i was able to contribute in the mapping of Abi LGA in Cross Rivers State and also attend the mapathon meeting in Nsukka Enugu via zoom

It was a wonderful experience mapping and I represented quite a good number of buildings on the map.

This diary entry was formerly titled “Sock puppet accounts on OSM”.

What is a sock puppet account?

A sock puppet account is defined as a person whose actions are controlled by another. It is a reference to the manipulation of a simple hand puppet made from a sock and is often used to refer to alternative online identities or user accounts used for purposes of deception. Online, it came to be used to refer to a false identity assumed by a member of an internet community who spoke to, or about, themselves while pretending to be another person.

The use of the term has expanded to now include other misleading uses of online identities, such as those created to praise, defend, or support a person or organization, to manipulate public opinion, or to circumvent restrictions, such as viewing a social media account that they are blocked from, suspension, or an outright ban from a website. A significant difference between a pseudonym and a sock puppet is that the latter poses as a third party independent of the main account operator. Sock puppets are unwelcome in many online communities and forums. https://en.wikipedia.org/wiki/Sock_puppet_account

Why do people create sock puppet accounts?

One reason for sock puppeting is to circumvent a block, ban, or other forms of sanction imposed on the person’s original account. A sockpuppet is a false online name and profile created to hide the author’s identity, usually because of personal, political, or financial ties to whatever is being discussed or reviewed. (News Literacy Project, Para. 2)

Sock puppet account vandalizes OSM

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I’ll mostly be fixing railroads on OSM, like improving alignment of train tracks so they’re better aligned with those shown in aerial imagery. Most railroads on OSM were imported from TIGER and may not align very well with train tracks shown in aerial imagery because most TIGER roads and rail lines were mainly used for taking census surveys and not for drawing actual alignments of roads and train tracks. I fixed a few rail lines by adjusting the train track nodes and adding new nodes to the train track ways so they’re better aligned with aerial imagery.

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I am sharing some of my favourite OSM-related tools/websites/apps with a very brief description, including the most popular ones (you never know). I’ve certainly forgotten many of them and don’t know as many.

Italian version

Websites

• overpass turbo: Fundamental website for database queries. Also useful for custom QA filters.
• taginfo: Check which tags are most used, their usage over time, the most used values for each tag etc. For the history of a tag there is also this site.
• RapiD: iD on steroids. Reports possible missing buildings and streets.
• osm-revert: Revert entire changesets (it replaced Revert UI which is no longer supported).
• Level0: Revert individual nodes. It is also a useful text editor for changing several tags at once. However, read this first.
• NotesReview: Filter OSM notes by user, date, text etc. There is also a site by Pascal Neis.
• Disaster Ninja: Not its main purpose, but there is an interesting layer called ‘Building Quantity’ in case you want to find areas with unmapped buildings.
• YoHours: To simplify the compilation of the opening_hours=* tag.
• How Did You Contribute: Stats about users. There’s also your changes’ heat map.
• Is OSM up-to-date?: Interesting site created by an Italian that tells you which nodes are less up-to-date. If there is nothing to update you can still leave a check_date tag.
• Field Papers: Edit OSM by taking notes on paper.

Renderer

• F4map Demo and OSM Buildings: In case you want to see the 3d tags rendered.
• Indoor=: In case you want to see the indoor=* tags rendered.
• Open Etymology Map: Another site created by an Italian. It renders the name:etymology tag. There is also a site that facilitates tagging it.

Wiki

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In a comment on their recent diary entry publicerination suggested that use of leisure=pitch with sport=tennis was always intended for single tennis courts. I had my doubts given that someone in San Francisco was adding quantity, and I have added pitch:count and there is also a documented tag courts. Were we just the odd mappers out?

A relatively quick way to answer this was looking at tennis courts in the UK as I have a 1-2 year old import available for Great Britain. Overpass can also be used to collect the data, but it’s not possible to calculate areas directly. I ran a query which pulled tags, the geometry and the area of each pitch in square metres and saved this first as geojson and then as a csv file.

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Wasted my time

I can’t get this crap to let me look up anything not even my own address. What is up with this? And y’all want a donation? For what ?

The setup

This diary is a follow on to my previous entry detailing Adding addresses with JOSM and MapWithAI. You’ll need all of the setup there plus the Conflation Plugin.

Finding a good area

The key to doing this quickly is to find an area with:

• High quality address data with good spatial positioning
• High density of building outlines to act as targets for the address data
• Extremely low current address density (resolving conflicts is important but does slow you down!)

The area I’ve been spending most of my time recently is Phoenix, AZ which has great address data from the [National Address Database] and a high level of building coverage. The suburb are also quite sprawling which means you can cover a lot of very regularized ground very quickly. Here’s a good candidate for rapid addition:

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Versão original em português: PlayzinhoAgro está morto

Not physically dead, but I am no longer an active mapper.

For the past three years I have dedicated myself intensely to OSM and it has been an amazing experience. However, it has been exhausting and I was only able to continue thanks to the Brazilian Mastodon community.

Having so much time to dedicate to mapping has been a privilege, but recently I was diagnosed with Autism and I’m planning to move away to enter university. Before that, I will finish importing the buildings in Fortaleza and do one last address import. The data from 90 cities, including 20 with building footprint data, will be available on Github, mostly under CC0 license.

The UX/UI designs are available on Github and I will continue to maintain and improve them for a better proposal.

The OpenCollective will remain open until the end of May, when I plan to finish all ongoing projects. Currently, I receive about 170 reais (about 33 dollars) per month. To continue I would need five times that amount, i.e. about 800 Reais ($158). Unfortunately, this amount is extremely low and if I can’t reach my goal, I will have to take a break from my work with OSM and look for a paid job.

Thank you for the opportunity to be part of this community and for all the support I have received so far. I hope to be able to continue contributing in the future.

https://opencollective.com/playzinhoagro

I haven’t used this diary up until now, but better late than never! Figured it was time to start logging my mapping projects. :)

One of the first things I noticed when I was starting to map sport pitches in the Bay Area was the use of the quantity= tag. It was often used to map multiple pitches under one area instead of mapping each pitch individually. I’ve also seen it used to note how many of the same pitches were near each other. For example 3 basketball courts next to each other would all have a quantity=3 tag. Although I’ve seen the latter usage far less.

Mapping multiple pitches under one area makes the map less accurate, as the leisure=pitch tag is only supposed to be used for one pitch.

I’ve been fixing pitches mapped with this tag for a while when I came across them. But yesterday I learned how to use overpass turbo and now I’m able to find every pitch using the quantity= tag far more easily. I’ve been spending last night and today fixing every pitch with a quantity= tag and plan to finish fixing them in the next few hours.

Example

These 3 tennis courts were all mapped out using one tennis court area with a quantity=3 tag. In order to fix this I swapped out the leisure=pitch tag for a landuse=recreation_ground tag to turn the area into a recreation ground.

I then swapped the quantity=3 tag for a courts=3 tag, which in contrast to the quantity= tag is a registered tag on the OSM wiki.

Lastly I mapped each individual tennis court. In this case I also added a barrier=fence tag to the recreation ground.

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This was a concrete lot 2 years ago. It is now low-income apartment building with 59 Apartments. Address 335 W 11th Ave. Eugene Oregon 97401

Edit: The imagery, according to one commenter, needs permission from the governement to be able to use it, my bad for mentioning a WMS link that i though had an open license to it.

Edit 2: Someone uploaded the database of Montreal buildings. Thanks for everyone that helped.

i swear i might have a dream of me just adding buildings in OSM but can i like, get some help with adding the buildings because this is gonna take too long. if anybody is actually reading this then if you want to help me, add buildings using Geodesie Quebec satellite as its 100% accurate , you just need to add parameters for it to function as custom satellite. https://servicescarto.mern.gouv.qc.ca/pes/services/Territoire/RESEAU_GEODESIQUE_WMS/MapServer/WMSServer

I’m slowly catching up with the mass of data I’ve collected over the past couple of years - uploading footage to Mapillary and the use of OSMUK Cadastral Parcels have improved my editing but vastly increase the time it takes to edit the map. Plus I’ve found other things to do in my spare time.

I’m probably going to pause my Isle of Wight edits now, work on some south of Basingstoke, then try to make it out to Farnborough, Woking, and Wokingham to make sure my data isn’t out of date before editing the map round there.

In my last diary post, I had written about the beginnings of mapping milk churn stands. This was kindly featured in the weeklyOSM 662 which resulted in a bit more attention from the OSM community from several countries. Thanks for all your kind comments!

Progress

When I ran an overpass-turbo query on Easter Monday, I noticed a sudden increase of mapped milk churn stands in Finland, a considerable increase (which has still grown more). I checked the changeset history to see who had caused this, found out it was user houtari and sent him a message to thank him. What followed was a very interesting exchange about milk churn stands in Finland. He even sent me a link to a most interesting article in Finnish, kindly translated by a certain popular translation website, but I’ll give you the original link, so you can decide what to use:

• Maitolaituri oli paljon enemmän kuin maidon keräyspaikka

It also led us to translate the wiki page into Finnish.

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OpenStreetMap (OSM) is an invaluable resource for geospatial data, providing free and open access to information about our planet. One interesting aspect of OSM is its ability to track the history of changes made to objects in its database. As someone curious about geospatial data, I’ve been exploring ways to visualize this data in a more intuitive manner. Recently, I decided to experiment with GPT-4, a state-of-the-art language model by OpenAI, to see if we could come up with a fresh approach to visualizing OSM data history. In this blog post, I’ll share my initial attempts, examples of the traditional OSM Deep History table, and the new visualization I created with GPT-4’s assistance.

Traditional OSM Deep History Table

The standard OSM Deep History page presents data history in a tabular format. While it’s a helpful tool for understanding how objects in the database have evolved, the table format can make it difficult to quickly grasp changes and trends in the data. The table includes a row for each version of the object, with columns for different attributes. As a result, finding meaningful insights can be challenging.

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Normally the edit button on the osm website is hidden on phones. That’s because you probably don’t have any remote-control-capable editor installed and iD is unusable on small screens. What you’re supposed to do instead is open the Share tool and tap the Geo URI link. This will let you launch any app that understands Geo URIs such as Vespucci.

But to my surprise I was able to use iD on a phone. My note viewer has a tool to open iD on the current map location. It should work similarly to the Edit button except it won’t disappear if the screen is too small. Actually it is hidden by default because too many tools would clutter small screens. But you can always add it back by pressing the ⚙️ button.

When I opened the link, I noticed that iD looks differently compared to what you usually get on a phone. I expected to get that oversized sidebar covering most of the screen. Instead I got everything scaled down to fit on the screen. That happened not because of any changes in iD but because note-viewer opens iD differently.

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It has been a busy time for OpenStreetMap Zimbabwe Community forging ahead to set it’s foot within the Global OpenStreetMap Family. This year started enormously with the introduction to the Anticipatory Response Program for Muzarabani.

OpenStreetMap Zimbabwe is one of those communities that is still emerging and testing the waters in pursuit of a safe landing space. I am sure it’s all smooth surface but not so easy to be well established. Starting up a community or resuscitating one is no little work; you sweat it out, you cry it out and you scream it out. Only commitment and dedication will see you through the winning point. Over the last couple of years, OpenStreetMap Zimbabwe has been active in terms of the YouthMappers Chapters. Vivid and energetic, the young mappers have been very enthusiastic, raising their home flag high. This year, tables should turn or rather tables should balance.

OpenStreetMap Zimbabwe jump-started this year at a climatic point with the first massive Mapathon ever which also served as an introduction to the Anticipatory Response Program for Muzarabani. The community which gathered at the University of Zimbabwe on the 20th of March 2023, made tremendous efforts to put Muzarabani on the map. The tasks cleared way for the Disaster Response Deployment which then took off the next day in the Muzarabani District. The occasion was rich in attendance (80+) from various institutions and organizations like the Chinhoyi University of Technology, Midlands State University, Harare Polytechnic, University of Zimbabwe, Zimbabwe Institute of Geomatics, Surveyors Institute of Zimbabwe, independent participants and supported by the Eastern and Southern Africa Hub (ESA). Training was led by Deogratius Kiggudde while the Zimbabwe Steering Committee and ESA (Jomokela Kennedy, Wilson Munyaradzi, Michael Osunga) chipped in to attend to the floor. It was a huge success.

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Preface

User Watmildon recently posted their conflation workflow with the new hospitals dataset in the HIFLD, and as such I thought I’d share my own process of converting these datasets into an OSM-readable format.

Workflow

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