There’s a saying in a certain article on the OpenStreetMap wiki that “tagging for the renderer” is equivalent to “lying to the renderer.”

Not only that, but the article also restricts the definition and meaning of “tagging for the renderer” as “the bad practice of using incorrect tags for a map feature so that they show up in the mapper’s renderer of choice. Such tagging goes against the basic good practice principles.”

I think that “tagging for the renderer” as a term should first be treated as neutral. On its own, there is no implication that “tagging for the renderer” forces us to lie to the system. Sometimes, people want to do tagging for the renderer simply because they want to place cool symbols around their area in OSM Carto.

Take me, for example.

Several months ago, I decided to download the entire openstreetmap-carto GitHub repository to analyze all of the (cool) icons contained within it and determine which tag combinations were needed to summon such icons on the OSM default map tile.

I found that the charging station icon was really cool. I loved its light blue color scheme, and its visibility on the map tile was quite good—it was already displayed at zoom level 17, on par with bank, gallery, and embassy icons.

I wanted to place this icon around my neighborhood soon. But alas, I didn’t know where any charging stations were located. So I shelved this idea for weeks and months.

Then, during a work trip to Bandung, while walking past the campus I attended as a student several years ago, I finally saw one. A charging station in the wild! It was stationed right in front of the parking area of the Labtek V building.

I was so elated—it felt like finding a legendary Pokémon in the wild! At that moment, I immediately stopped walking, opened Vespucci, and mapped the charging station.

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UMBRAOSM Brazilian Openstreetmap Mappers Union provides several video classes on its YouTube channel. Access our content and enjoy mapping!

Video lessons for mapping objects in OpenStreetMap.

How to map buildings using the Buildings_Tools plugin in the Josm Editor

https://www.youtube.com/watch?v=nVPdf9MjvjQ

How to map a neighborhood boundary in OpenStreetMap with a custom background layer.

https://www.youtube.com/watch?v=sTe-1N2QvLY&t=2s

How to map in OpenStreetMap with the help of Mapillary images using the ID editor.

https://www.youtube.com/watch?v=dmDW5LhfQpk&t=52s

How to customize the colored painting style to offset street names in the JOSM Editor.

https://www.youtube.com/watch?v=4jOnFjtuI10&t=57s

Enabling remote control and expert mode in the JOSM editor

https://www.youtube.com/watch?v=H8qL_l18f7c

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Con motivo del Open Data Day de este año invité a diferentes instituciones educativas de la Comarca Lagunera para recibir talleres de mapeo básico entre el 1 y el 7 de marzo.

El taller “Mapeando tu escuela” lo impartí en:

• Universidad Autónoma de la Laguna, el 5 de Marzo.
• Universidad Tecnológica de La Laguna Durango, el 7 de Marzo.

Espero más universidades se sumen a este evento el siguiente año.

مياه

سكن رعوي

صفيح زيقوا

En un reciente análisis publicado en mi blog, exploré la distribución de piscinas en Santa Cruz de la Sierra utilizando datos de OpenStreetMap. La hipótesis detrás del estudio es que la presencia de piscinas privadas puede ser un indicador del nivel socioeconómico de una zona, considerando los costos asociados a su construcción y mantenimiento. Puedes leer más sobre esto en el artículo completo aquí: ¿Dónde están las piscinas?

Previo al análisis, dediqué aproximadamente tres semanas a mapear alrededor de xxxx piscinas en el área metropolitana de la ciudad, utilizando JOSM para la edición de datos. Este esfuerzo fue clave para mejorar la cobertura de OSM en la región y asegurar que la base de datos reflejara con mayor precisión la distribución real de estas infraestructuras. Durante este proceso, utilicé imágenes satelitales (Imágenes aéreas de ESRI mundial).

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مناطق رعوية قديمة

25/3/15-25/3/16 高野山の光明院という宿坊にて開発合宿を決行。

Please note: This blog post is part of a series of blog posts about the new OSM file format “OMA”. This is the second post. At the end of the article you’ll find links to the other blog entries.

 

This time I will give you an example of how to query Oma files. I wrote a prototype of a library for working with Oma files. I called it OmaLibJava.

To explain how to use this library, let’s say, we want to create an overview map of all the power facilities in a certain town.

 

The Classical Approach

The classical approach with OSM files would be, to first reduce the size of the file by creating a smaller file containing only the data of interest. This is typically done in two steps: remove everything that is not a power facility / remove everything that is not in the town. The order of these two steps is not important for the result, but might have a huge impact on the duration of the process.

Although it is not necessary – or even counterproductive – this can easily be done with Oma files too. For example, the following small Java program extracts all power facilities of Germany:

import java.io.*;
import de.kumakyoo.omalibjava.*;

public class ExtractPower
{
    public static void main(String[] args) throws IOException
    {
        Extractor e = new Extractor("germany.oma");
        e.addExtract(new BlockFilter("power"),"power.oma");
        e.run();
    }
}

Running this program on germany.oma on my computer takes 8.5 seconds. It creates the file power.oma, which is about 22MB in size and contains all power facilities of Germany.¹

Let’s have a closer look at the program: the library contains a class called Extractor, which reads an Oma file (here germany.oma) and writes several extracts simultaneously (here only one, called power.oma).

An important part is the filter BlockFilter("power"). This tells the extractor to keep only elements with the key power. I’ll tell you more on filters in a moment. But first I want to show you why you don’t need this step.

 

… See full entry

My edits are not git commits.

If anyone that is interested in knowing my change set history I would be more than happy to send them a link to one.

The ability to edit my bio and profile picture are all the personalization that I require.

Since OKANA is finally open next door, I think it might be time to bring this landmark’s map up to snuff

I am no expert on indoor mapping but I will research and try my best, flagging for review any edits I’m unsure of.

Feel free to help!

Objectif

Sur une idée de benoitdd, faire des stats sur les changeset ayant modifié des adresses en France en 2024

Méthodo

Sur OSMCha, préparation d’un filter (une requête) avec :

• filtre sur la modification de tag addr:street ou https://wiki.openstreetmap.org/wiki/Tag:type=associatedStreet
• filtre sur la France
• filtre sur date pour récupérer 1 seule journée (sinon retour trop gros, pb de timeout + limitation à max 500 changeset dans le retour de toute façon)

Puis avec un script ruby, en utilisant l’api OSMCha :

• boucle sur les jours du 01/01/2024 au 31/12/2024
• mise à jour des dates de début date__gte et de fin date__lte dans la requête “aoi” grâce à l’endpoint PATCH aoi_partial_update
• récupération des changesets grâce à l’endpoint GET aoi_changesets_list
• lecture du geojson pour extraction en tsv des infos intéressantes

Puis traitement sur excel

Résultats

Le tableur des données brutes est dispo ici : https://lite.framacalc.org/osmfr-adresses-2024-adcm

j’y ai cru mais ça ne marche pas !!!!!

Par exemple le filtrage par type=associatedStreet ne trouve pas les changesets avec des créations de relation, uniquement les modifications, bizarre. Sur un autre exemple, le filtrage par addr:street=* inclut un changeset créant 3 nodes, mais qui n’ont pas ce tag dans leur version #1, bizarre aussi.

Bon, ben on continue avec ces updates relativement au hasard 😅

Ce mappeur OpenStreetMap DÉNONCE certaines mauvaises utilisations de ces panneaux à Seraing - Une petite sortie live écourtée où je montre des panneaux “zone de rencontre” mal utilisés aux Biens Communaux. J’avais prévu quelque chose d’un peu plus long au départ, mais un des panneaux avait été rectifié entretemps et je me suis retrouvé bien con lorsque je l’ai vu sur place 😅

Améliorons Seraing (sur OpenStreetMap) - Épisode 42 (Entre mise au point et trottoirs) - Une session OSM classique qui était plus un prétexte pour parler des derniers mois d’un point de vue personnel et d’annoncer quelques changements prévus pour la chaîne Youtube

Projet OSM #1 : ce mappeur AMÉLIORE le Domaine d’Épinlieu à Mons (sur OpenStreetMap) - Première (et pour le moment seule, j’y viens) vidéo d’un nouveau concept où je prends un quartier ou quoi et montre toutes les modifications que je fais dessus jusque la fin du “projet”

Le “problème” de ce concept est que avant de faire cette vidéo, j’ai effectué un boulot conséquent à Chapelle-lez-Herlaimont pour mettre à jour principalement des bâtiments qui étaient mappés assez sommairement (des rangées de maisons étaient simplement de gros blocs avec aucune adresse, mauvais tags, bâtiments manquants, etc) et ça a pris un bon lot d’updates et évidemment de temps pour arriver à mon but initial. C’est de ce projet hors écran que m’est venu l’idée d’enregistrer certains projets plus modestes pour Youtube et montrer un avant/après.

… See full entry

Toutes les modifications OSM générées via ce profil sont faites dans le cadre d’acquisition de données des SERM. Pour plus d’informations au sujet de ces modifications: osm.wiki/France/Gares_SERM

Зачем же? Поправить мои правки!

Не так давно я добавил магазины сети Батон на карту, а сейчас начал расставлять магазины сети Русский Разгуляйка.
Проблема? Я расставлял POI с точностью до адреса дома, а не до двери. Поэтому, если кому то нечего делать, приглашаю вас рассмотреть мои пакеты правок^[3][4][5][6], и обращаясь к Яндекс Панорамам (или любым другим источникам данных) разметить POI’шки точнее, к дверям.
Буду рад помощи, и спасибо!

upd 14.03.2025

самостоятельно поправил магазины сети “Батон”

Went back to Henderson to finalize the updates. I think i updated all i could with out starting to assume details. Also some mappers suggested straightening out the roads, so i did that across the entire town.

Henderson, Nebraska

Final Edit:

as a reminder, this is how it started:

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Source: https://gurs-import.karlas.si/project/1 (previous URL: https://osm.karlas.si/project/1)

• YYYY-MM-DD = date of import
• XXXXXX_X = number of task in Simple Task Manager
• Name of the settlement
• N i. b. = number of imported buildings according to the source.

Changesets/imports:

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在博客中查看

这个OpenStreetMap变更集的范围原本应是12*8km，范围不超过福州四区的福马路部分。但在我编辑地图期间有人修改了台州部分的104国道，八杆子打不着的地方硬是因为一个104国道的“关系”需要在发布变更时选择使用本次编辑亦或是使用上个版本的编辑（放弃这次修改）。这两个选择极具迷惑性，不会有超出选项栏提示字以外的更多解释。且ID编辑器没有第三个选项，你不能同步后再修改。

相同的逻辑，如果我分解了连霍高速连云港路段作为路堤，但在我发布这些修改前有人在伊犁的连霍高速入口增加了收费站路段分割车道。我的变更集范围岂不是就扩大到半个中国了？这时候，任何人，在伊犁以东南，连云港以西，徐州以北的范围点击网站顶部导航栏的“历史”就能看到这个本应该是连云港范围的变更集莫名其妙的就出现在了历史列表里？

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Tenkeli (Тенкели) Mapping Project

Overview

Over the past 3 weeks I’ve discovered, researched and mapped out the area of the abandoned Russian town of Тенкели, located in the middle of Siberia.

The location had only a rough outline of the town mapped along with the airport runway and main road. There were no buildings, no roads and the landuse was tagged incorrectly. The quarries were tagged as ‘landfills’. Apart from that, the nearby settlement, Суор, was also not even tagged. I decided to take matters into my own hands.

I found this video which proved a great help in learning the history and details of the place. Based on this, satellite imagery and images scattered along random, long forgotten forum websites (as well as TimeMachine snapshots from tenkeli.ru), I pieced together the most (if not only) accurate map of this settlement.

I plan to continue this project until the entire area is detailed up to a standard I deem sufficient

Changes made

• Added nature landuse in the vicinity
• Removed unsupported and old tags
• Added every building in Тенкели/Суор with their respective tags
• Added the road system with specified smoothness and surface types
• Added lakes/reservouirs
• Adjusted rivers
• Cleaned up existing things

Stats (as of 11/03/2025)

1. Changes - 41 266
2. Changesets - 67
3. Average Changes/Changeset - 615,91
4. Average Changeset/Day - 3,7

To Do List

1. Improve the river system near Суор
2. Fix the mediocre nature tags in the area
3. Specify building tags around Суор and the industrial area below Тенкели
4. Find addresses and street names (If anyone has any information on that, contact me)

Before (General)

… See full entry