OpenStreetMap
Планирую актуализировать информацию по Парку Горького:
Буду рад если кто-то ещё подключится.
YouthMappers A Bank of Sustainable Skills for students.
I have never forgotten what happened when I was a student that day in the afternoon. I can’t unveil the whole incident without highlighting what caused it and in this case, YouthMappers started it. In fact, that was in the 2nd year, when YouthMappers continued to give students an equal opportunity to thrive and find their path in their career side. In my case, I don’t regret that I chose YouthMappers as a student over many other organizations. Career-wise, I wanted to be a computer or Data scientist but the University never gave me the chance to choose what I wanted, therefore I was pushed into Records and Archivist management and I graduated as an information specialist.
In YouthMappers as a student, I learned different skills in both academics and leadership. I have never learned any course related to mapping or GIS in my profession, but I freely acquired these skills from YouthMappers. Further, among the most important things YouthMappers value is inclusive and equal access to opportunity. I came from a background that has nothing to do with geospatial and geography but I was allowed to join YouthMappers and gained a lot of skills which I have also taught to many communities. As a student, I acquired skills from theories and practical points of view without learning them in class but through YouthMappers, open source, and mapathons.
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I was curious about the usage of Maxar over the last year, so did some quick work to see where it was used. To start, I used a Python 3 version of ChangesetMD to load the latest changesets into PostgreSQL, using the -g option to create geometries.
I then, with a bit of manual work, identified the changesets of the last year are those between 122852000 and 137769483. Using this, and knowledge of tags normally used with maxar, I created a materialized view with just the Maxar changesets
CREATE MATERALIZED VIEW maxar AS
SELECT id,
num_changes,
st_centroid(geom)
FROM osm_changeset
WHERE id BETWEEN 122852000 and 137769483
AND (tags->'source' ILIKE '%maxar%' AND tags->'imagery_used' ILIKE '%maxar%');
This created a table of 2713316 changesets, which is too many to directly view, so I needed to get it by country.
I did this with the border data from country-coder
curl -OL 'https://raw.githubusercontent.com/rapideditor/country-coder/main/src/data/borders.json'
ogr2ogr -f PostgreSQL PG:dbname=changesetmd borders.json
This loaded a quick and dirty method of determining the point a country is in into the DB, allowing me to join the tables together
SELECT COALESCE(iso1a2, country), COUNT(*)
FROM maxar JOIN borders ON ST_Within(maxar.st_centroid, borders.wkb_geometry)
GROUP BY COALESCE(iso1a2, country)
ORDER BY COUNT(*) DESC;
In the past I made the mistake that I took pull requests of foreign language support I do not speak or am at least not good enough at.
Thus I now added more features using English language and I would like to have people translating this to French, Spanish and Russian accordingly.
Please contact me if you can help.
Sven
En Internet se encuentra el logo de Wikipedia en modo real, o sea, la esfera de rompecabezas impresa en 3D, y yo siempre había querido hacer algo equivalente para OpenStreetMap, el mapa y la lupa en modo real. Como he utilizado el logo de OSM para crear pines o calcomanías, he utilizado el archivo SVG e identificado los pliegues del mapa, los cuales son particulares desde una perspectiva del origami (papiroplexia realmente). Sin embargo, un día mientras leía Twitter, vi en la cuenta de Massimo un pliegue para despliegue de satélites, llamado Miura Fold. Lo mejor de esto es que eran exactamente los pliegues del logo de OSM.
Me puse a buscar cómo hacer este pliegue y adaptarlo a OSM. Primero siguiendo las instrucciones del doblez el cual es originalmente para una proporción de papel diferente (no cuadrado), por lo que me tocó hacer ajustes para encontrar la forma de hacerlo para un papel cuadrado.
اصلا فاقد اهمیت
##Completed## • Landuse has been filled in on the map. • Buildings have been added using RapID. • Roads have been updated with ref:penndot and unsigned_ref tags.
• Addresses are a work in progress and is a very time consuming task. • Business POIs.
When I first started mapping this area, there was very little mapped. Allegheny College, retail centers, and a few other isolated areas were the mapped exception. It’s been a fulfilling opportunity to map undermapped communities, especially in the Appalachia region.
Смотрю в этих ваших ютубах различных путешественников, и периодически обращаю внимание на то, что у ребят появляется острая необходимость в питьевой воде! Cтранно, да? 😁
Кто-то вынужден объезжать населенные пункты и тратить время на поиски колодцев, колонок и родников, а кто-то не парится и набирает воду из рек.
Насмотревшись путешествие на велосипеде Андрея Едунова Москва-Владивосток, где он набирал воду на АЗС и реках, задумался о написании данной статьи.
Он кстати является активным пользователем мапсми, проданного в итоге левой компании. Очень рад что разработчики объединились и на основе исходных кодов сделали замечательный Organic Maps (github).
Всё же вода из родника будет по-вкуснее.
Если по какой-то причине перестали загружаться изображения, то можно воспользоваться сайтом web.archive.org. Предусмотрительно сохранил страницу там.
Помните - не все колодцы и родники являются безопасными. Изучите и почитайте в интернете, как определить пригодные для питья родники и колодцы.
Всегда держите в аптечке средства от расстройства желудка и противомикробные препараты для кишечника.
Раз уже пошла речь, начну с него.
Можно скачать с Google Play, F-Droid, AppStore, Huawei AppGallery или отдельно .apk с github.
Сам стараюсь устанавливать приложения с F-Droid, так как они самостоятельно скачивают и компилируют из исходных кодов. И в целом свободное и открытое программное обеспечение (FOSS) рулит!
Что такое F-Droid, как его установить и пользоваться, можно почитать на их сайте, в википедии или 4pda.to.
Главным преимуществом данного приложения является его чрезвычайная легкость. Это самое оптимизированное, и от того сберегающее заряд батареи приложение. Что очень важно для путешественников.
Скачанные карты занимают очень мало места.
Например:
Hello everyone, I am here again with the 3rd Blog of my journey as an Outreachy intern. For those who don’t know me , I am Neelima Mohanty , selected as an Outreachy intern at Humanitarian OpenStreetMap Team (HOTOSM) for the May to August Cohort. If you are new to my blog then make sure you read my Blog 1 and Blog 2 before going through this blog post.
Recently a person named Berra Karaman messaged me on LinkedIn that she is interested in applying as an Outreachy intern and wished to know more about my application and journey .
On reading her message , I thought that not only she , many other applicants also must be wondering about applying to Outreachy and some may also be thinking to apply to work at the organisation I am working at as an Outreachy intern. So , I decided to introduce my community to a newcomer who decides to apply in HOT(Humanitarian OpenStreetMap Team) as an intern in the upcoming Outreachy cohorts.
Here are some important perks of being an Outreachy intern at HOT
This is a place where your skills are not only appreciated but also allowed to implement them at a fixed paced , not too slow and not too fast. My mentors never compel me to hurriedly complete a task . Of course deadlines are set and we together try our best to complete the tasks in an efficient manner before the deadline but if it gets completed partially then we again conduct a meeting , discuss the agenda and make changes accordingly to the schedule in order to complete the work .
Other than working on the project , I get to learn a lot new things related to open source and the community . For instance , my mentor Rob Savoye shared his experience of attending the SOTM-US-2023 and Petya Kangalova shared every single details of the open source conference FOSS4G which she recently attended . They give me tips regarding these conferences and the open source community.
I did lot of contribution data analysis on Wikipedia. I wanted to do similar thing for OSM. Finally, here is my first analysis. I downloaded the fuel outlets data as of 2023-07-07 from OSM in Andhra Pradesh using overpass-turbo query. I used google sheets to analyse the data. Here are some results. 
Total : 504
Year Count
2008 1
2011 8
2012 17
2013 23
2014 6
2015 23
2016 29
2017 23
2018 59
2019 52
2020 48
2021 54
2022 83
2023 78
year Unique contributors
2008 1
2011 5
2012 5
2013 6
2014 2
2015 6
2016 10
2017 10
2018 18
2019 19
2020 28
2021 8
2022 24
2023 10
Top 10 contributors (as per last touch) accounted for 54.76% of contributions. There were 132 contibutors in all.
Hello!
This is my first blog post and it will be about AI and how to use it to map buildings in New Zealand rapidly!
Some of you might already have heard that there is a better version of the iD editor available called Rapid editor (by Facebook) which is a lot faster than iD but uses the same user interface.
The cool thing about this editor is that it enhances the map with datasets that are AI generated and are suggested to you.
I have started mapping a lot of buildings in New Zealand in the last couple of weeks and I love how fast it goes.
Since there is still a lot to do, I would like to ask you for your help.
This is the link that brings you directly to the editor with the dataset already loaded: Rapid Editor
Get started by Login, zoom in, click on a yellow marked building and press a key to accept or d key to ignore (much faster than clicking on the button on the left sidebar). Some buildings need some adjustments as the AI suggestion is not 100% accurate but in my experience in 99% it is good.
More info about Rapid Editor can be found here: https://developers.facebook.com/blog/post/2023/04/04/rapid2/
I’m looking to hear about your mapping experience!
Nowadays, crosswalks are often drawn in an X shape to accommodate pedestrians.
And here we have an entire area designated as a crosswalk.
There’s been an OpenStreetMap presence on Twitter and the Fediverse/Mastodon for years. And in the last few months, the @OpenStreetMap account on Mastodon/Fediverse has gotten much more engagement on Mastodon compared to Twitter.
The OSMF has had a formal policy committment to use open communication channels for 3+ years, but it’s important to also use closed platforms if it helps reach people. So where are the people?
As part of my work for the OSM Communications WG, I maintain some OSM social media channels. For several months, Mastodon engagenment has been much higher than Twitter. Here’s some raw data and examples.
(Here I show the number of retweets/boosts (🔁) and stars/likes (⭐) posts get on Mastodon (🐘) and Twitter (🐦))
The important OSMF post about recent Maxar imagery unavailability got about the same, ( 🐘 4🔁 3⭐ vs 🐦 5🔁 7⭐, but Mastodonians like OSMF internal posts about the 2023 Screen to Screen. 🐘 9🔁 5⭐ vs 🐦 1🔁 1⭐, or the post about the OSMF SSRE’s first year, got 4 times as many boosts/retweets 🐘 23🔁 17⭐) vs 🐦 4🔁 8⭐.
State of the Map is also a popular topic, with Mastodon toots out-performing Twitter tweets. From general “Have you been to SotM?” posts (🐘 12🔁 11⭐ vs 🐦 3🔁 6⭐) to requests for new host bids reach more people on Mastodon (🐘 16🔁 12⭐ vs 🐦 7🔁 23⭐
This analysis is just the tip of the iceburg. Compare the OpenStreetMap mastodon account to the OSM Twitter account to see more examples. Don’t forget: The “number of followers” on Twitter is 10 times higher than the on Mastodon (84K vs 6K), and yet Mastodon is reaching more people, and driving more communications.
Others in OSM have seen this. Pieter Vander Vennet showed how WeeklyOSM was increasingly linking to Mastodon, rather than Twitter. Geomob podcast episode № 171 described the “amazing” difference in engagement they got on Mastodon versus Twitter.
According to wiki, hov=lane is
“Deprecated and nonstandard. If seen on a way, this value should be removed; instead,
hov:lanes=*is the preferred tagging for HOV access restrictions per lane.”
This makes sense as with this value, it’s not clear which lanes require HOV. There were ~8k road segments with the value, all in the US. I’ve systematically replaced them with the more specific hov:lanes, here’s a history graph: https://taghistory.raifer.tech/?#***/hov/lane. Some of the ways already had hov:lanes, so I removed hov=lane; the majority had a comment in note:lanes like “left lane is hov” (probably from an import), so I used it to set the lanes; and for the rest, I checked the images (Bing/Mapbox/Mapillary) to set the correct lanes. All the changes were done manually (often in bulk).
One more complicated case was in Alexandria, VA where two streets have their right lanes designated to HOV during certain times. Mapillary allowed me to update those correctly with a tag like hov:lanes:forward:conditional = ||designated @ (Mo-Fr 16:00-18:00): changeset/137988567.
The last 80 segments are the most complicated yet. They are for a part of I-93 south of Boston, MA: https://overpass-turbo.eu/s/1wXB. The complication comes from this: note:lanes = during rush hours, 5 lanes (left one hov) in peak direction and 3 in off-peak direction. This is confirmed by Southeast Expressway HOV lane, whereas Boston I-93 HOV Lane has an image of it.
I’ve mapped the permanent barriers between the directions in changeset/138024161.
I see two ways of mapping the HOV lane:
but in the opposite direction. Even though it’s one lane of the already mapped road (in the opposite direction), there is always a physical separation (present when the lane is open), so it makes sense to map it separately; also there is no interaction of these two directions. Tagging is simpler with this approach:
I started taking on mapping commissions and I want to do those with a different user account. JOSM doesn’t have built-in support for multiple user accounts, so I created a script for it that lets me switch without pain. It works on a typical Linux setup or other *NIXes such as macOS, not on Windows.
It modifies JOSM’s preferences.xml file to change your credentials, and then launches JOSM. You create one copy of this script for each OSM user account, and run those instead of launching JOSM the normal way.
I created two files with this script in a directory in my PATH and made them executable: once as ~/.local/bin/josm and once as ~/.local/bin/josm_commissioned. For Linux desktops: If you want, you can also create .desktop files in ~/.local/share/applications so you can run these scripts easily from your main menu or launcher. Feel free to share those in the comments!
Find the OAuth key and secret in JOSM’s preferences XML file, and fill them in in the script. Especially for macOS, you may need to change the JOSM_PREFS and JOSM_EXECUTABLE paths.
如题，苏州市内的快速路全都被更改成了高速公路类型。这个错误十分明显，但现在好像没人改（ 请阅读wiki再进行编辑，有关道路类型的页面是有中文翻译的。 我的josm为什么连不上代理啊啊啊
Ein OpenStreetMap-Nutzer hat via Hinweis gefragt, wie denn die Nummerierung hier zustande kommt.
Zitat: “Der Hardweg endet mit Hausnummer 15 und der Weißdornweg beginnt mit Hausnummer 17. Ist das in der Realität wirklich so?”
Da ich vor 1,5 Jahren diese Erweiterung des Wohngebiets gemappt hatte, wollte ich der Sache auf den Grund gehen.
Tatsächlich ist es so, dass der Hardweg nicht mit 15 endet. Stattdessen gehört die Nummer 17 ebenfalls noch zum Hardweg - und das, obwohl das Wohnhaus mit seiner Grundstücksauffahrt bereits an der als “Weißdornweg” beschilderten Straße steht (Foto von der markierten Kreuzung Richtung Norden):
I spent the last week with my band in Nice in France playing in an Irish pub, but since we only played late in the evenings, that left plenty of time for some mapping.
The general impression of the quality of mapping in Nice from my Irish (i.e. living and mapping in Ireland) perspective is that the basic mapping is very well done: buildings, house numbers (probably an import), building heights even (most probably a data import), bilingual street names, ebike locations, some street lights, some bins, most businesses. I can only speak for Vieux Nice (i.e. the Old Town) here, because that’s where we spent most of our time.
We used OSMAnd for navigating on foot to find the tram stops, pub, hotel etc which worked fairly well. It wasn’t always the most direct route, but it always got us there.
I used OSMAnd for mapping mostly, but it wasn’t ideal, because I didn’t qualify for the live updates in the short time I was there, so it was a bit tricky to remember what I had already mapped, as to not create duplicates. I had to use it in combination with EveryDoor which at least showed what I had mapped, even though I couldn’t use it to map more of these specific things, because there are no presets in EveryDoor. I also created gpx tracks to know which of the little streets I had already walked and where I had already mapped guard stones.
