pnorman and stereo analysis of Changesets

Following the temporary interruption of Maxar Imagery Access for OSM edits, pnorman and stereo published in the last few days analysis by changesets of Maxar usage. They used OSM Changesets Data for the last 12 months to make partial analysis from of Imagery usage by country showing a concentration in some countries from Asia and Africa.

Synthetic view of changesets and by Objects edited, 2022

I wanted to react rapidly and present a synthetic view. My excuses if any inconsistancy in resuls. The data I have on hand was extracted from the OSM Planet changeset file ending in 2022 using my own version of changesetMD. Analysis for 2022 is grouped by Continent / Sub-Continent where I divide Asia and America for North and South (South-Asia + Oceania).

The tags variable in the file provides the source and imagery_used keys, both with references to imagery used as source. And you can have sometimes simultaneous references to many images (example: Maxar, Bing, Esri). This can come from JOSM which presents us with a list of all the imageries opened in our session or is simply the fact that the contributor indicates that he used more then one image provider.

What I present is also a brief analysis where I classiy sources as :

1. Maxar
2. Other Major Imageries (Bing, Esri, MapBox)
3. Others (all other sources - hard to classify rapidly)
4. Noref (no source indicated).

Previous analysis were based on the comparison of the number of Changesets by country. I do present results for both Changesets and Objects Edited (ie. no of Nodes, ways, relations edited). The variable num_changes (no. of Objects Edited) better represents the intensity of mapping. A changeset can contain only one building (5 objects edited) or thousand of objects edited.

Analysis by changesets

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Hello everyone, I am here again with the 4th 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 previous Outreachy Blogs before going through this blog post.

This blog post will help you to know me better and offer me job or internship opportunity according to my skills after I complete my Outreachy internship.

My skills and experience

Being a Computer Science and Engineering Student , I have learned a list of technical skills and am still learning more. As I believe that learning without implementation is worthless thus I have had experience of each skill that I have learned in the form of internships in various organisations. I welcome everyone here to have a look into my Resume to know about my experiences and skills in detail.

Opportunities I am looking for

I am looking for developer roles as well as technical writer roles . I will be interested to work and assist on job or internship related to any of the following domains : web development , app development , AI/ML , Cloud Computing or technical writing. I am eager to contribute my skills and assist in any capacity within these areas.

What makes me Unique for your organisation?

Below are some of my interpersonal skills which I consider as my strengths for an job/internship opportunity:

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Carried out some updates while in a different area. The sidewalks/ pavements were mapped separately from the associated road. This made it a pain to improve road alignment and routing results were not ideal. Using the sidewalk tag on the road object and joining a physically separate path object to it seems easier/clearer?

Last month, a friend and I started an Irish mappers’ “Stammtisch” called the Kilkenny History Mappers. It was his idea to have a regular in-person meeting mapping history, and I organized it.

I had sent a press release about the next meeting to our local paper (this is what they made of it, image not provided by me), and because everyone is connected here, the local community radio station contacted me and asked for an interview. I was hoping it was going to be a recorded one rather than live, because I’ve never done a live radio interview before, but alas…it was live. But it was fine.

His questions were good, I thought. It was lucky that I had mapped the area around his house. Well, maybe not so lucky, since I’ve mapped a lot, but it helped and made it relatable.

If anyone is interested, here’s the link. There are a lot of ads, because the radio is financed through them.

The audience of the radio station is probably 50+, to say the least, so I’m not expecting to recruit any new mappers, but it was nice of them to give us air time.

Last month, at SotMUS in Richmond, Virginia, I, along with Marjan Van de Kauter and Keara Dennehy, presented on “How to Use OSM Channel Data for Effective Communications”

Background:

The genesis of the project comes from Marjan Van de Kauter’s and my work piloting an OSM community engagement program for TomTom. To make sure we were communicating about TT’s organised editing correctly, we began tracking and organizing communications channels. As the list grew, we realized we needed a better tool, so we worked with a TomTom developer to build a webscraper that could show us in which channels the community was active.

Later, we brought Keara on board as a business analyst who could build a more robust tool to manage all of the data. By this time, we had realized that this information was something that the community could use at the global, regional and local level.

Then, when I left TomTom, but kept volunteering for the CWG and the OSM/F board on fundraising and communications, we saw additional applications for the data. So, we decided to create a proof of concept for a communication channel data store and present our first efforts and findings at the 2023 SOTM US in Richmond.

The Context:

As background, Marjan and I shared some of the results from the Communications Survey we conducted in May. I wrote about it here. Some of the findings were skewed, but we identified some interesting trends, including:

• Some respondents reported that they felt the forums have a hostile tone (35%)
• Many respondents said they were able to keep up with the conversations, both locally (60%) and globally (49%). Nearly 70% said that they got at least one useful response if they posted a question
• Respondents were more likely to read than post: 379 said they read daily or weekly and 152 said they posted daily or weekly
• Older respondents were more likely to use the Listservs or Community Forum, whereas younger respondents were more likely to use Discord or Reddit

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The Lilongwe University of Agriculture and Natural Resources Youthmapper was privileged to be among the YouthMapper chapters that attended the Malawi and South Africa Youth Mapper workshop that was scheduled between September 2 and 4th, 2022 at University of Malawi. The training attracted five youth mapper’s chapters from Malawian universities namely, Malawi University of Science and Technology, Malawi University of Business and Applied Sciences, Mzuzu University, University of Malawi and Lilongwe University of Agriculture and Natural Resources itself. The South African Counter Parts comprised of University of LImpompo as well as University of Pretoria.

The training was organized by Youth Mappers and USAID Washington and comprised of the delegation of Brent Mccuster, Zola Manyungwa, Ndapile Nkuwu, Adele Birkenes and Christine Urbanowicz.

It was aimed at imparting knowledge and sharing mapping experiences on ID editor, Java Open Street Mapping, QGIS and Kobo collect Toolbox, in facilitating improved contributions and utilization to the open source community activities. Chapter members that attended the knowledge exchange platform were tasked with training their fellow chapter members in their respective colleges, as a post training activity.

LUANAR YOUTH MAPPERS DELEGATION The three member delegation for LUANAR YouthMappers were Tarcizio Kalaundi, Susan Chibophe and Martha Chirwa. They share their experiences for the Youth mapper’s workshop.

‘It was an inspiration to network with chapter members across the universities, learning from the potentials of Youthmapper’s organization and our role as chapter members to keep the dreams of the founders alive and perhaps develop new motivations and aspirations from the limitless mapping world. My take home assignment was to inspire fellow youths to explore opportunities with Youthmappers.’Tarcizio Kalaundi, chapter president.

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YouthMappers A Bank of Sustainable Skills for students.

What I learned in YouthMappers when I was a student.

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;

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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

City of Meadville, Vernon Twp, West Mead Twp

##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.

Work in Progress

• 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.

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

• Skill Enhancement

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 .

• All about Open Source

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.

• No Gender Discrimination

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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.

Summary of geometries

Total : 504

• node:373 (74%)
• way:131 (26%)

Year of last touch

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

Unique contributors

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

Top 10 contributors (as per last touch) accounted for 54.76% of contributions. There were 132 contibutors in all.

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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.

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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.

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HOV lanes

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): osm.org/changeset/137988567.

Contraflow HOV lanes near Boston

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 osm.org/changeset/138024161.

I see two ways of mapping the HOV lane:

As a separate way along the interstate

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:

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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.

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1. Please do not use iD if you can. Use jOSM. iD sucks at arranging member order, and can cause a lot of havoc (e.g. node discrepancy)
2. Please always add the tag public_transport:version=2 for routes. That way others can verify your work more easily.
3. If you find there are other map features needing change, do those changes first. Keep your final change set clean with the bus route relation(s) being the only constituent(s).

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.

Urine deflectors

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I honored the invitation to help train some volunteers during the Lion Mappers Nsukka campus launch on the 6th of May, 2023. I taught them to map using the I.D Editor on HOT Tasking Manager, MapRoulette, and Mapillary mobile app. It was fun to meet them all. I made new friends. I went out to lunch with National Coordinator, Mr. Victor, and other coordinators () who came to assist with the training. One notable thing I gained is that I understood mapping more as I trained them, which confirms the saying that you learn from teaching. I also gained more confidence in public speaking. Thank you Unique Mappers Network for the opportunity.

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