OpenStreetMap (OSM) is fun and fantastic for so many reasons. One being able to roam around the world from the comfort of your chair. I started mapping on OpenStreetMap in 2015 by coincidence through a friend. And OSM later became part of my work at Mapbox. Where I went through out the world as an armchair mapper. I used to maintain a list of interesting places as I encountered them. Then map it later when I am free. Here are my 3 memorable OpenStreetMap edits.

Valparai, Tamil Nadu, India

Tea plantations in Valparai by Thangaraj Kumaravel | Image license: CC BY 2.0 Deed

I have been to Valparai several times as a kid during summer vacations. It’s surreal and beautiful. My uncle’s place there used to be at the top of the hill, above the clouds itself. You won’t be able to see the road when it is cloudy. We used to play hide and seek in these gigantic guava trees. Or maybe they felt gigantic as I was a kid then. Trees were our targets because leopards were regular visitors and we were not “technically” allowed to go out of house plot.

Valparai hence was one of the places I always wanted to map due to cherished memories. Which is what I did. I have put in hours here to map detailed map features. Rekindling the memories while doing so were worth the time I have put into adding data here.

Screenshot of Valparai in openstreetmap.org

My edit

Screenshot of my edits on Valparai in openstreetmap.org

Pettineo, Sicilia, Italy

Image of Pettineo in Wikipedia Image details: © LigaDue | License: CC BY-SA 3.0 Deed

I came across Pettineo, Sicilia thanks to end user feedback from Mapbox maps. Amazing place. At least from the satellite imagery, it was. To my surprise, it was not mapped at all when I looked at it in JOSM. The edit I did here was far far more grander than Valparai. Or that’s how I remember it. What I didn’t know was that JOSM somehow hadn’t loaded the data of the place. Almost 4ish hours or so of my time resulting in duplicated data as I realised I have mapped over the original data. My edit was extremely detailed over the original data as I recall it. But it did not connected to any data that was already present. Merging felt far more complex and I had to revert my edit.

After the initial panic and changeset revert, I did edit Pettineo again, it was not as large as my first edit since I didn’t have to map half of it. I was just relieved that I was able to fix it as soon as I messed up.

Screenshot of Pettineo in openstreetmap.org

My edit

Screenshot of my edits on Pettineo in openstreetmap.org

Dierks Lake, Arkansas

Dierks Lake, Arkansas, USA Image details: © Recreation.gov

Over the years, I have created a huge interest in natural features. Especially water bodies. It started with one of my first few edits where I added some of the swimming pools in Delhi which hosted most of the foreign embassies in India.

Dierks Lake, Arkansas came through work as well. It had only extremely bare geometry. Which I hate in a waterbody. Or anything natural. Whether it is a waterbody or a tree, they have distinct shape and geometry which should be celebrated. Editing the entire lake was around ~2ish hours of work IIRC. Dierks Lake’s mapping was the reason I became a fan of waterbody mapping. And hence has a sweet spot in my heart.

My edit

My edit on Dierks Lake, Arkansas, USA ## What’s next? Once you have maps in your life, you will see it everywhere. Apart from some of the map related projects I have been working on, I wanna restart mapping in OSM. Especially natural features like forests, water bodies etc. Here is to creating more map memories.

Mapping Cary’s Downtown Park

First Contribution

This was my first attempt at trying to map out a public park from the original CAD drawings attempting to draw out this map by hand using JOSM. If there’s a way that I could trace polygons from QGIS and be able to save them, I’ll probably end up trying to go that route.

What I Learned

1. AutoCAD files aren’t always geocoded
2. GeoParquet files are your friend
3. Geodatabases are your best friend
4. Don’t trust Aerial Imagery, field surveys

Bar soria

Részletek / details:

https://wiki.osm.org/Hungary/20231204

Someone should really praise me for the incredible job I’m doing of mapping a shitload of POIs in my neighborhood

Also, how do I put smileys, on here ?

Let’s take a look at addition and division mapping of natural and landuse. First we will look at the inconveniences that exist when mapping such areas. Next we will look at the method behind division mapping and scenarios of how to apply it. And finally take a real world example of how these two mapping styles were applied.

The definition of addition mapping is the act of adding new data to a white spot area aka an area with no data.

The definition of division mapping is the act of taking an existing object and dividing it down into smaller partitions.

Inconveniences when mapping natural and landuse

There are two main inconveniences when mapping natural and landuse from aerial imagery. First, depending on the resolution of the imagery, deciding where to make a clear cut if it is a distinct natural or landuse area. And second, the amount of clicking required to create a new area.

For the first inconvenience, more or less, it is personal choice and level of details. E.g. try to answer this question: when would one make a distinction between natural = scrub and natural = wood? The difficulty exists in the fact that the value scrub permits trees and lots of time these trees are/aren’t growing close enough to each other.

For the second inconvenience, lots of editors have the option to split a way (aka division mapping). In JOSM you can split an area with ALT+X (UtilsPlugin2 required). Or manually split the circumference of an area at two nodes and then separately connect the two arcs.

UtilsPlugin2 - Split Object tool

Let’s say one needed to create 4 square farmlands in a grid layout. How many node clicks are required?

Mapping the traditional way (aka addition mapping) 16 node clicks are required. One square has 4 nodes, and there are 4 squares, so 4 * 4 = 16.

Mapping with UtilsPlugin2, it takes 8-10 node clicks. There are two methods to achieve this. The first step is equivalent for both methods by drawing the circumference which is 4 node clicks.

Method 1

• Draw the half line of the circumference which is 2 node clicks and split it in half with ALT+X. Now one will have two rectangles.
• Repeat the process on both of the rectangles, 2 * 2 = 4.
• The total node clicks is 4 + 2 + 4 = 10.

Method 2

• Draw the one half line of the circumference which is 2 node clicks.
• Draw the second half line of the circumference which is 2 node clicks, so that the two half lines make a cross.
• Select the two half lines and SHIFT+I to add nodes at the intersection. This in return will already select the one node.
• Select one of the half lines and P to split the way.
• Now select the larger of the half lines and ALT+X and do the same with the smaller ones.
• The total node clicks is 4 + 2 + 2 = 8, (though more interaction with the keyboard and lines is needed).

In this simple example there is already an improvement in node clicks. Next we will look at splitting larger areas.

Splitting a large area

Let’s say there is a 200 node circumference as circum# and one needs to split it in half. Let split# be the count of nodes for a split line with the minimum being 2.

Scenario 1

With the UtilsPugin2 one just needs to add the split line with a minimum of 2 node clicks, select it, and execute ALT+X.

Total node clicks are split# (minimum 2).

Scenario 2

One does not have access to UtilsPlugin2, which is the case when not using JOSM. Thus choose the two nodes where to create the split of the circumference at. Then draw the split line and connect it to one of the circumference halves and do the same thing for the other half.

Total node clicks are 2 + 2 * split# (minimum 6).

Scenario 3 (not recommended)

One is not familiar with the split methodology and thus one starts the area anew (not recommended since the history of the nodes is lost). Draw the first area which has split# + circum# / 2 node clicks and do the same for the second area.

Total node clicks = 2 * (split# + circum# / 2) = 2 * split# + circum# (minimum 204).

Planning on how to map natural and landuse

Let’s say one is mapping in an area that already has existing natural and landuse areas. One should plan ahead of how to map the white spots, since one can predispose oneself to inefficient mapping.

Let’s take a look at this animation of natural and landuse contribution in Croatia.

Area A shows white spot mapping, where as area B shows the split method.

Choosing the correct tool for the circumstance

From above we learnt that JOSM can handle both area A and B, though the downside of JOSM is that it is PC bound. On the other side Vespucci can handle also both, but being less efficient for B compared to JOSM.

Thus to min-max one’s daily living, if one commutes or has other spouts of down time, one could use the time to map via Vespucci, especially the A areas, since these areas are fairly straightforward and mundane to map. And once one has access to a PC, one can take upon the task of splitting up the newly mapped areas like in B.

Conclusion

In conclusion there are two ways of contributing natural and landuse data, either by addition (seen by white spot mapping) or through division (seen by the splitting method).

We use the data from OpenStreetMap while hiking through Colombia, Panama and Peru. It is really solid and a big thanks you to all the contributors!

One thing always stands out though. Almost all of the local people have never heard of the name ‘OpenStreetMap’. However, whenever we get information about trails they ask if we use Maps.me or recommend using it. For those that don’t know, Maps.me is simply an app showing data from OpenSteetMap!

We’re not sure why Maps.me is such a popular recommendation, though the name may be easier to remember that OpenStreetMap. We think it may simply have been one of the first apps that was free and allowed you to easily download maps for offline use?

We use an app called Organic Maps ourselves and can recommend it to anyone that goes hiking in another country. It is a privacy-friendly app and we found out it even preloads data from Wikipedia (for instance on towns, soms highlights/attractions and mountain tops).

IVIDES.org promoverá o GIS DAY 2023, como parte da iniciativa global #osmgeoweek, the OpenStreetMap Awareness Week. O Instituto IVIDES.org conta com a colaboração do HUB YouthMappers Rio de Janeiro, que inclui um poll de universidades brasileiras - UFRJ, UERJ e UFRRJ. A responsável pelo evento é a Dra. Raquel Dezidério Souto - raquel.deziderio@gmail.com.

As atividades programadas - palestras especiais, mapatonas e validatonas, serão promovidas para melhorar a completude dos dados no Estado do Rio de Janeiro (Brasil), uma contribuição para a redução de riscos e desastres em cidades selecionadas (nesta primeira fase do projeto) - Maricá, capital Rio de Janeiro (Mosaico das Vargens, Recreio dos Bandeirantes) e Seropédica.

Informações em:

https://ivides.org/hub-youthmappers-rio-de-janeiro-brasil

Palavras-chave: OpenStreetMap, IVIDES.org, HUB YouthMappers Rio de Janeiro, Brasil, mapeamento colaborativo.

IVIDES.org will promote the GIS DAY 2023, as part of the global initiative #osmgeoweek, the OpenStreetMap Awareness Week. The Institute IVIDES.org has the colaboration of the HUB YouthMappers Rio de Janeiro, that includes a poll of Brazilian Universities - UFRJ, UERJ and UFRRJ. The promoter and responsible of this event is Dr. Raquel Dezidério Souto - raquel.deziderio@gmail.com (IVIDES.org).

The scheduled activities - special keynotes, mapathons and validatons will be promoted to improve data completeness in the State of Rio de Janeiro (Brazil), a contribution to the reduction of risks and disasters in selected cities (at this first stage of the project) - Maricá, Rio de Janeiro (Mosaico das Vargens, Recreio dos Bandeirantes) and Seropédica.

The event is open to all and the subscriptions can be done at this direction: https://encurtador.com.br/knEFJ

Wellcome to Rio! Wellcome to OpenStreetMap and the free and open software comunity!

Keywords: OpenStreetMap, IVIDES.org, HUB YouthMappers Rio de Janeiro, Brasil, Brazil, colaborative mapping.

EVENTO - 14 e 15 de Novembro de 2023 - GISDAY AMAZÔNIA 2023 🌿🌍

Semana de Conscientização Geográfica

EVENT November 14th and 15th, 2023 - GISDAY AMAZÔNIA 2023 🌿🌍

Geographic Awareness Week

Participe deste evento incrível e explore o poder da geoinformação na Amazônia!

📆 DATA: 14/11/23 - Presencial na UEPA/NUPAD/LEGA 15/11/23 - Híbrido - Online

🕘 HORÁRIO: 09:00 às 18:00

🤝 ORGANIZAÇÃO: LEGA (Laboratório de Estudos e Pesquisas Geoambientais da Amazônia) - UEPA

🤝 PARCERIA: Meninas das Geotecnologias - IFPA

🌟 APOIO: Esri, UmbraOSM, Youthmappers

✅ INSCRIÇÕES ABERTAS em https://doity.com.br/gisday-amazonia-2023

Não perca! Este evento é uma oportunidade única para aprender, colaborar e descobrir como a tecnologia geoespacial está moldando o futuro da Amazônia. Junte-se a nós e seja parte dessa jornada rumo à conscientização geográfica! 🌎🌿 #GisDayAmazônia2023 #Geoinformação #PreservaçãoAmbiental

UMBRAOSM - União dos Mapeadores Brasileiros do Openstreetmap www.umbraosm.com.br

https://www.instagram.com/umbraosmbrasil/

https://www.instagram.com/meninasdageo/

Am Samstag, den 11. November 2023 habe ich HocusLocus 12 bei https://www.opencaching.de installiert.

Gefahrenhinweise auf Langweile wurden berücksichtigt, sind aber nicht so wichtig.

Wer sich über das didaktische Konzept informieren möchte, kann diesen Link aufrufen: HocusLocus

Wem es an weiteren Informationen fehlt, sollte HocusLocus 13 besuchen.

Been putting some effort into expanding detail around Upper Mast Landing Rd. in Freeport, Maine.

A V Olimpíada Brasileira de Cartografia - OBRAC 2023 incluiu o OpenStreetMap como parte da sua segunda etapa, de natureza prática. As equipes participantes, compostas de professores e alunos (de 14 a 18 anos), de escolas públicas e privadas e de todo o País, mapearam aspectos ambientais e socioeconômicos de áreas selecionadas da Região Amazônica brasileira, utilizando editores on-line e aplicativos para mapeamento com o OpenStreetMap.

Exposição Amazônia no Mapa

A Dra. Raquel Dezidério Souto (IVIDES.org e UFRJ), que coordenou a parte técnica desta segunda etapa da competição, criou a exposição virtual Amazônia no Mapa, com parte dos mapas elaborados pelas equipes participantes.

Fonte: equipes participantes da OBRAC 2023 - Ref. 6298800859 (topo esq.); 6299051019 (topo dir.); 6116334695 (centro esq.); 6474822799 (centro dir.); 6169070179 (inf. dir.); 6191786719 (inf. esq.).

OBRAC

A OBRAC é realizada desde 2015 e coordenada pela Universidade Federal Fluminense (UFF), na pessoa da Profa. Dra. Angélica C. Di Maio, em parceria com diversas instituições de ensino e pesquisa brasileiras. O projeto tem o apoio do Conselho Nacional do Desenvolvimento Científico e Tecnológico (CNPq).

OBRAC at IVIDES

EXPO Amazônia no Mapa

Interactive uMap of the OBRAC teams - 2015-2023

The V Brazilian Cartographic Olympiad - OBRAC 2023 included OpenStreetMap as part of its second stage. The participating teams, integrated by teachers and students (aged between 14 and 18 years) from public and private schools, from all over the country, mapped environmental and socioeconomic aspects of selected areas of the Brazilian Amazon Region, using online editors and applications for mapping with OpenStreetMap.

Exposition Amazônia no Mapa

Dr. Raquel Dezidério Souto (IVIDES.org and UFRJ), who coordinated the technical part of the second stage of the 2023 edition, created a virtual exhibition Amazônia no Mapa, where anyone can visit the maps of the Brazilian Amazon Region, created by the teams of the OBRAC 2023.

Source: OBRAC 2023 Teams - Ref. 6298800859 (topo esq.); 6299051019 (topo dir.); 6116334695 (centro esq.); 6474822799 (centro dir.); 6169070179 (inf. dir.); 6191786719 (inf. esq.).

OBRAC

The OBRAC is realized since 2015 and is coordinated by the Federal Fluminense University (UFF), by Prof. Dr. Angélica C. Di Maio (UFF), in partnership with several Brazilian educational and research institutions. The project has the support of the National Council for Scientific and Technological Development (CNPq).

OBRAC at IVIDES

EXPO Amazônia no Mapa

Interactive uMap of the OBRAC teams - 2015-2023

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Only two public bookcases identified today. I think the project could be wrapped up in around 10 more hours.

This project was featured on OpenStreetMap’s Instagram and Facebook pages - very flattering and validating considering I started editing OSM several months ago!

Intro

Part 2

Part 3

Part 4

Part 5

Excited to contribute my first “commit.” The iOS app is really something, ain’t it?

1.1

Tampermonkey is web browser extension that allows adding JavaScript to any website in your browser and manipulate content of that website. It sounds scary and probably should, first you need to trust extension itself and then scripts that you install. Since extension itself has huge community and history, millions of installs across Chrome/Edge/Firefox extensions stores, 5 stars… Let’s assume we can trust it…

I wrote some time ago script that I want to share with everyone, it adds few buttons to OpenStreetMap.org website. Here is example how it looks like:

On example of New York above buttons would take you to following websites:

• PeWu nice and simple history view of changes on nodes, ways or relations
• DeepHistory another history viewer, but in tabular view
• Relation Analyzer helpful website for validating/analyzing relations
• Overpass Opens Overpass at same viewport as currently seen on OSM website

It also adds different set of buttons linking to Achavi, OSMHV, OSMCha and OSM Lab websites when viewing changeset on website:

To install this extension in your browser go to https://www.tampermonkey.net/ and follow instructions…

Once you have it installed… You will want to install script that I wrote to do that:

• Click Tempermonkey icon at top right corner of your browser then Dashboard
• Inside Tempermonkey dashboard there is Utils tab, click that
• At bottom of that page there is Import from URL entry
• Stay vigilant when installing scripts, check the code…
• Copy-paste following URL there https://gist.githubusercontent.com/DavidKarlas/81b684dc6853f489b233715d157c145b/raw/EnrichOSMWebsite.js

Now go to OpenStreetMap.org or some changeset/node/way or relation and new buttons should show up.

You can give suggestions or report bugs either here or at https://gist.github.com/DavidKarlas/81b684dc6853f489b233715d157c145b

Happy mapping,

David

A couple of million-dollar ideas

1. Do you like to write descriptions for edits? And review other people’s edits if there is an unclear comment? Autogeneration of descriptions like in MAPS.ME and EveryDoor is interesting. But why not make ChatGPT do it?

2. ChatGPT is already pretty good at recognising pictures. And we have thousands of open notes from StreetComplete with signs of establishments. It would be nice to add tags to the object in a couple of clicks that ChatGPT could recognize. Or build this function directly into some editor.

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What kind of work would you put AI to?