In Leaflet, I really enjoy using Leaflet.Control.Layers.Tree and find its possibilities amazing. That’s why I’ve named the control I describe here Layertree. For now, I want to start small and document the learning steps I’ve taken with vanilla JavaScript. Since I don’t have much experience yet, feedback or suggestions for improvement are very welcome! I hope this post will be helpful to others who are learning as well.

Layertree Control

Base Layers

A base layer is the lowest map layer that provides the general background or geographic context — things like:

• Streets, buildings, rivers, landscapes
• Satellite imagery or simple map drawings

It serves as the foundation on which other data can be displayed as overlays (e.g., markers, routes, thematic layers).

There is already an official control, maplibre-basemaps, which, however, only supports raster sources. I want to make it possible to use vector sources as basemaps as well.

Here’s a simple code example showing how to create a custom basemap layer switcher in MapLibre GL JS to switch between different base maps (layers) — whether vector or raster.

… See full entry

About a week ago, I was thinking about the height of the buildings of my campus from above, especially in relation to the relatively flat terrain and skyline around Daytona Beach. Other then Embry-Riddle and the speedway, the only other ‘tall’ buildings are literally just hospitals that I can see two of from my sixth-floor dorm.

I had figured that the OSM state of the map seemed pretty good from a first glance, but looking at the F4map Demo showed me that some the 3D data was scuffed, for lack of a better term. Think: flat buildings and parking garages, ghost buildings in place of flat terrain, etcetera. I figured I could go in and correct some heights and roof shapes during class. While I was doing this, I noticed that a bunch of the building footprints were also misaligned (and some were just straight inaccurate), so I figured it wouldn’t hurt to fix those in later changesets.

My first changeset that involved actually editing the shape of buildings was my first polish pass on New Residence Hall 1. This dorm, along with New Residence Hall 2, has two rather obvious wings that are connected via a hallway bridge on every floor other then the first, where the main entrances are. The F4map had this missing for both the dormitories, and the editor revealed that NRH1 was being represented by two different buildings that shared a wall each with the bridge, which was also its own building, for some reason. It was relatively easy to delete two of the ‘buildings’ and extend the third to cover NRH1’s full footprint, and using building part tags to denote the wings and bridge seemed to do the trick for the 3D map. It was also around this time that I started switching often between Bing Aerial, Esri World, and Esri Clarity as my imagery source; some of these buildings were tall enough to obscure the sidewalks and bike parking nearby.

… See full entry

hi, hru :)

La mia proposta delle aree di protezione civile di qualche tempo fa, è attualmente in fase di draft ufficiale. Seguiranno le successive fasi quando avrò consolidato la proposta.

A voi il link della wiki osm.wiki/Proposal:Civil_Protection_Areas

When I was in Hyderabad and Bengaluru, I used to map the roads and buildings of the places in my hometown in Bhubaneswar.

Today, I got a chance to visit those places physically. It felt good on the mapping I did from more than a thousand kilometers away. Those road additions helped me add other features like adding streetlamps and POIs easily. I have an obsession with streetlamps 1.

Moreover, the early morning walk also has a new motivation now. I am using the Every Door and StreetComplete apps to add the POIs immediately as I walk past them. Thanks to these apps contributors.

I wonder, apart from streetlamp addition and road surface mapping. What else can I do?

ZuhaWorld Social Impact

The location and address belong to by ZwS Zuha and the ZuhaWorld Social Impact - Social Club Location and Surrounding Area. Full address is 265 Uttar Muradpur, Haji Lal Mia Sarkar Road, Muradpur, Dhaka, Dhaka Metropolitan, Dhaka District, Dhaka Division, 1204, Bangladesh.

Треба да се доврши:

• Додај/уреди долапе (ако постоје):
  • Долап код Кукурића врта (лијева обала) и узводно код јаза крај Студенца
  • Долапи на јазу у Дражин Долу, иза моста (нема их)
  • Долап на Придворачком краку, на јазу код трафостанице (нема га)
  • Провјери да ли је долап (на лијевој обали) на јазу, од ког ријека прелази у вјештачко корито (Рупе), функционалан
  • Покушај да ископаш називе
• Додај насипe/подзиде:
  • Требишњица од Мале бране до новог моста у изградњи
  • Придворачки крак кроз Растоке (додат)
  • Придворачки крак уз Брадвице и низводно до села (додат)
  • Придворачки крак од Придвораца до ушћа
  • Требишљица на Рупама
• Стазе:
  • Провјери проходност стазе на Рупама, од ушћа Поточине, преко јаза до кривине.

I thought there wouldn’t be much on my bucket list for 2025, but everything has turned into something magical that fills my mapper’s heart with joy. So much has been happening in our country lately—exhausting and heartbreaking events that test our strength as individuals and as a community. If only mappers could instantly make all our hopes happen, we would have done it already.

SOTM 2025 made me realize so many things: the effort every mapper puts in, the love they pour into their work, and the dedication to translating languages to make maps easier for everyone to understand. It reminded me that even small contributions can create big ripples. SOTM 2025 highlights the importance of mapping in so many areas: for disaster response, for raising awareness, for promoting inclusivity—by marking safe spaces for women and the LGBTQ+ community, mapping pet-friendly areas, and ensuring that no one is left behind.

Mapping is no longer just about roads and buildings;

… See full entry

3537133008

Tommy’s Hut Historical Landmark 1255 whittlesea Yea Rd Kinglake West

Hello! I have finally finished my work in Teton Pines! Unfortunately, I learned recently that there is a big construction project(s) going on there at the moment. So, I will likely be circling back to update the area when new imagery comes in.

On another note, I have been experimenting with adding wooded areas (natural=wood) in the mountains directly west of Wilson. I am feeling some uncertainty about this effort so if anyone with experience in mapping forests wants to take a look at the work I have been doing, I am more than open to advice and suggestions!

Anyways, with this finished I am now moving on to the area I am calling South central Wilson, which I have outlined in red on the attached image below. I have gotten a bit of a head start by mapping a majority of the ponds in this area. My work here will include the following: Adding water features, improving roads, adding houses/structures, and driveways. I will provide another update once this work is completed.

South Central Wilson Image: https://commons.wikimedia.org/wiki/File:SouthCentralWilson_OSM.jpg

La prise en compte des pénalités par les GPS

La plupart des GPS se basant sur les données OSM utilisent la signalisation routière et le marquage au sol (stop, panneaux, feux de signalisation, ralentisseurs, passages piéton, îlots, …) pour fiabiliser le calcul d’itinéraire et améliorer le temps estimé d’un itinéraire. La prise en compte dans les calculateurs se fait souvent via un système de pénalités impactant l’itinéraire en en associant une pénalité par défaut pour un type d’objets donné.

CoMaps regroupe les différents objets dans 7 types différents et OSMAnd applique une pénalité pour chaque type d’objets/valeurs possibles ce qui permet d’avoir une plus grande finesse.

Un travail d’ajout et de mise à jour dans la base de données est aussi nécessaire en utilisant les éditeurs ID/JOSM ou StreetComplete.

Contribution

J’ai souhaité contribuer à cette thématique notamment sur les clés valeurs crossing=* et traffic_calming=* suite à la prise en compte des pénalités dans CoMaps en m’appuyant sur l’outil Taginfo.

Taginfo est un superbe outil pour découvrir la richesse d’OSM (création de nouvelles clés/valeurs par la communauté) et réaliser un travail de nettoyage et de mise à jour sur des clés/valeurs peu utilisées car il permet de visualiser l’usage des valeurs les plus utilisées aux valeurs les moins utilisées.

Les contributions ont consisté à corriger les valeurs les moins utilisées (utilisées moins de 10 fois) s’apparentant à des erreurs.

Les erreurs rencontrées dans la base de données OSM sont :

… See full entry

Recently, ESRI World Imagery updated to include imagery from early 2025 in Gaza. Now, for the first time since the conflict escalated in October 2023, it is possible to update OSM using open satellite imagery to reflect the many features in Gaza that are destroyed or no longer standing.

If you are updating OSM in Gaza, please follow OSM lifecycle prefix conventions:

• For features (buildings, roads, etc) that are destroyed or severely damaged, please use the demolished lifecycle prefix: for example demolished:building=yes or demolished:highway=residential. This prefix is most appropriate in Gaza.
• A similar but alternative ‘destroyed’ prefix is only used for features that were destroyed by an event other than intentional demolition, such as a natural disaster. So this is most likely not appropriate in Gaza.
• Please do not delete: It is only appropriate to delete a feature if there is absolutely no trace of the original feature, and the land has been repurposed. Note that in many/all cases it will not be possible to tell if there is no trace of an object from satellite imagery, so features should be updated with a lifecycle prefix, and not deleted. See nonexistent features for more information. Eventually, if structures are rebuilt and no trace is confirmed, then deletion may become appropriate.

For now, it is important to avoid deleting features and use appropriate lifecycle tags in order to retain data OSM. In 2024, Humanitarian OpenStreetMap Team mapped all pre-conflict buildings in Gaza. If you need to access the full pre-conflict dataset, you can still access the data on HDX.

Thank you for the dedication in OSM, and Gaza.

The PCT exits Yosemite National Park though Dorothy Pass at the northern edge of the park. This marks the high point for through hikers after a 70 mile uphill. Statationed there with a National Parks trail crew this summer season I noticed that mapping data was sparse and inacurate. Water and campsite markings were esspecialy lacking.

I have made a number of additons and adjustements based on my notes from this summer and added ponds/streams where they are vissible on satilite data. Any stream marked as intermintet was personaly verified by me, otherwise I have left them unknown.

I belive that the avaiable tags for backcounty conditions are insuficiant and that there would be a use for a point of interest to indicate cellphone reception points in mountain areas.

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🚀 O Projeto Mapeia Brasil foi lançado!

Tivemos a alegria de apresentar nossa iniciativa em uma entrevista publicada no blog da OpenCage. https://blog.opencagedata.com/post/supporting-mapeia-brasil

O Mapeia Brasil nasce com a missão de atualizar e enriquecer os dados geográficos do OpenStreetMap, fortalecendo a comunidade e levando informação livre e colaborativa para todo o Brasil. 🌍

Na entrevista, eu (Raphael de Assis, presidente da UMBRAOSM) converso sobre: A motivação e trajetória no OpenStreetMap, Os desafios e as oportunidades de mapear ruas no Brasil, especialmente em regiões invisibilizadas; O projeto Mapeia Brasil: seus objetivos, metodologia e impacto esperado;

A importância do apoio global e colaborativo, e como iniciativas como essa podem transformar realidades locais.

Esse espaço no blog da OpenCage representa um reconhecimento importante para o Mapeia Brasil.

Ao divulgar a iniciativa em um canal internacional, conseguimos: Dar visibilidade ao trabalho da comunidade de mapeamento no Brasil. Atrair possíveis apoiadores, voluntários e parceiros interessados em geodados abertos.

Contribuir para que mais pessoas conheçam a importância de dados geográficos precisos e democráticos.

Link da entrevista; https://blog.opencagedata.com/post/supporting-mapeia-brasil

Site do Projeto: https://projeto-mapeiabrasil.mapaslivre.com.br/

In downtown Minneapolis, MN, USA, there are 80 linked blocks of connected buildings, making up the largest distance of indoor navigation in the world^[1]. The “Skyways” are a mix of interior hallways, unmarked tunnels, stairs, pedway bridges, and occasionally outdoor 2nd Floor paths which connect hundreds of local businesses. Each building sets its own hours and holiday schedules for it’s portion of the skyway.

There have been a few PDF maps and maybe a defunct app here and there. Sometimes the city publishes a list of businesses as PDF. But to truly improve the skyway, data needs to be accurate, editable, and updated for ever-changing city.

Skyway.run

I created Skyway.run (a web app) to make the skyway easy and fun to use. And an app that is easy to improve.

The app includes walking navigation filtered only to the skyway system, and highlights the changing hours and holiday/event schedule of each building. You can click a building and see the businesses inside, and easily jump to OSM to update the data.

Now I need help mapping the skyways.

Improving Skyway Data

OpenStreetMap is the data source for Skyway.run, and anyone can enroll as an editor to OSM. Once you create an account, there are a few ways you can help improve the data of the skyway:

• Delete businesses that are no longer operational and add new businesses moving in.
• Change the opening_hours for buildings and businesses as you walk past their signage.
• Update the walking footpaths and building shapes of the skyway system itself.

Starting with small changes like updating a business node is the best way to learn OSM editing. There are several editors for making changes, and each one has its own strengths. Try them out based on how you plan to map:

… See full entry

What are Super Mappers?

Update: This new feature is live on Tasking Manager as of 14 October 2025

HOT’s Tasking Manager is about to undergo the most significant user experience upgrade since 2020. A brand new Super Mapper level will be introduced, one step higher than ‘Advanced’ mappers and much more rigorously assessed.

Entry to this new mapper level will require you to attain a series of new badges, which are automatically allocated to mappers based on the number of objects mapped. Once you have the required badges, a human assessment will then grant access to this most prestigious of mapper levels!

Wait, badges? Yes, badges are also a completely new feature with this upgrade. Users will automatically attain badges once they have made a certain number of edits, for example: mapping more than 1,000km of roads will grant you a highways badge. Once you’ve attained a badge you’ll see it against your public user profile page on Tasking Manager.

This is how the badges and Super Mapper level will appear on your user profile page in Tasking Manager (once you have them!):

… See full entry

HeiGIT recently published an analysis together with the German Federal Agency for Cartography and Geodesy (BKG), comparing land cover data from OSM with the official CORINE Land Cover (CLC) dataset from BKG.

I want to use this opportunity to make an appeal to HeiGIT and similar projects analyzing OSM data: just because data is published by an authoritative (mostly government) source does not make it more correct than OSM.

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I’ve often observed that OSM is compared to external datasets, and the analysis is framed around the question of whether OSM is “right.” This framing does OSM a disservice, because it suggests OSM is wrong and the other dataset is right.

In reality, all open datasets I’ve compared with OSM—whether bicycle parking, public parking spaces, buildings, cycling infrastructure, or cycling routes—have always contained errors in both datasets. The reality is: the publishing authority has no inherent influence on data quality.

Of course, this does not mean such comparisons should be avoided. They are very useful and important. But I urge that the way these analyses are communicated be reconsidered. The communication must make clear that such comparisons are evaluations of both datasets, aimed at finding similarities and differences. It must be explicit that this is not an evaluation of correctness.

Correctness of data can only be checked through ground truth and usually by sample analysis. This is a lot of work, but only this approach can truly allow for an assessment of data quality.

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At this point, it would also be valuable for such analyses not only to acknowledge that all datasets contain errors, but also to highlight one of the central advantages of OSM compared to other datasets: how errors are handled once they are found.

… See full entry

Další ze stovek jiných dnu.