Yesterday which was the 5th of August, 2023 we ha our weekly mapathon. This holds every Saturday of every week. I trained our newbie from last week on how to use Maproulette and how to map road. Then I also opened a new account and trained a newbie yesterday on how to map. We had two newbies yesterday but I could only open an account for the other because our time was up. We all also had refreshments and had fun mapping. We were a total of 6.

I attended the monthly coordination meeting that took place on the 5th August from 9:45am-11am. The Agenda for the meeting 1. Map Nigeria Mapathon Project -progress and concerns 2. Other community Activities- 3. Reports from Mapathon centers/State Chapters/Campus Team 4. SotM Nigeria 2023-updates and Actions required

I also invited 2 persons to attend the meeting. It was quite nice.

There’s lots of software around to work with OpenStreetMap data - querying it, creating maps from it, using it for navigation. One area that there has historically been less support is analysing OSM changeset data. As an example, here is one of mine.

However, many years ago Toby Murray wrote ChangesetMD. That can be used to maintain a database of changeset information (tags, discussions, etc.). Martijn van Exel updated that to a recent version of Python and I made a couple more changes to support very recent Python versions and made the replication more scriptable.

Downloading changeset data

Over on the planet.osm.org site, there’s a download for all the changeets generated at the same time as the weekly “planet” file is created, and also one for all the changeets and discussions as well. The changesets-only one is just over 6GB (bzipped), and the one with discussions as well is only about 250MB more, because most changesets don’t have discussions.

If you’re not interested in changeset data dating back to 2012 you don’t need to download this file; you can just start replicating from whatever point in the past you are intereted in starting from.

Installing the software

If you’re on Debian or Ubuntu, you’ll likely want to follow these instructions from a non-root user account of your choice (substitute that account for “youruseraccount” in the instructions).

Running it for the first time

From the virtual account created by the installation, which you can reenter by running

cd /home/${youruseraccount}/src/ChangesetMD
source .venv/bin/activate

Run something like this

python changesetmd.py -d changesets -c -g

The “-g” is optional and initialises the database to store geometric data. “changesets” in the line above is just the database name.

Loading a changeset dump file

To load the database with changesets and discussions:

python changesetmd.py -d changesets -g  -f ~/data/discussions-latest.osm.bz2

… See full entry

Added lots of building in SA between anderson loop-huebner and I10-NW Military HWY. Will continue adding in sections until SA buildings are filled in completely.

ฟิวแฟคอฟฟี่

I participated in the coordination of the conference state of The Map Nigeria in preparation for the Conference

Magic Earth is an Android App that used OpenStreetmap as it’s mapping source. Unfortunately many streets i travel either had no speed limit or a value that was in ERROR. So tonight I joined OSM and learned how to edit Speed Limits on streets. To my surprise I racked up 27 changes to post.

Editied OSM again this week.

I’ve spent time at Sargent Park (Winnipeg, Canada), and noticed a lot of missing pathways, which I can use on a bike or walking. I’ve made several updates to paths, roads, parking, fences, building names, facility names, etc.

I’m quite happy with the changes.

I haven’t found a good android app for OSM, either. Someone must know something decent– a kind of google maps competitor.

Today I came to think again about on-demand bus service areas. There is one mention on the OSM wiki: this explanation from Belgium, but I’m not sure if it really refers to a service area rather than a line with on-demand stops. The idea of the on-demand bus service area is that from one central stop a small bus will take you wherever you want to go, almost like a taxi, but only at certain times, and together with other passengers (if there are any). The concept has been quite common for some time in rural areas all over Europe. In my opinion, we could just draw the area, give it some tag so it is put down in the data that this rural area is generally accessible by public transport.

Mapper BroccoliB did so here, and his attempt was also what made me think about it again.

The reason I came across his edit was that my wife and I had a day off and used it for a bike ride through the sparsely-populated area north-east of Wolfsburg, just across the former border between West and East Germany. It was nice cycling along the Mittellandkanal - but I have to say that we are quite used to gravel tracks and have equipped our bikes with appropriate puncture-safe tyres. Some excellent pear trees along the road here. No traffic at all because of a road closure further south. When we came to the nearest larger village, we had to decide if we wanted to continue on the road in heavier traffic now or use a track running parallel. To our surprise (it wasn’t mapped as such yet), it had excellently smooth asphalt. For the way back we had opted for a bus line that also carries up to five bicycles (for free!). It’s really amazing what the land of Saxony-Anhalt with its limited resources and sparse population does for an attractive public transport. Lower Saxony could take a page from its book!

🗺️🦀 Witajcie, społeczność OpenStreetMap,

Dziś dzielę się z Wami moim najnowszym projektem, osm-yolo-crossings — nowym narzędziem wykorzystującym zaawansowaną technologię AI do samodzielnej detekcji i mapowania przejść dla pieszych (zebry) w OpenStreetMap. Po udanym imporcie budynków w Polsce za pomocą AI, przyszedł czas na poprawę bezpieczeństwa pieszych!

Dzięki mocy detekcji obiektów YOLOv8, to narzędzie automatyzuje mapowanie brakujących przejść dla pieszych na naszych mapach. Z imponującą precyzją wynoszącą ponad 99,7%, jest w stanie zaimportować około 88% wszystkich wykrytych przejść. Pozostałe 12% jest odrzucane z powodu niskiego poziomu pewności. Dzięki inteligentnemu filtrowaniu, system ten jest niesamowicie wydajny. Na przykład, jest w stanie zmapować całą Polskę w ciągu zaledwie dwóch miesięcy, używając pojedynczego serwera bez karty graficznej. To AI pracuje mądrze, a nie ciężko!

Przykładowy zestaw zmian.

… See full entry

🗺️🦀 Hello OpenStreetMap community,

I am excited to share with you my latest invention, osm-yolo-crossings — a new tool that harnesses cutting-edge AI technology to autonomously detect and map pedestrian crossings (zebras) in OpenStreetMap. After the successful AI building import in Poland, it’s now time to expand and improve pedestrian safety!

Leveraging the power of YOLOv8 object detection, this tool is designed to ensure that we no longer miss pedestrian crossings on our maps. With an impressive >99.7% precision rate, it’s able to import around 88% of all detected crossings. The tool discards the remaining 12% due to low confidence levels. Thanks to smart filtering, this system is incredibly efficient. For instance, it can map the entirety of Poland in just about two months using a single server without GPU. This is AI working smart, not hard!

See an example changeset.

… See full entry

背景

大约两周前通过Subway Validation检查工具发现长沙地铁部分地铁关系出现严重错误。这里涉及的编辑包含138741823、138790779等。

尝试了解动机，通过在138741823的评论、站内消息和编辑者有少量沟通。猜测是因为线路是单线，没有拆分成上下行两条线的原因。另一位在138790779也有英文提问，未有答复。从过往的编辑历史看，不是故意破坏，应该只是对地铁关系的规范或iD编辑器不熟悉导致的错误。

问题

目前发现1号线的部分问题。总结如下

1. 1号线开福福区政府 –> 尚双塘方向线路关系被删除。
2. 1号线线路关系中的地铁线被删除。
3. 添加了重复的1号线主关系，原始主关系和新主关系。新主关系错误，用的是type=route标签，而不是type=route_master，而且主关系中错误的加入了地铁站点。
4. 添加了重复的1号线线路关系。开福福区政府 –> 尚双塘方向原始关系(已被删除)和新关系。尚双塘 –> 开福区政府方向原始关系和新关系。新线路关系未添加地铁线。

其他线路的类似问题

1. 2号线光达 –> 梅溪湖西方向线路关系被删除
2. 2号线主关系被删除
3. 4号线单方向线路关系被删除
4. 4号线主关系被删除
5. 5号线的单方向线路关系的所有标签被删除。添加了重复关系。
6. 磁浮快线单方向线路关系被删除，之后添加了不完整的新关系，新关系后续被其他编辑者修复
7. 重复添加的西环线

参考规范

• osm.wiki/China/Transport/Urban_Rail_Transit
• osm.wiki/Metro_Mapping

With the new release of more than 59 million points of interest (POIs) from Overture, consisting of Microsoft and Meta POI datasets combined, the natural question arises: how can this be useful for OpenStreetMap?

Challenges to consider

The most important challenge in getting this data into OSM is making sure the place labels in Overture have an equivalent in OSM. This is mostly doable with automation, but many cases require context.

Validation of these is a forthcoming challenge: street-level imagery from Mapillary will be especially helpful, but being there in person to validate is also a big advantage. That aside, even if the data can be added to OSM one-by-one (not imported) with validation, the tags need to have a proper format.

Loading up the data to analyze

I got started by referencing Feye Andal’s great and succinct guide on viewing the data in AWS Athena. I found a slight lack of clarity in the instructions: you need to make sure your Athena instance, and your S3 bucket where queries are saved, are on us-west-2 region, same as the Overture dataset, unless you copy the dataset first to a bucket in your other region. So make sure the regions are the same, and the instructions should work flawlessly!

Analyzing the data

Exploring the dataset, there are 1037 unique place labels in it. 86,000+ are structure_and_geography which can refer to a wide range of natural geography or built structures in OSM, difficult to match with any specific tag without context. Others translate directly, such as a laundromat.

Some example tags include: "forest", "stadium_arena", "farm", "professional_services", "baptist_church", "park", "print_media", "spas", "passport_and_visa_services", "restaurant", "dentist"

To get most of the tags matched, I used Python to import the OpenAI module, and connect to my OpenAI account, which charges a few fractions of a penny per request.

I set a system message, which defines the role the AI should play or assume. My message was:

… See full entry

Pre začiatok tu máme všetky oficiálne trasy KST a SCK. Tie majú dohodnuté značenie a tagovanie.

Následne sú tu náučné chodníky ktorých systém značenia sa líši. Áno väčšina náučných chodníkov je značená zeleným backslash. Stretol som sa už aj s takým chodníkom, ktorý značenie nemal a trasa bola len na náučnej tabuli.

Lokálne trasy sa tiež značením líšia od miesta k miestu. Niektoré sú označené len pomocou smerovníkov alebo route_marker. Niektoré sa nachádzajú len na nejakej tabuli.

Náboženské trasy, ktoré sú dôležité pre pútnikov, ale bežným turistov len zavadzajú na mape, pretože sú väčšinou neznačené.

Bežecké trasy, ktoré sa behajú raz za rok.

Vlastné trasy.

Mtb trasy tiež väčšinou v teréne nie sú značené. Trasy sa nachádzajú buď len na tabuli s mapou, alebo na internete.

Odlíšenie ciest, po ktorých je v národnom parku povolené pohybovať sa na bicykli. Jeden nemenovaný požívateľ pridáva trasy v národných parkoch. Nie sú to ale cyklotrasy, ale cesty, kde je povolené v návštevnom poriadku národného parku pohybovať sa na bicykli. Je toto vhodné riešenie?

Mestské cyklotrasy, ktoré nie sú značené v teréne, ale len niekde na stránke mesta/obce.

Mestské cykotrasy, ktoré majú vlastné značenie.

Cyklochodníky vybudovené za nejakým účelom spájajúce rôzne miesta ako súčasťou relácie cyklotrasy.

O reláciách cyklotrasy, na ceste, kde sa dobre bicykluje ani nepíšem, pretože tá v OSM jednoducho nemá čo robiť.

• route=hiking
• route=running
• route=foot
• route=bicycle
• route=mtb

Po sprístupnení DMR 5.0 prišlo obdobie, kedy konečne začali byť v lese viditeľné lesné cesty, mnohé prírodné úkazy, zrázy, skaly a mnoho iného. Po čase sa mi ale naskytá otázka: “Mapovať každý jeden objekt, ktorý je vidno na DMR 5.0?”.

• Máme mapovať každú jednu dieru v zemi?
• Máme mapovať každú jednu lesnú cestu?
• Máme mapovať každú jednu baňu a hlušinu pred nimi?
• Máme mapovať každý jeden vrchol?
• Máme mapovať každé jedno koryto potoka?
• Máme mapovať každú jednu skalu?
• Máme mapovať každý jeden strom?

A to všetko bez overenia v teréne?

Viem, že nie je v ľudských silách prejsť všetky vymenované veci, ale fakt majú byť všetky v OSM?

It seems that there is only one instruction for getting fresh Sentinel-2. It tells you quite well how to prepare images, but it is difficult to explain how to use them in OSM editors. So after step 7, you can do

without GeoTIFF and tile server

1. Select in QGIS: Processing->Toolbox->Raster Tools->Generate XYZ tiles (MBTiles)
2. Set the parameters:
   • to Extent of the map area you need.
   • Maximum Zoom is most likely 15.
   • In Output Path, specify where to save the tile file
3. Click Run and wait for rendering to finish.
4. Install the mbtiles plugin in JOSM
5. Open the file you received in step 3.

By the way, recently Guru Maps learned how to tear off MBtiles https://gurumaps.app/blog/2023/06/14/mbtiles

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But if you still want a tile server, you can do without tileserver-php from the instructions. And without the QTiles plugin, it will also work faster!

Classic tiles with a web server

1. Select in QGIS: Processing->Toolbox->Raster Tools->Generate XYZ tiles (Directory)
2. Set the parameters:
   • to Extent of the map area you need.
   • Maximum Zoom is most likely 15.
   • Set Output Directory. You can immediately select the directory of your web server.
3. Click Run and wait for rendering to finish.
4. Start your web server. If you didn’t use Nginx or Apache, open the folder with your tiles in the terminal and try using the web server in Python: python -m http.server 80 or PHP: php -S 127.0.0.1:80
5. In JOSM, open Preferences->Layers->+TMS
6. Enter a URL like this: http://localhost/<tile folder name>/{zoom}/{x}/{y}.png
7. Get closer to the desired area in JOSM and select your new layer from the Layers menu.

p. s. I used QGIS 3.32.1-Lima.

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upd: method from @maraf24

Classic tiles for JOSM without a web server

Instead of starting the web server, specify the following URL in JOSM: file://<absolute path to the folder with tiles>/{zoom}/{x}/{y}.png

Кажется существует единственная инструкция по получению свежих снимков Sentinel-2. Она неплохо рассказывает, как подготовить снимки, но сложно объясняет, как использовать их в редакторах OSM. Поэтому после шага 7, можно обойтись

без GeoTIFF и тайлового сервера

1. Выберите в QGIS: Processing->Toolbox->Raster Tools->Generate XYZ tiles (MBTiles)
2. Задайте параметры:
   • в Extent нужную вам область карты.
   • Maximum Zoom скорее всего вам нужен 15.
   • В Output Path задайте куда сохранить файл с тайлами
3. Нажмите Run и дождись завершения рендеринга.
4. В JOSM установите плагин mbtiles
5. Отройте файл полученный на шаге 3.

Кстати, недавно Guru Maps научился отрывать MBTiles https://gurumaps.app/blog/2023/06/14/mbtiles

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Но если вы тайловый сервер всё-таки хочется, то можно обойтись без tileserver-php из инструкции. И без плагина QTiles, что будет ещё и быстрее работать!

Классические тайлы с веб-сервером

1. Выберите в QGIS: Processing->Toolbox->Raster Tools->Generate XYZ tiles (Directory)
2. Задайте параметры:
   • Задайте в Extent нужную вам область карты.
   • Maximum Zoom скорее всего вам нужен 15.
   • Задайте Output Directory. Можно сразу выбрать директорию вашего веб-сервера.
3. Нажмите Run и дождись завершения рендеринга.
4. Запустите ваш веб-сервер. Если вы не работали Nginx или Apache, то откройте в терминале папку с вашими тайлами и попробуйте использовать веб-сервер в Python: python -m http.server 80 или PHP: php -S 127.0.0.1:80
5. В JOSM откройте Настройки->Слои->+TMS.
6. Введите URL вида: http://localhost/<имя папки с тайлами>/{zoom}/{x}/{y}.png
7. Приблизьтесь к нужной вам территории в JOSM и в меню Слои выберите ваш новый слой.

p.s. я использовал QGIS 3.32.1-Lima.

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способ от @maraf24:

Классические тайлы для JOSM без тайлового сервера

Вместо запуска веб-сервера в JOSM можно указать URL вида: file://<абсолютный путь до папки с тайлами>/{zoom}/{x}/{y}.png

This OSM diary is an English translation of Yekastreet’s OSM diary post called Sobre el “Mapping Workshop 2023”. Translating and re-posting because I enjoyed it so much :D

A reflection of YEKA and our journey…

Among the many kilometres of routes we have mapped in the seven years since Youthmappers started, our own journey as YEKAStreetMGA continues to surprise and please us the most. We have grown as a team, from our first mapathons in the barely equipped classrooms of the university, to the partnerships we are now forming with our local mapping networks. Design by design, we make the use of open data tools a little more accessible. Through methodological design (a term unthinkable for us in the early days), we have now transformed our first university meetings into structured processes to disseminate and share our knowledge with a new community of mappers.

What we have experienced as students, as women, in a socio-political context that routinely places us between non-functional institutionalism and the uncertainty of self-management in educational processes, reaffirms once again that teaching is a highly political act. Empowering. Essential in the construction of new models of society. And, in a country where making community is a crime, mapping and locating ourselves is in itself an act of humanitarian rebellion. Here we are, here we exist, more than planimetry and satellite rasters. We are vectors on the map, with direction and meaning. And our dedication and commitment to cultivating and growing the community in Central America overcomes the risks and dangers.

Central America yes, because when we speak of Latin America we make invisible the particular individuality of Central Americans, we exist between Mexico and South America, and although we share, we are indisputably different from the rest of Latin America in our struggles, way of life, needs and challenges.

… See full entry

wow!

i’m loving open street maps! never gave it the time of day before ;)

Una reflexión de YEKA y su recorrido…

Entre todos los kilómetros de trayectos que hemos mapeado en estos últimos siete años desde que iniciamos con Youthmappers, nuestra propia trayectoria como YEKAStreetMGA es la que nos llega con mayor sorpresa y gratificación. Hemos crecido como equipo, desde nuestros primeros mapatones en las aulas apenas acondicionadas de la universidad, a las alianzas que estamos formando ahora con nuestras redes locales de mapeo. Diseño a diseño metodológico, para hacer un poco más accesible el uso de las herramientas de open data. Empezando por el uso del término diseño metodológico, que era impensable para nosotras en nuestras primeras reuniones de universidad que ahora se han transformado en procesos estructurados para divulgar y compartir nuestros conocimientos con una nueva comunidad de mapeadores.

Lo que hemos vivido como estudiantes, como mujeres; en un contexto sociopolítico que rutinariamente nos coloca entre la poco funcional institucionalidad o la incertidumbre de la autogestión en los procesos educativos, nos reafirma nuevamente, que enseñar es un acto altamente político. Empoderador. Esencial en la construcción de nuevos modelos de sociedad. Y en un país donde hacer comunidad es un crimen, mapear y ubicarnos es en sí, un acto de rebeldía humanitaria. Aquí estamos, aquí existimos, más que planimetrías y rásteres satelitales. Somos vectores en el mapa, con dirección y sentido. Y nuestra dedicación y compromiso a cultivar y cosechar comunidad en Centroamérica se sobrepone a tales riesgos y peligros.

Centroamérica sí, porque cuando hablamos de latinoamérica invisibilizamos la individualidad particular de los centroamericanos, existimos entre México y América del Sur, y aunque compartamos somos indiscutiblemente diferentes del resto de América Latina en nuestras luchas, modo de vida, necesidades y retos.

… See full entry