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 ?

Je suis sur le point de partir pour le GR 10 et je m’apperçois qu’il manque un grand nombre des horaires d’ouverture des magasins dans les villages que traverse le GR 10. C’est une chose qui peut être très importante; aussi mon objectif est-il de compléter un maximum ces données. Si d’autres veulent se lancer dans l’aventure, ce serait formidable.

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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Оказывается дополнять карты - это круто. Наконец-то вчера добавил дорожки в рощу рядом с домом. Давно смущало что на карте были указаны не все.

English version: PlayzinhoAgro is dead

não está morto fisicamente, mas estou deixando de ser um mapeador ativo.

Durante os últimos três anos, dediquei-me intensamente ao OSM e foi uma experiência incrível. No entanto, tem sido desgastante e só consegui continuar graças à comunidade brasileira do Mastodon.

Ter tanto tempo para dedicar ao mapeamento foi um privilégio, mas recentemente fui diagnosticado com Autismo e estou planejando mudar de cidade para entrar na universidade. Antes disso, terminarei a importação dos edifícios de Fortaleza e farei mais uma última importação de endereços. Os dados das 90 cidades, incluindo 20 com dados de buildings footprint, estarão disponíveis no Github, a maioria com a licença CC0.

Os projetos de UX/UI estão disponíveis no Github e continuarei mantendo e melhorando para uma proposta melhor.

O OpenCollective continuará aberto até o final de maio, quando pretendo terminar todos os projetos em andamento. Atualmente, recebo cerca de 170 reais (cerca de 33 dólares) por mês. Para continuar, precisaria de cinco vezes mais, ou seja, cerca de 800 reais (158 dólares). Infelizmente, esse valor é extremamente baixo e, se não conseguir atingir minha meta, terei que dar um tempo no meu trabalho com o OSM e procurar um trabalho remunerado.

Obrigado pela oportunidade de fazer parte desta comunidade e por todo o apoio recebido até agora. Espero poder continuar contribuindo no futuro.

https://opencollective.com/playzinhoagro

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.

… See full entry

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.

… See full entry

GeoRSS

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.

… See full entry

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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About HIFLD

OSM power user SherbetS has been documenting the HIFLD dataset. It is a large corpus of public domain licensed geospatial information about infrastructure around the United States.

Get all the data into JOSM

Download the dataset in GeoJSON format here. Fire up JOSM and open the file. This will create a layer that is just the HIFLD data. If won’t have any fields that look like OSM fields so DO NOT upload this directly.

Next we need to get the OSM data into JOSM. For this demo we will use the data for the state of Wyoming.

• Click the green download button to open the Download dialog.
• Click the “Download from Overpass API” tab at the top.
• In the Overpass text box put something like:

// fetch area “Wyoming” to search in
{{geocodeArea:Wyoming}}->.searchArea;
// gather results
(
  // query part for: “amenity=hospital”
  nwr["amenity"="hospital"](area.searchArea);
  // query part for: “amenity=clinic”
  nwr["amenity"="clinic"](area.searchArea);
);
// print results
out body;
>;
out skel qt;

• Hit the “Download into new layer” button at the bottom

We now have 2 layers. One with the HIFLD data and one with the OSM data.

Finding unmapped items with the conflation plugin

We will now use the Conflation Plugin to match the nodes in the HIFLD dataset with OSM downloaded elements. Any elements that do not match to an OSM item should be reviewed and additions made. Any matched elements may be reviewed for completeness in OSM but that’s a separate matter.

We will start by selecting elements from the HIFLD dataset that are in our state of interest (“WY” in this case) and add this to the Conflation tool as the “Reference”. This is the set we’re trying to match elements to.

… See full entry

I did a number of edits to stop signs, yield signs, speed bumps and a path today.

… See full entry