OpenStreetMapThere has beena very interesting question on the OSM US Slack lately.
“Does anyone have a method to search through the OSM database for a building of a particular shape? I need assistance finding OSM buildings with this specific shape. They should be located in NJ, DE, northeastern MD, eastern PA, or southern NY.”
The question quickly exploded into a huge discussion. At the time of writing, there are already 71 replies.
Someone suggested :
“You could load OSM buildings into PostGIS and then useST_HausdorffDistance to compare the geometries.”
From there, the discussion veered into how to solve that specific puzzle and find the exact OSM building in question.
One person added, “So the strategy is: create the shape of the building you want to search for, scale it to, say, fill a 100x100 m bounding box or something. Ask Postgres to, within a search-area bounding box, take each building and scale it to a 100x100 m bounding box, compute the Hausdorff distance with the scaled input shape, and return all OSM element IDs and their Hausdorff distances, sorted in ascending order.”
Another said, “What I’m currently doing is combining several shape exports into a single file with around 20,000 objects that have concavity. Concavity plus more than 10 nodes eliminates most buildings.”
At that point, instead of hunting that elusive specific OSM building, I became more interested in the generalized version of the problem.
So I added my two cents to the discussion:
“The generalized version of this problem would be : Can we represent a shape in some kind of data type that allows us to computationally check whether two objects have the same shape, regardless of rotation and scaling?
I haven’t studied the Hausdorff distance yet, but I’m wondering whether it can solve this problem, or if there’s a better alternative—Hu moments, Procrustes analysis, Fourier descriptors for contours…”
Someone replied :
New CNEFE Tool Revolutionizes Street Name Correction in OpenStreetMap Brazil
The community of Brazilian mappers has just gained a powerful ally to improve one of the most crucial and, at the same time, challenging data points in any map: street names. The CNEFE Verification System platform has been launched, accessible athttps://cnefe.mapaslivre.com.br, a tool created by and for the OpenStreetMap (OSM) community in Brazil, aimed at validating and correcting address data using the latest information from the 2022 IBGE Census.
The project is an initiative of UMBRAOSM (Union of Brazilian OpenStreetMap Mappers) and was developed by experienced mappers Raphael de Assis, president of UMBRAOSM and member of the OpenStreetMap Foundation, and Anderson Toniazo, both active members of the OSM Brazil community. The tool arrives to solve a long-standing bottleneck in national mapping: the updating and verification of street names based on official sources.The Challenge of Street Names in Brazil
For those mapping in Brazil, one of the biggest challenges has always been the lack of a complete, accurate, and freely accessible street database. Through the Demographic Census, IBGE compiles the National Registry of Addresses for Statistical Purposes (CNEFE) . This registry is a vast list of addresses from across the country, containing street names, address types, neighborhoods, and, in many cases, geographic coordinates, especially in rural and non-residential areas.
Historically, the OSM community has used CNEFE data from previous censuses (such as 2010) to enrich the map. However, the process was complex, involving downloading text files (fixed format), cross-referencing them with census tract shapefiles, and extensive manual work to match the information with the streets already drawn on the map, in addition to correcting spelling differences.
A comunidade de mapeadores brasileiros acaba de ganhar uma poderosa aliada para aprimorar um dos dados mais cruciais e, ao mesmo tempo, desafiadores de qualquer mapa: os nomes das ruas. Foi lançada a plataforma Sistema de Verificação CNEFE, acessível emhttps://cnefe.mapaslivre.com.br, uma ferramenta criada por e para a comunidade OpenStreetMap (OSM) no Brasil, com o objetivo de validar e corrigir os dados de logradouros utilizando as informações mais recentes do Censo 2022 do IBGE.
O projeto é uma iniciativa da UMBRAOSM (União dos Mapeadores Brasileiros do OpenStreetMap) e foi desenvolvido pelos experientes mapeadores Raphael de Assis, presidente da UMBRAOSM e membro da Fundação OpenStreetMap, e Anderson Toniazo, ambos membros ativos da comunidade OSM Brasil. A ferramenta chega para resolver um antigo gargalo no mapeamento nacional: a atualização e verificação dos nomes das ruas a partir de fontes oficiais .O Desafio dos Nomes de Ruas no Brasil
Para quem mapeia no Brasil, um dos grandes desafios sempre foi a falta de uma base de dados de logradouros completa, precisa e de livre acesso. O IBGE, através do Censo Demográfico, coleta o Cadastro Nacional de Endereços para Fins Estatísticos (CNEFE). Este cadastro é uma vasta lista de endereços de todo o país, contendo nomes de ruas, tipos de logradouro, bairros e, em muitos casos, coordenadas geográficas, especialmente em áreas rurais e não residenciais .
Historicamente, a comunidade OSM já utilizava dados do CNEFE de censos anteriores (como o de 2010) para enriquecer o mapa. No entanto, o processo era complexo, envolvendo o download de arquivos de texto (formato fixo), o cruzamento com shapefiles de setores censitários e um trabalho manual intenso para casar as informações com as ruas já desenhadas no mapa, além de corrigir diferenças de grafia .
Today I contributed to OpenStreetMap by improving map completeness in my local area in Bengaluru, Karnataka.
🔹 What I Worked On
Added a missing café using local knowledgeVerified placement to ensure it was mapped at the correct entrance locationAdded appropriate tags including:amenity=cafename= ##Bean Stop Café
Checked for duplicate entries before uploading
🔹 Mapping Approach
I focused only on verified, ground-truth information and avoided copying from copyrighted sources.All additions were based on direct familiarity with the area.
🔹 Quality Checks
Ensured the point was not placed on the roadwayConfirmed correct spelling and capitalizationReviewed surrounding features for consistency
🔹 Objective
The goal was to improve local POI completeness and contribute accurate, structured data to OpenStreetMap.This is part of my effort to make consistent, quality-focused contributions rather than large, unverified edits.
Hi everyone,
I recently noticed that many modern pedestrian crossings are equipped withautomatic detection sensors that trigger the traffic signal without requiring a push button.
Currently, in OpenStreetMap, we can tag:
highway=crossing andcrossing=traffic_signals for signalised crossingsbutton_operated=yes/no to indicate if a manual button is presenttraffic_signals:sound=yes/no for auditory signalsHowever, there isno standard way to indicate automatic activation by a detector for pedestrians or vehicles.
To address this, I have proposed a new tag on the OSM forum:detector_operated=yes/no, which would clearly indicate that a traffic signal is automatically triggered by a detector.
You can view and comment on the proposal here:https://community.openstreetmap.org/t/proposal-tag-traffic-signals-detector-operated-pedestrian-presence-sensor/141624
In this changeset (176210161), I focused on improving building-level mapping by adding missing building outlines and refining structural details using Bing Maps aerial imagery.
The objective of this session was to enhance spatial accuracy and improve map completeness in the area. I ensured that:
This edit was completed using the iD editor (v2.37.3), and I requested a review to ensure quality validation and community feedback.
Working on building details helped strengthen my understanding of:
I will continue improving structured building data and map quality in Karnataka.
Today, I worked on improving map data around Yelahanka Taluku, Karnataka. I updated the official name of Sai Vidya Institute of Technology to reflect accurate real-world information and ensured proper tagging consistency.
In addition to correcting the name, I reviewed campus boundary structure, building tagging, and surrounding infrastructure to avoid duplication and maintain data integrity. I verified that the edits align with real-world sources and OSM tagging standards.
My focus during this session was on:
This session helped reinforce the importance of precise tagging, version tracking, and reviewing live map data versus cached tiles.I will continue contributing to improving structured geospatial data across Karnataka.
Contexte :Le17 février 2026, j’ai résolu lanote #5169818 signalant un problème d’itinéraire cyclable à Toulouse (coordonnées : 43,5615376 ; 1,4920996). Unbloc de béton obsolète (après la fin des travaux) provoquait un détour inutile sur les calculs d’itinéraire.
Actions réalisées :- Correction dans OSM : suppression de l’obstacle (changeset #178691426).- Attente de la mise à jour des données parGeovelo.
Lien direct pour tester :Geovelo - Itinéraire test
À faire :-Vérifier vers le 19 mars 2026 si l’itinéraire est corrigé sur Geovelo/OSRM.- Si le problème persiste, rouvrir la note ou contacter Geovelo.
Localisation :Voir sur OSM
#OpenStreetMap #Toulouse #Vélo #Contribution #Geovelo
Di seguito le persone coinvolte nel progetto: “Pesaro ha bisogno di te!”.
A un gruppo di studenti e studentesse è stato chiesto di incrementare il livello di precisione e accuratezza della mappa nella loro città (e dintorni, alcune e alcuni vivono in zone limitrofe).
Tutte le modifiche saranno ritenute validese, e solo se, riporteranno l’hashtag#PCTOMarconi2026 e verranno effettuate dagli utenti coinvolti nel progetto di seguito elencati (viene riportato solo il nome utente).
⚠️ In caso di necessità, vi prego di contattarmi via email <giacomo.alessandroni@wikimedia.it> o su Telegram (@galessandroni). In questi canali sono più reattivo rispetto alla messaggistica interna.
Naturalmente, sentitevi liberi di correggere qualsiasivandalismo refuso doveste notare.
Many people have noticed that publicly available Overpass servers have been suffering from overuse (a typical“tragedy of the commons”).OSM usage policies generally contain the line “OpenStreetMap (OSM) data is free for everyone to use. Our tile servers are not”. Unfortunately,there have been problems withoveruse of the public Overpass servers, despite theusage policy. “Just blocking cloud providers” isn’t an option, because (seehere - use the translate button below) lots of different sorts of IP addresses, including residential proxy addresses, are the problem.
People who want to use e.g. Overpass Turbo do have theoption to point it at a different Overpass API instance. If you’re using Overpass Turbo and you get an error due to unavailability, likely that is because the Overpass API that it is using is overwhelmed. There areother public Overpass API instances, but they may be complete (in terms of geography, or history) or up to date.
Hello! This is my first Diary Entry and I wanted to dedicate it to theForum Post that I made about the UKs Only (I Believe) ER OUT routes in the case of any emergencies: mainly flooding in this case.
After major flooding in 2013 the council created the Lincolnshire ER Routes to enable people to quickly evacuate from the flood areas. Many of you make have driven past these and never even noticed!They are Red rectangular signs with the white text of ER out on them with a direction to follow. They are placed at every turn, so the evacuees follow the road ahead until a signs says otherwise.
The end of the route signifies that the evacuees are clear of the major flood risk and (presumably) there would be further guidance at the end of the route. The route end sign is the same as the direction signs however it features 5 black diagonal lines.
Σε εφαρμογές που “πατάνε” στους Open Street Maps (σίγουρα στις Mapy. OSMand, Organic Maps, ίσως και αλλού), ως E65 εμφανίζεται ΛΑΘΟΣ ο παλιός δρόμος Λαμία-Δομοκός-Φάρσαλα-Λάρισα και όχι ΣΩΣΤΑ ο αυτοκινητόδρομος Θερμοπύλες-Καλαμπάκα (και ημιτελές Βορειότερα ως την συμβολή με την Εγνατία). Ιδίως για τους ξένους ταξιδιώτες είναι μέγα μπέρδεμα.
2026-02-01に’さくらインターネット Blooming Camp’で行われた「マッパーズサミット2026」での発表内容です
発表内容のうち、OSM wikiに記載されている項目の解説を「OSMの基礎知識編」します
「基礎知識」と思ってバカにしないでください。日本の編集のほとんどすべて（９９％以上）がOSM wikiに記載事項に違反しています
また、’talk-ja’などでの意見も OSM wikiに記載事項を理解されていないと思われるものが多いです
実例を使って交差点のタグ付けを考えて見ましょう。
ちなみに、この例は私の自宅近くにある交差点で一般的なものです、特殊な例ではありません。
junction=yes とします。OSMのマッピングをはじめて、今日で継続年数1年たった。
アカウント自体は5年前に作っていたが、
当時は県道沿いに建物は張り付いてた分しかなくて（うるおぼえ）、
かつて住んでたところくらいはと、3町分の建物を描いたところで、飽きてしまい辞めた。
そして去年の今日、たまたまマップを見てみたら、建物やPOIがかなり充実してたのを見て再燃し、今に至る。
今のところ、熱は冷めてない。
個人的に継続中の調査テーマもあるし、描きたいものもたくさんある。
続けていくつもりなら、いずれはデータを活用する側にも回りたい。
そのためにもマッピングを進めていこうと思う。
オレはようやくのぼりはじめたばかりだからな
このはてしなく遠いマッピング坂をよ……
大阪市の中心付近に、信号停止線に「一時停止」タグがつけられた箇所がたくさんあります。
「一時停止」標識が存在しない場所なので、誤ったタグ付けなのですが、交点に信号機があるだけの状態よりも優れたマッピングです。
しかし、このままでは、初心者マッパーに「誤りだから・・」という理由で単純に削除されてしまう恐れがあります。
「osmwiki JA:Tag:highway=traffic_signals」で推奨されている「highway=traffic_signals」に書き換えましょう！
Safe Routes to School is a program designed to help parents encourage their children to walk and bike to school safely, while promoting healthy engagement. In some locations, walking or biking to school is a child’s only means of getting to school. My goal is to help parents find the best routes to school and to assist them in working with local governments to improve safety. But we need more volunteers to help improve the data.
Bike maps already exist. Not only does OSM offer two different map layers for cyclists, but there are several apps available. Pedestrian maps are a different story. While there are some pedestrian maps, such as the University of Washington’s Taskar Center for Accessible Technology’sAccessMap.app, they are limited. What is needed is a tool that parents can use to find a good walking route to school, as well as a tool that can help improve pedestrian mapping, much like OpenStreetMap US’sOpenTrailMap.us. The rendering should show pedestrian ways, crossings, accessibility features like tactile pads and kerb ramps.
OSM has some great routing engines. The user interface will likely need to be improved so that features can be added to avoid. For example, railways may be dangerous for children to cross. By allowing the addition of features to be avoid, it’s possible to provide a safe route.
About 99% of supplements have garbage in them like seed oils, starch, citric acid or other fillers because most people are too ignorant to read the ingredients labels, let alone realize that ultra-processed pseudo-food is harmful for them in the first place.
I wonder if there is some tag for a nutrition supplements store to state that they offer clean supplements with just one ingredient, just like vegetarian tags, except focused on health rather than ethics.
Maybe diet:raw=* could somewhat apply?
县道、乡道、村道的编号规则是什么？答：1.县道命名及编号规则：
（1）命名规则：以起终点行政节点名称第一个汉字加“线”组成，如起于高淳县东坝镇终于高淳县固城镇，则命名“东固线”；如起终点为非行政节点，则以起终点具代表性的名称第一个汉字加“线”组成。
（2）编号规则：本轮县道网编号以现有编号体系为基础，现有县道编号基本保持不变，新增县道编号按照方向和类型，在现有县道编号后依次排列，即“老路老编号、新路新编号”。具体编号原则如下：
①编号由字母和数字共10位构成，如“X105320125”，其中，“X”反映县道的性质；“105”反映线路的类型、方向和顺序；“320125”为线路所在县（市、区）的行政代码（以国家统计局发布的2013年江苏省行政区划代码为准）。
②例：“105”：第一位“1”表示线路方向和类型，“05”表示为顺序码。
“1”开头表示由县城（市、区）向外辐射的树状县道网，顺序码从正北方向顺时针依次增大；
“2”开头表示南北纵向县道编号，顺序码从东向西依次增大；
“3”开头表示东西横向县道编号，顺序码从北向南依次增大；
其中，“101~150”、“201~250”、“301~350”编号，适用于保留、局部延伸或调整的现有县道线路，原有县道线路编号不做调整；“151~199”、“251~299”、“351~399”编号，适用于本轮新增县道和上轮县道规划后陆续增编的临时县道编号线路（即X+字母+两位数字+行政区划代码的线路）。
2.乡道命名及编号规则：
（1）命名规则：以起终点行政节点名称第一个汉字加“线”组成，如起于溧水区晶桥镇止于溧水区晶桥镇新山里村，则命名“晶新线”；如起终点为非行政节点，则以起终点具代表性的名称第一个汉字加“线”组成。以上两种命名规则，必须保证在同一县域范围内名字不重复。
（2）编号规则：路线编码由行政等级代码+三位编号+县级行政区划代码共十位组成，具体表示方法如下所示：
“Y”：代表乡道的行政等级代码；“101”：代表乡道的排列顺序编码，采用“老路老编码，新路新编码”原则，老线路以及延伸段采用原有编码，新线路编码从“AA0”开始至“ZZ9”；“320111”：代表该县（市、区）的行政代码。
县（市、区）交通运输局根据各乡镇的实际情况拆分乡道编码，确保县（市、区）域范围内乡道编码的唯一性。
3.村道公路命名及编号规则：
（1）命名规则：以起终点行政节点名称第一个汉字加“路”组成，如：起于溧阳市上兴镇建盟村，终于溧阳市上兴镇红旗村，则命名“建红路”；如起终点为非行政节点，则以起终点具代表性的名称第一个汉字加“路”组成。以上两种命名规则，必须保证在同一县（市、区）域范围内名字不重复。
（2）编号规则：路线编码由行政等级代码+三位编号+县级行政区划代码共十位组成，具体表示方法如下所示：
“C”：代表村道的行政等级代码；“101”：代表村道的排列顺序，采用“老路老编码，新路新编码”原则，老线路以及延伸段采用原有编码，新线路编码从“AA0”开始至“ZZ9”；“320125”：代表该县（市、区）的行政区划代码。
县（市、区）交通运输局根据各乡镇的实际情况拆分村道编码，确保县（市、区）域范围内村道编码的唯一性。
Неўзабаве скончыў перакладаць openstreetmap на клясычную (тарашкевіцу).
Спроба сыстэматызаваць тое што было, пасьлядоўна ды ґрунтоўна прайшоўся водле працы якую пачалі ўжо даўно. Пэўныя тэрміны, магчыма, будуць незразумелымі ці нязвыклымі, мэтай была ўжываць нашыя спрадвечныя адменьнікі, унікаючы калькаваньня.
Цяпер патрэбная вычытка, прыбраць хібу, якую я мог дапусьціць.
Пераклад ужо бачны на сайце, каб пабачыць трэба выбраць мову, яна ніжэй, пад “беларуская”. Перакладзены толькі сайт, не id-рэдактар, там нашмат болей працы, і іншы пляц для перакладу, не такі зручны як translatewiki.
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