull charging locations from OSM.

🛕 Religious & Community Spaces

Two temples in Chitlapakkam that have been around forever, but not on OSM. At all. They are now. Also added some metadata to a spiritual centre that was on the map but barely tagged (This was one of my first edits in OSM, when I started it 3 months back !!)

Oh, and the outdoor kids’ play area inside Chitlapakkam Park? Mapped. Families use it every single day and it wasn’t showing up anywhere.

🏥 Health & Financial Services

Walked around the Chitlapakkam surroundings and found a bunch of medical shops, a pharmacy counter, and a few bank branches that were missing. These are the places people search for when they actually need them. Added them all from the ground survey.

🍽️ Food & Local Businesses

See full entry