何に対して付けるタグか（意味合い）

主にバス、タクシーのいずれかまたは両方を運行する会社（の事務所、営業所）

その他、旅客を輸送する陸上の交通機関（の事務所、営業所）に使うことも考えられる （※物を運ぶものはoffice=transportなどが一般的のため、その方が適していると思われる）

このタグ（値）が適していると思った理由

まず最初に、taginfoで同じような意味の値を誰かが考えていないか確認した。そのうえで、意味的に最も適しているのが「transportation」であると考えた。

• company=busではダメか

意味合いの項目で書いた「バス、タクシーの両方を運行する」場合、 company=bus;taxiのように複数の値を列挙することになる

現状、companyタグのほとんどは1つの値が付けられており、列挙すると混乱を招くため、大まかに交通機関であることを示し、別に具体的な内容を書く（階層構造にする）ほうが良いと考えた

• company=transportではダメか

transportは日本語で「輸送」であるから、本来はそれでよいと思われる

しかし、現状は「荷物の輸送」（運送・物流）を意味する目的で使われており（osm.wiki/wiki/Tag:office%3Dtransport ）、旅客のみを輸送する会社に対して使うのは混乱を招くため、違う単語を使うほうが良いと考えた

• company=public_transportではダメか

日本語ではだいたい「公共交通機関」や「乗合交通機関」などになるが、後者で考えると「乗合」に当てはまらないタクシーを含めると不自然なため、使わないことにした

office=transportationはどうか

これは、それでもよいと思う。companyタグを挟むべきかどうか迷ったので、ひとまず挟む方を選んだ

様子を見て、wikiにも書くことを考えているが、「なぜこれを選んだのか」という説明として日記に投稿した

This blog post is part of a series of blog posts about the new OSM file format “OMA”. This is the fourth post. At the end of the article you’ll find links to the other blog entries.

The real subject of this blog series is the newly developed file format. So far I have mainly talked about the tools for creating and using the format, because the format itself is a dry subject. But now it’s time to dive more deeply into the format itself. I will not go into all the details, because I think that apart from some freaks like me, people are not interested in all the details. If you are, take a look at the specs.

Fast Access

OpenStreetMap data consists of a set of elements. Some of these elements are nodes, some are ways, and some are relations. You can think of OSM as a big storehouse where all the elements are scattered around:

Obviously it’s hard to find what you’re looking for, if there is no order.

The Order of OSM Files

Fortunately, it’s not that bad. In traditional OSM files there is some order: Elements are sorted by type and, as a second criterion, by ID.

This order doesn’t help much, when looking for certain elements. Especially: You can’t take an element out of the middle and look at it, you have to go through the elements from top to bottom.¹

The Order of Databases

Because it’s hard to work this way, many ways of sorting OSM elements have been developed over time. For example, in a database they can be stored as tables with one element per row and one table for each type. You can think of this as storing nodes in one room, ways in another, and relations in a third room in our storehouse.

Typically, databases also contain some indexes. In our analogy, they are like posters at the entrance to each room, telling you, which shelf to look on for a particular element. Indexes are very important for quick searching.

The Order of OMA Files

Oma files sort elements on three levels: First by type and geographic location, second by key, and third by value. They contain something like a database index at each level, so typical searches can be handled very quickly.

In our analogy, you might think of the rooms in the building as the first level, the shelf units in each room as the second level and the shelves in each shelf unit as the third level; again, with posters at each level.

Small Filesize

The second design goal was to keep the file size small. Two mechanisms are used for this: Efficient storage of the elementary datatypes and compression. There are basically three elementary datatypes to handle: geographic coordinates, integers and strings.

Geographical coordinates

Coordinates in OSM data are given as a pair of numbers expressing longitude and latitude in the WGS84 coordinate system. A naive approche of storing them would be as a pair of floating point numbers. For full accuracy you would need to use double precision numbers, resulting in 16 bytes per coordinate.

That’s a lot. For example, germany.oma contains 576,208,086 pairs of coordinates. At 16 bytes per pair, this alone would result in a file size of over 8 GB.

It would be possible to use single precision numbers, accepting some small rounding errors. This would halve the number of bytes used. But there are better ways: If you multiply each number involved by 10,000,000, the two coordinates become integers that can be stored in 8 bytes without loss of precision.

This can still be improved using a technique called delta encoding: Two consecutive nodes in the file are often close to each other. So the difference between the coordinates of these two nodes is a much smaller number that can be stored in fewer bytes.

In Oma files, if the difference between two coordinates is between -32767 and 32767, this difference is stored, using only 2 bytes. This case is used in 94% of all coordinates. If it’s larger, 6 bytes must be used. This results in a total of 4,4 bytes for a pair of coordinates on average, almost halving the amount needed again.²

For comparison, the pbf and o5m formats use a similar, but slightly more complicated delta encoding. The result is the same: an average of 4,4 bytes for a pair of coordinates.

Integers

If you look carefully at OSM data, there are many places where there are small non-negative integers (the number of tags of an element, the number of nodes of a way, the version number, and so on). A normal integer takes up 4 bytes of space, and that’s a waste when the numbers are so small, because almost always 3 of those 4 bytes are just zeros. That’s like writing 0008 instead of 8.

So, Oma files store integers smaller than 255 in just one byte. Integers between 255 and 65534 use 3 bytes, and all larger integers use 7 bytes. On average, this results in 1,006 bytes per integer, which is almost perfect (using germany.oma as a reference).

Strings

There are a lot of repetitive strings in OSM data. Imagine how many times the string highway alone occurs. It would be nice to store these strings more efficiently. Other formats use lookup tables to do so. For example, the lookup table might contain highway at position 3, so instead of storing the string highway, the number 3 could be used.

I have experimented with such lookup tables too, but they turned out to be a bad idea. Why is that? Well, the whole thing is piped through a compression algorithm called deflate. This algorithm is very good at recognising repetitions, and so the repeated highway strings can be compressed better than repeated occurrences of 3.

It turned out, that table lookup mechanisms together with deflate increased the file size instead of reducing it.

So I didn’t do much with strings. There is only one small difference from the standard way of storing strings (in Java): I do not use a two-byte value to store the length of the string, but an integer, as explained above, which most of the time uses only one byte.

Compression

All slices can be compressed using an algorithm called deflate. This is a very old and well-established algorithm. It was developed back in the eighties and is used in zip files, pbf files and many other places.

Well, I didn’t think any more about compression – it worked, so what?

In a comment to my introductory post, user cello pointed out, that there are better algorithms available today. They are about 5 to 10 times faster, often with similar or even better compression.

I don’t know how well these algorithms will work together with the element storage decisions I wrote about above. They probably need to be added to the tools to find out. I haven’t found the time to do that and I probably won’t find the time to do so in the near future.

But I thought I could calculate rough estimates of the speed gains of these algorithms. All I had to do was measure the time taken by the deflate algorithm and divide it by 5 or 10. Unfortunately, the measurement produced some very strange results, leaving me with very little information to estimate.³

It could be, that the speed gain is almost nothing, or even a loss. It could also be that access times are halved. I can’t predict.

I thought for a long time about what to do with these new compression algorithms. Yesterday I finally forced myself into a decision: I will not include them in version 1 of the file format. It would take too many resources on my part and I can’t tell yet if anyone (besides me) will use OMA files anyway. But I definitely plan to include these algorithms in version 2 of the file format, when the time is ripe.

See also

• A New File Format for OSM Data
• Using the Oma Library
• Getting Files in OMA File Format

1. The analogy of a stack is somewhat missleading here. Actually you can look at every place in the pile, but you do not know, where one element ends and where the next starts. I described this in more detail in my introductory post. ↩

2. Oma files do not restrict the order of elements in a slice. If they where sorted in an approbriate manner, the average amount of bytes needed could probably be reduced to almost 4,0. I never tried this though. ↩

3. I used two versions of germany.oma: One compressed, the other not. The second one is about three times larger as the first one. Reading the whole file byte by byte takes 1 minute for the first one and 3 minutes for the second one; that’s what I expected. Next, I used these two files to read them with an OmaReader. I used an empty filter which means, that all elements are read. I expected this to be slower in both cases. While this was true for the compressed version (took now about 2 minutes), it was not true for the uncompressed version (took only 1 1/2 minutes). I have no clue why reading the whole file while jumping around in the file and doing some additional compution with the bytes is much faster than just reading the file sequentially… ↩

Coordinates should be formatted 1.236345 4.23643 Written by ChatGPT Due to kramdown I have to use https://docs.google.com/document/d/1P4YrHsAhZKu9BRt1HRnsBbQJl8MdDMoJ76Ht9w1aqG0/edit?tab=t.0

Explorando el Humedal El Totoral

El Humedal El Totoral es un ecosistema estratégico que enfrenta diversas presiones ambientales, como la expansión agrícola y ganadera, la urbanización descontrolada y el uso inadecuado de agroquímicos. Para comprender mejor estos problemas y generar datos abiertos sobre el territorio, organizamos una jornada de mapeo comunitario con ChatMap, una herramienta innovadora para la ciencia ciudadana.

Mapeo Comunitario con ChatMap

¿Qué es ChatMap y por qué lo usamos? ChatMap es una herramienta de mapeo que funciona empleando WhatsApp, lo que la hace muy accesible y fácil de usar. A diferencia de otras aplicaciones moviles pensadas desde el GIS, que pueden ser complejas para quienes no están familiarizados con tecnologías geoespaciales, ChatMap permite mapear de manera sencilla y en tiempo real.

Algunas ventajas que encontramos de emplear ChatMap en la educación ambiental:

• No requiere instalar nuevas aplicaciones.
• Interfaz familiar para el usuario (WhatsApp)
• Permite visualizar datos en tiempo real a través de la página Chatmap
• Ideal para educación ambiental y monitoreo comunitario.

¿Cómo funciona?

Creamos un grupo de Whatsapp con los participantes. Explicamos que solamente deben enviamos la ubicación (Ubicación actual, no Ubicación en tiempo real) y un breve reporte, este puede ser una imagen o un texto. Al final del ejercicio exportamos el chat con archivos adjuntos, lo cargamos a la plataforma y cada punto queda registrado automáticamente en el mapa. Chatmap Finalmente descargamos la información y la importamos al nuevo desarrollo de HOT basado en uMap uMap

Resultados del Mapeo

Durante la actividad participaron 25 personas, registrando 40 puntos con información sobre biodiversidad y conflictos socioambientales.

Flora y fauna identificadas

• Especies vegetales: Plantas herbáceas, arbustivas y árboles nativos.
• Fauna silvestre: Patos, halcones y anfibios.

Conflictos ambientales detectados

• Canalización del humedal para desecamiento.
• Depósito de residuos de agroquímicos cerca del agua.
• Expansión de la ganadería dentro del humedal.
• Presión sobre la totora, una especie nativa clave y expansión del pasto kikuyo, como especie invasora.
• Acumulación de escombros y residuos en la zona

Esta información puede servir como punto de referencia para visibilizar los problemas ambientales del ecosistema y promover estrategias de conservación basadas en datos abiertos y ciencia participativa.

Ciencia Ciudadana y Educación Ambiental

El uso de ChatMap en educación ambiental permitió: * Involucrar a la comunidad en la generación de datos geoespaciales * Facilitar el aprendizaje sobre biodiversidad y conflictos ambientales * Crear un mapa colaborativo y que puede ser fácilmente actualizado en el tiempo

Esta herramienta desarrollada por (Emilio Mariscal)[https://www.linkedin.com/in/emiliomariscal/) del equipo de Humanitarian OpenStreetMap Team me resulta un desarrollo muy útil para realizar trabajo con comunidades. Seguiré explorando la herramienta y compartiendo los resultados que obtenga con ella.

Consulta el mapa interactivo aquí: Mapeo de biodiversidad y conflictos sociambientales Humedal El Totoral

¡Gracias por leer!

What is anti-SEO aktion?

Maybe you’ve seen one of my changeset comments reading “anti-SEO aktion”. Maybe I even reverted your changes in a changeset with that comment. You might be wondering, what does it mean?

Well, I hope “anti-SEO” is clear enough. OpenStreetMap is not a platform for boosting your online presence. Your OpenStreetMap listing, in all likelihood, does very little to improve your rankings. If the marketing agency you hired is improving their listing here, you ought to find one that used more evidence-based SEO practices.

And what of “aktion”? It’s a play on Antifaschistische Aktion, which was an anti-Nazi resistance effort in Weimar Germany. It’s not a political statement, per se. It’s just a bit of fun with changeset comments.

How do I get involved?

Any experienced mapper probably knows what belongs in OpenStreetMap and what doesn’t. For those who don’t, here are the general steps involved in fixing spam within the U.S. While following all of them isn’t necessary, it’s the best way to turn SEO efforts into a real business listing that improves the map.

1. Check if the feature was placed onto an existing feature, such as a node being added to a highway or a highway being renamed. If so, revert and you’re done.
2. Check if the tags used follow OSM schema. If not, revert and you’re done.
3. Check if the location is correct. If not, revert and you’re done.
4. Check if description reads like ad copy or doesn’t provide any useful, objective information not already present in the tags. If so, delete the description. 99 percent of the time, there’s probably no need for any sort of description.
5. Check addr:* tags.
   1. Is addr:street spelled out in full, matching the nearby road? If not, fix it. If it contains a suite number, remove it and put just the number in addr:unit.
   2. Does addr:housenumber contain any sort of unit number? Move it to addr:unit.
   3. Does addr:city match the surroundings?
   4. Is addr:state the two-letter postal abbreviation for the state? If spelled out, improperly lowercase, or abbreviated some other way, fix it.
   5. Is country in use? The tag is sometimes confused with addr:country. I generally avoid this tag because I don’t believe it to be very useful. Either remove it or fix it.
6. Is name correct? If it’s a title you wouldn’t use casually, it’s probably incorrect.
7. Is operator correct? It shouldn’t match the name. It probably shouldn’t contain titles or credentials, either.
8. Is phone correct? In the US, phone numbers are often displayed without the country code and with the area code in parentheses. Make sure the number is in +1-area_code-exchange-local_number format.
9. Is wikidata correct? Some spammers have taken to adding this tag to features to make them harder for iD users to delete. If this tag is present, verify that the identifier is correct. For example, you might spot the wikidata item for dentist present on a dentist office, which is incorrect.
10. Ditto for wikipedia.
11. Is website correct? It should not contain any tracking codes and should lead to a location-specific page. In the case of a chain, you don’t want the website to lead to a corporate homepage. Sometimes, the best you can do is a list of locations in a state. The best way to fix the website is to navigate to it, go into the address bar and hit “select all”, then copy that. This ensures the protocol and www prefix are included. This also avoids any redirects. While on the website, it also helps to check that the business details match up with the OSM feature.
12. Are there any extraneous tags on the feature? A common one is Category. Remove them, potentially adding that information through an appropriate tag.
13. Does the feature have any descriptive tags, and are they correct? For example, office=yes gets used generically, and isn’t very useful. Try to find out more about the business to come up with a more appropriate tag, or invent your own. Similarly, recognized keys may be used improperly. This is where iD comes in handy with its presets for things like healthcare and car repair specialties. Check the presets to see if any values can be replaced with more widely used ones. Generic values that add nothing (like healthcare:specialty=dentist when a feature is already tagged with healthcare=dentist) should be removed.
14. Are payment method tags used correctly? This is another case where iD’s presets are useful. For example, some features may be tagged as accepting “financing” as a payment method, which isn’t recognized. Alternatively, some payment methods could be improperly abbreviated, e.g., amex for american_express.
15. Is the image tag an actual image of the feature? SEO spammers often use it for a logo, which is not the intended usage. If it’s on an image hosting site or CDN, that’s a red flag. If it’s a photo on Wikimedia Commons, it’s more likely to be an image of the feature.
16. Is opening_hours properly formatted? There are a lot of nuances to this tag that I can’t properly capture here. The main issues I see on spam listings are three-letter day abbreviations, use of AM and PM, spaces around hyphens, specifying days as being closed rather than leaving them out, and commas instead of semi-colons.

Finding SEO spam

Section under construction! In the meantime, I welcome all tips you may have.

I have two main techinques for finding spam. The primary one is monitoring new features tagged with description. The second one is subscribing to the RSS feed of U.S. changeset comments.

There is potential to use a large language model here to analyze all changeset comments and look for generic changeset comments like “Updated” (seemingly used by particular spammers), changesets by usernames that sound like business names, or obvious ad copy. I’ve yet to try this out for myself, but it’s on the docket as I try to understand how much spam actually gets added to the platform.

Conclusion

There are many different tagging mistakes made by spammers, and doubtlessly this is far from an exhaustive list. If you’ve noticed any other commonalities between spam listings and/or suggestions for detecting and fixing them, leave a comment.

If you’d like to keep up-to-date with my efforts to remove spam, here’s a filter.

Here’s to wiping spam off the map, wherever it may take hold!

Objects in private gardens which do not require a build permission, such as small shelters and especially movable objects like (round) swimming pools, should NOT be entered into ANY public maps! They add nothing to the quality and usefulness of a map, I consider it a map data spam.

I may sometimes remove such objects from the Frýdlant region, especially if not mapped correctly (private swimming pools must be marked as private to not interfere with searching for nearby swimming pools).

Ler em Português

MapComplete, Panoramax, overpass turbo and uMap: what can you do with these programs when mapping trees?

But first, a suitable question: how important is it to map trees?

In addition to the urban issue, in which it is often assessed whether natural elements and urban equipment are preserved, whether they are adequate or well distributed in a given area, the greatest motivation for mapping trees is to monitor vegetation cover, since these individuals are ecologically relevant. Combined with an educational activity, it also helps to raise awareness of their importance among students.

Trees provide various ecosystem services (or environmental services), such as providing shelter and food for different species, cooling the ambient air, removing atmospheric CO2, producing biomass, preventing soil erosion, reducing noise pollution et al.

Mapping with MapComplete

MapComplete is an easy-to-use Web application to edit OpenStreetMap that allows you to map features related to different themes, one of which is exactly the tree mapping. The program automatically sends the data to OpenStreetMap, as long as you are logged in with your OSM user account. Link to MapComplete tree theme

The interface also offers some useful features, such as the possibility of registering a photograph locally (at street level) and uploading it to the Panoramax server, gaining a unique key that can be referenced in other software (such as uMap, below in this text). It is also possible to view the mapped item directly on the website https://osm.org.

In addition, various attributes can be specified. The program also allows you to create customized theme schemas. In the MapComplete default scheme, we highlight:

A) the leaf type:

• tag leaf_type=broadleaved » refers to angiosperms (species that produce flowers and have broad leaves), e.g. Beach Almond - Terminalia catappa, Q271179.

• tag leaf_type=needleleaved » refers to gymnosperms (species that do not produce flowers and have needle-shaped leaves), e.g. Pinus - Pinus silvestres, Q133128.

B) the species’ code on the Wikidata (easy search by name):

• tag species:wikidata=* , e.g. coconut palm - Cocos nucifera, Q13187.

C) the circunference - in meters, to be measured at 1.3 m from the ground (standard value for this measurement):

• tag circunference=*

D) the height - in meters:

• tag height=*

E) the location of the individual - whether near a highway, whether in an urban area or not, etc:

• tag denotation=*

Viewing on Panoramax

Link to panoramax.xyz

Once the individuals (each tree) have been mapped, the photographs are stored forever for all users (unless someone deletes them or the project is ended). It is important for recording the health of trees or their age, all characteristics that can be easily observed in it. In addition, it makes it possible to observe the distribution of trees near the highways.

Viewing on overpass turbo

Link to overpass turbo

Once the points have been mapped, the attributes included, and the photographs recorded, it is still possible to create schemes for visualization in the turbo overpass, the simplest of which is shown in the code below, which colors trees with different types of leaves (wide or thin, as mentioned above) with specific, custom codes.

node
  [natural=tree]
  ({{bbox}});
out;

{{style: /* added by auto-styler */
*[leaf_type=broadleaved]
{ color: #3E600B; fill-color:#3E600B; }
*[leaf_type=needleleaved]
{ color: #97E71F; fill-color:#97E71F; }
}}

It is also possible to export these results and/or query these features with the same color scheme in other areas, as the query is automatic, according to the enclosing rectangle that appears on the screen (or bounding box).

Viewing on uMap

Link to uMap (some features were modified to illustrate this article).

The uMap is a French project which provides a Web mapping platform which allows Web maps to be created very quickly and, currently, with dynamic layers which are generated as the coordinates change in the browser address. In this way, mapped trees can be viewed in any region of the world and with color schemes, labels and click behavior, customized according to the project.

For the example presented here, overpass queries were used according to leaf type (leaf_type), in order to distinguish trees with broad leaves from those with needle-shaped leaves. This is done very simply directly from the uMap panel, in edit mode, in the import menu.

To show the photo on the feature label, you need to choose the “OpenStreetMap” mode in “Interaction options” » “Pop-up content style” in the uMap layer config panel. Or program the contents of the label according to the project instructions - https://github.com/umap-project/umap.

Green Open Data Day 2025

March 31, 2025

Information:

https://ivides.org/green-open-data-day

That’s all for today! Hope to see you mapping trees! Send me the pic.

This content was proudly developed entirely with free software ;)

Translated to English with DeepL.com (free version). Reviewed by human.

Read in English

MapComplete, Panoramax, overpass turbo e uMap: o que você pode fazer com esses programas, ao mapear as árvores?

Mas, antes, uma perguntinha: qual a importância de mapear as árvores mesmo?

Para além da questão urbanística, em que, são avaliados frequentemente se os elementos naturais e equipamentos urbanos estão conservados, se são adequados ou se estão bem distribuídos em uma determinada área; a maior motivação para o mapeamento de árvores é o monitoramento da cobertura vegetal, uma vez que estes indivíduos são relevantes, do ponto de vista ecológico. Aliado a alguma atividade educativa, ainda ajuda a promover a consciência sobre tal importância nos educandos.

As árvores proporcionam diversos serviços ecossistêmicos (ou serviços ambientais), tais como: servir de abrigo e alimento para diferentes espécies, refrigeração do ar ambiente, remoção do CO2 atmosférico, produção de biomassa, evitar a erosão do solo, redução da poluição sonora etc…

Mapeando com o MapComplete

Alguns dados foram modificados apenas para ilustrar este artigo.

MapComplete é um programa belga, que permite mapear feições relacionadas a diferentes temas e, um deles, é o mapeamento de árvores. O programa envia automaticamente os dados para o OSM, desde que você esteja logado com sua conta de usuário(a). Link para o tema de árvores do MapComplete

Na interface, ainda são oferecidos alguns recursos úteis, como a possibilidade de registrar uma fotografia localmente (em nível de rua) e subi-la para o servidor do Panoramax, ganhando uma chave única, que pode ser referenciada em outros softwares (como o uMap, a ser mencionado adiante neste texto). Também é possível visualizar o item mapeado diretamente no site https://osm.org, por meio de um link.

Além disso, podem ser especificados vários atributos. O programa também permite a criação de esquemas personalizados de temas. No esquema default, destacamos:

A) o tipo de folha:

• etiqueta leaf_type=broadleaved - refere-se às angiospermas (espécies que produzem flores e de folhas largas). Ex: Amendoeira da praia - Terminalia catappa, Q271179.

• etiqueta leaf_type=needleleaved - refere-se ás gimnospermas (espécies que não produzem flores e com folhas em forma de agulha). e.g. Pinus - Pinus silvestres, Q133128.

B) o código da espécie na Wikidata (busca fácil pelo nome):

• etiqueta species:wikidata=* . Ex: Coqueiro - Cocos nucifera, Q13187.

C) a circunferência - em metros, a ser medida a 1,3 m do solo (valor padrão aceito internacionalmente):

• etiqueta circunference=*

D) a altura - em metros:

• etiqueta height=*

E) a localização do indivíduo - se próximo a alguma via, se em área urbana ou não etc.:

• etiqueta denotation=*

Visualizando no Panoramax

Link do panoramax.xyz

Uma vez mapeados os indivíduos (cada árvore), as fotografias ficam armazenadas eternamente (a menos que alguém a delete ou que o programa seja encerrado) para todos os usuários, sendo importante para registro da saúde das árvores ou a idade das mesmas, todas características que podem ser facilmente observadas nele. Além disso, permite observar o nível de arborização das vias e o quanto os galhos de árvores estão ou não entremeados com fiação elétrica, que, no Brasil, é suspensa (e não no subsolo) e que provocou diversos transtornos e prejuízos nos eventos ocorridos em São Paulo (capital), com queda de muitos postes de luz, durante uma tempestade no verão de 2025.

Visualizando no overpass turbo

Link do overpass turbo

Mapeados os pontos, incluídos os atributos, registradas as fotografias, ainda é possível criar esquemas para visualização no overpass turbo, sendo o mais simples, o que segue no código abaixo, que colore com códigos específicos, personalizados, as árvores com tipos diferentes de folhas (largas ou finas, como mencionado acima).

node
  [natural=tree]
  ({{bbox}});
out;

{{style: /* added by auto-styler */
*[leaf_type=broadleaved]
{ color: #3E600B; fill-color:#3E600B; }
*[leaf_type=needleleaved]
{ color: #97E71F; fill-color:#97E71F; }
}}

Também é possível exportar estes resultados e/ou consultar estas feições com o mesmo esquema de cores em outras áreas, pois a consulta é automática, de acordo com o retângulo envolvente que aparece na tela (ou bounding box).

Visualizando no uMap

O uMap é um projeto francês, que provê uma plataforma de Web mapping, que permite a criação de mapas Web muito rapidamente e, atualmente, com camadas dinâmicas, que são geradas à medida em que as coordenadas mudam no endereço do navegador. Assim, podem ser visualizadas as árvores mapeadas em qualquer região do mundo e com esquemas de cores, etiquetas e comportamento ao clicar, personalizados segundo o projeto.

Para o exemplo apresentado aqui, foram utilizadas consultas overpass segundo o tipo de folha (leaf_type), de modo a distinguir as árvores de folhas largas, daquelas de folhas em forma de agulha. Isto é realizado de maneira muito simples diretamente do painel do uMap, em modo edição, no menu importar.

Link para o uMap (obs: algumas feições foram modificadas para ilustrar este artigo).

Para que a fotografia apareça na etiqueta da feição, é necessário escolher o modo “OpenStreetMap” nas “Opções de interação” » “Estilo de conteúdo do pop-up”. Ou programar o conteúdo da etiqueta, conforme as indicações do projeto - https://github.com/umap-project/umap.

Participe do evento Green Open Data Day 2025

31 MAR 2025 - manhã/noite

Informações e inscrições:

https://ivides.org/green-open-data-day

E isso é tudo por hoje! Espero encontrá-lo(a) mapeando árvores por aí!

Este conteúdo foi orgulhosamente desenvolvido totalmente com software livre!

After spending a bit of time mapping and getting a feel for the scope, type of work this project will require, it’s clear that this project will unsurprisingly take quite a bit of time.

To make this process as engaging as possible, I think it would be wise to alter my workflow slightly. Initially, I planned to start with only mapping buildings for the entire island. However this would mean hours and hours of monotony, so I think a good workaround here is to keep my current workflow structure, but just apply it to a smaller scale. For example, I’ll pick smaller sections of the island to do both the building and the terrain mapping. This will give the work more variety and also make it more clear which areas I’ve already worked on.

Project Outline

This entry is a statement of my intention to map out Bell Island, Newfoundland. I will start south and move my way north as the south is less densely detailed and work will likely be quicker. My intended workflow is stated below, where I will not move on to the next item on the list until the first item has been mapped as thoroughly as possible on the entire island. While I am experienced at working with geospatial data, this is my first project on OSM so any suggestions/comments on my work are appreciated.

I will provide updates through future diary entries as my work progresses. This is a casual project so I am not setting any timelines.

Workflow

1. Buildings & associated roads
2. Terrain
3. (Might drop due to lack of local knowledge) Secondary urban & rural characteristics (cemeteries, parking lots, etc.)

Whether you’re passionate about maps, data, or shaping the future of  OpenStreetMap (OSM), the community is always looking for your inspiring ideas! Why not sharing them during State of the Map 2025

The call for participation of SotM 2025, taking place in Manila, Philippines, on October 3 – 5, is now open! The programme committee is ready and waiting, eager to unwrap your submissions for talks, workshops, and panels. These sessions aren’t just part of the conference; they’re its beating heart, driving conversations and sparking ideas that resonate worldwide. Presenting your work, projects and ideas at SotM is also a great way to get in touch with the wider OSM community.

Tracks

Sessions can be submitted for the following tracks:

• OSM Basics – Information dedicated to newcomers
• Community and Foundation – Bringing people together, working group experiences, strategies & vision
• Mapping – All about making the mapping easier and better
• Cartography – Your ideas on how to create good-looking presentations of the OSM dataset
• Software Development – Software for processing and editing data
• Data Analysis & Data Model – Reflections about the OSM data, its model and analysis of quality and completeness
• User Experiences – Stories of using OSM and its data as a user
• Education – How you use OSM in an educational context

If your submission doesn’t seem to fit into one of these tracks, don’t worry – as long as it is clearly related to OpenStreetMap, you’re perfectly fine if you simply choose the track that feels to fit best.

Academic Track at SotM 2025

In addition to this general call for participation, there will again be a proper academic track with a separate CfP, which will be announced later. So, if you’re knee-deep in the captivating world of OpenStreetMap, stay tuned for the official call: The working group is eagerly awaiting the most riveting insights and groundbreaking results from your studies. Get your research hats on, gather your data, and prepare to submit the best of your studies.

Timeline and Deadlines

• 18 May 2025 23:59:59 UTC: Deadline talk, workshop and panel submissions
• End of June 2025: End of review phase, speakers will be informed, schedule published
• July 2025: Talk video production (test video and final video)
• 3-5 October 2025: State of the Map

For more information on the above track categories, submission requirements and rating criteria, please visit the complete call for participation and the submission guidelines on the SotM website and then submit your session on Pretalx using our submission form!

Stay tuned for more news about the State of the Map 2025! See you later this year in Manila, Philippines, and online!

The State of the Map Working Group

Do you want to translate this and other blogposts in your language…? Please email communication@osmfoundation.org with subject: Helping with translations in [your language]

The State of the Map conference is the annual, international conference of OpenStreetMap, organised by the OpenStreetMap Foundation. The OpenStreetMap Foundation is a not-for-profit organisation, formed to support the OpenStreetMap Project. It is dedicated to encouraging the growth, development and distribution of free geospatial data for anyone to use and share. The OpenStreetMap Foundation owns and maintains the infrastructure of the OpenStreetMap project, is financially supported by membership fees and donations, and organises the annual, international State of the Map conference. Our volunteer Working Groups and small core staff work to support the OpenStreetMap project. Join the OpenStreetMap Foundation for just £15 a year or for free if you are an active OpenStreetMap contributor.

OpenStreetMap was founded in 2004 and is an international project to create a free map  of the world. To do so, we, thousands of volunteers, collect data about roads, railways, rivers, forests, buildings and a lot more worldwide. Our map data can be downloaded for free by everyone and used for any purpose – including commercial usage. It is possible to produce your own  maps which highlight certain features, to calculate routes etc. OpenStreetMap is increasingly used when one needs maps which can be very quickly, or easily, updated.

“Fina and the Maps” is a children’s book that aims to get children excited about collaborative cartography. The authors and translators hope that some of them will take part in the community project OpenStreetMap, which maps the world and makes the data available to everyone – similar to Wikipedia. The book is intended to promote open education and the development of collective knowledge and can be downloaded for free as an eBook (PDF). The recommended age range is 8 to 12 years.

The colorfully illustrated children’s book (“Fina e os mapas”) about cartography and collaborative maps was originally written by Pablo Sanxiao in Galician and Spanish. It has already been translated into English, French, Italian, Catalan and (Brazilian) Portuguese and is now also available in (Swiss) High German. It can be translated into other languages in the spirit of open education and is therefore also available in raw text (Markdown).

Here is a summary: Fina is a girl who loves technology and often visits her grandmother by bike to enjoy her exciting stories and delicious cookies. When the power goes out one day, her grandmother shows Fina old atlases and tells her how maps used to be drawn by hand, sparking Fina’s interest in cartography. Inspired, Fina discovers the OpenStreetMap project, starts entering places digitally with her grandmother and becomes a digital cartographer herself.

Share this! Website and download: https://finaeosmapas.ghandalf.org/

Bağlantılar / Links

• hdyc: https://hdyc.neis-one.org/?heyturkiye58
• TR list: https://osmstats.neis-one.org/?item=countries&country=Turkey
• Comments: https://resultmaps.neis-one.org/osm-discussion-comments?uid=12667120
• OSM Wiki: osm.wiki/wiki/User:HeyTR

Ich war am 19.3. zum 1.Mal beim OSM Stammtisch im Kaffeesatz. Da wurde mir die App StreetComplete empfohlen. Die habe ich mir installiert und am Donnerstag intensiv ausprobiert. Es hat Spaß gemacht und mich gefesselt. Drei Stunden bin ich zwischen Tietz und Moritzhof hin und her gelaufen und habe ca. 60 Einträge erfasst. Demnächst werde ich mal JOSM ausprobieren.

You may have noticed that I have marked a lot of buildings in Nanaimo with notes indicating that each of those buildings has multiple businesses in it. This is because on the next sunny weekend, I will be going down to Nanaimo to survey all of those businesses, and I need to be able to see at a glance which specific buildings I need to survey. I will need to know the exact position of each business within each building, so what I end up putting into OSM as a result of this survey is an as-accurate-as-possible depiction of each building’s “floor plan”, if you will.

One of the reasons as to why I loved this image set was because it was almost centered completely from the top-down, which made tracing buildings far easier. This new set that was introduced makes it extremely hard now, and all of the already-traced assets like buildings and roads are now quite skewed when based off the new set. It’s frustrating.

日暮里駅南西側に所在する天王寺。毘沙門天であるが、一帯の霊園・墓地を構成する敷地を有することに今回は着目した。
「一帯の霊園・墓地」と記したが、都立谷中霊園・寛永寺墓地そして天王寺墓地が入り組んでいる。
都立霊園は比較的直線的に区画が整備されているが（マッピングされている訳では無いが）、天王寺墓地内は通路が入り組んでおり、寺のお坊さんも案内に苦労しているそうだ。また、都立霊園管理事務所で一帯の区画図が配布されているが、一応民有地ということか、配布地図では「天王寺墓地」という五文字だけで内部は空白表示である。
現地で猫と戯れつつ通路をマッピングしていった。また、銘板のある墓所は地物としてプロットした。
前述のように民有地として都の配布地図には載せていなかったが、墓地内に東京都教育委員会指定の墓所があった。なかなか筋を通すのは難しい土地の入り組みのようだ。
また、寺のお坊さんと更新した地図を見ながら、墓地内の無縁観音・千人塚、都立霊園内の天王寺銅造菩薩坐像台座跡を加えてマッピングした。

当日の天気は曇り、東京のサクラ開花宣言が気象台より出された日である。屋外行動には良い気候であった。花粉症は万全の備えで乗り切った。4時間程で現地での歩数は1万歩に達するか否かのラインであった。
天王寺境内のサクラも花開き始めており、霊園のさくら通りが見頃を迎える頃また花見に行きたいと思う。

了

i wish that we could pin locations, visible only on our account. it would make it a lot easier to keep track of multiple locations. i’m sorry if my formatting is wrong, or if i’m using this entry wrong. i’m very excited about this website, thank you!

.

Despite the apparent lack of public transit, Redmond Watershed Preserve is accessible with a bit of walking.

Redmond Watershed Preserve is a city park in Redmond, WA, abutting the Redmond Ridge development to the east, and the Puget Power Trail (aka PSE Trail) to the south. It is just outside of the walkshed that trip planning services use but is still reasonably easy and safe to get to using the Power Trail and some on-street walking, due to the Power Trail not actually being contiguous.

1. Catch the Metro 250 bus to Avondale from Bellevue TC, South Kirkland P&R, Kirkland TC, or Redmond TC. If you are traveling on a weekday make sure you are on a bus to Avondale and not Bear Creek P&R; Metro provides 15-minute service but at the expense of dropping the Avondale tail from half of the trips.
2. Get off at Avondale & Puget Power Trail and walk east.
   • If you need a bathroom or want to see some farm animals, you can detour to Farrel-McWhirter Park.
3. Take either the Power Trail or Perimeter Loop trail (if you detour to the park) to 196th Ave NE.
4. Walk N to NE 116th St
5. Walk E in the shoulder to 206th Ave NE.
6. Walk S to NE 112th Street, and then walk W to the continuation of the Power Trail.
7. Keep walking until you run into the Pipeline Connector Trail or Pipeline Regional Trail, both of which will take you through the Watershed Preserve.
8. When returning, simply follow the directions in reverse.

During the week, Metro’s 224 DART service runs along Novelty Hill Road and makes various stops in Redmond Ridge, but its lack of frequency makes trip planning tricky unless you’re willing to wait in a suburban waste for an hour or more.

https://github.com/skylarthompson/transithikes/blob/main/puget_sound/redmond_watershed_preserve.md

13/03/2025-19/03/2025

Mapping

• Comments are requested on these proposals:
  • Wheelchair users might need assistance in toilets and grab_rails=*, which is a handlebar-like support mounted on the wall, are vital information, since it aids in the movement from one’s wheelchair onto the toilet.
  • Standardise disc_golf_course=* mapping, including course type and equipment, to improve their display and analysis.
  • Deprecate socket:tesla_supercharger and socket:tesla_destination in favour of more generic manufacturer-independent charging plug tags instead of the Tesla-specific tagging schemes.
• This proposal is ready for voting:
  • contact_line=*: to precisely map contact lines for electric trains, trams or trolleybuses, including their physical properties. It can be voted on until Sunday 30 March.
• This proposal was approved:
  • catenary_mast=*: for the detailed recording of catenary masts (a structural support used in railway electrification systems to hold up the overhead catenary wires that supply power to electric trains), including their design and function. The proposal was adopted with 11 votes in favour, 0 votes against, and 0 abstentions.

Community

• InfosReseaux (with frodrigo) have spent some time in recent weeks developing quality controls for the French power grids on Osmose. There is a wiki page ► that documents the process.
• MapMyTree allows you to report the trees that you have planted within the EU to count towards the European Union’s pledge to reach 3 billion additional trees in the EU by 2030. Use the app to report and manage your planted trees, locate and browse for areas with tree-planting potential, and follow the progress of the European tree planting pledge.
• Rphyrin has challenged the notion that all instances of ‘tagging for the renderer’ equate to ‘lying to the renderer’, arguing that visually appealing OSM Carto symbols can, in fact, inspire mappers to contribute even more actively.
• tlohde is seeking recommendations for a web mapping course focused on embedding interactive map widgets into static websites.

Events

• From 28 to 30 November the OSM Africa community will host another exciting conference: State of the Map Africa 2025. It will be held in Dar es-Salaam, Tanzania and you are invited to participate as a sponsor or regular participant.
• Are you planning a little contribution ► at State of the Map France 2025? To propose one, go to Pretalx ► by Friday18 April.

OSM research

• HeiGIT reported that Milan Fila and others have published a paper on AI-generated buildings in OpenStreetMap. This study explored the impact of AI-generated data in OSM, addressing key research questions related to data identification, distribution, quality, and modifications over time using the ohsome API and OpenStreetMap History Database (OSHDB).

Humanitarian OSM

• Laura Bortoloni (University of Ferrara, Italy) interviewed Dr. Raquel Dezidério Souto (IVIDES.org), about her professional career and the mapping campaign held in response to the Rio Grande do Sul flood of April and May 2024. The advantages of using free and open source software plus open data were pointed out, as well as the difficulties faced by Brazilians in collaborative mapping aimed at disaster mitigation. The interview is also available as a PDF.

Software

• ^[1] Bastian Greshake Tzovaras has shared some updates on how recent code contributions have improved Amanda McCann’s before/after comparison-image pipeline, including creating time-lapse GIFs and running fully online without needing to install local tools.
• HeiGIT reported that MapSwipe, an open-source mobile and web app that enables volunteers to map missing geodata, now includes street-level imagery from Mapillary. This new feature allows users to to identify new objects and enrich existing ones with valuable attributes.
• Organic Maps explained that their GitHub account has been temporarily blocked, likely due to a contributor being geolocated in a US-sanctioned region. They have submitted all necessary documents and expect it to be resolved soon.

Programming

• In a blog series, exploring their newly developed OSM file format ‘OMA’, kumakyoo introduced a prototype Java library ‘OmaLibJava’, designed for working with and querying OMA files.

Releases

• The MapComplete team tooted that their latest version features a new theme, which allows users to view and annotate wayside shrines.

OSM in the media

• Selene Yang, one of the founders of Geochicas, spoke, in an interview ► for the Spanish newspaper El País, about the importance of OpenStreetMap in community processes where cartography is approached collectively and recognises the knowledge of different identities.
• Telepolis presented ► three advanced OpenStreetMap apps – OSMand, Komoot, and Gaia GPS – that support outdoor professionals with a range of features such as offline navigation, detailed route planning, and precise tracking for hiking, biking, and other outdoor activities.
• Employees of the city of Woldegk are discussing ►, under time pressure, whether the purchase of the AI-supported road detection software Vialytics is worthwhile, since advantages such as automated damage analysis are offset by existing concerns regarding the database maintenance effort and costs.

Other “geo” things

• Apple has launched the internal ‘Surveyor’ app to collect roadside data including street signs via partner company Premise, using user-submitted photos to enhance Apple Maps with more precise and up-to-date details.
• Bryan Cockfield, of Hackaday, reported that Chris Doble has taken on the challenge of developing a software-defined GPS receiver entirely from scratch. The project utilises an RTL-SDR dongle – a low-cost software-defined radio originally designed for digital TV reception – along with Python to achieve location accuracy within a few hundred metres. The receiver is capable of resolving a position within 24 seconds from a cold start and presents its data through a web-based interface.
• ‘PROJ’, the coordinate system transformation software that has been successful for decades, celebrated its 26th birthday and the geoObserver posted ► their congratulations.
• Raymond Zhong and Mira Rojanasakul, of The New York Times, have illustrated the far-reaching consequences of Earth’s warming climate through an interactive global map, highlighting several critical environmental shifts, including the mass death of coral reefs, thawing permafrost, the collapse of Greenland’s ice sheets, the breakup of West Antarctica’s ice, shifts in the West African monsoon, the loss of the Amazon rainforest, and the potential shutdown of Atlantic Ocean currents.
• OpenCage tooted a curated collection of geographical trivia about India.
• Christoph Hormann has released another expansion of his Musaicum satellite image mosaic, created using Sentinel-2 data. This update now includes coverage of the entire United States, including Alaska, Hawaii, and Puerto Rico.

Upcoming Events

Where	What	Online	When	Country
Stadtgebiet Bremen	Bremer Mappertreffen		2025-03-24
Derby	East Midlands pub meet-up		2025-03-25
Münster	FOSSGIS-Konferenz 2025		2025-03-26 – 2025-03-29
Fuenlabrada	Taller de OpenStreetMap en las IV Jornadas de Cultura Libre.		2025-03-26
Seattle	OpenThePaths 2025		2025-03-27 – 2025-03-29
	[Online] OpenStreetMap Foundation board of Directors – public videomeeting		2025-03-27
Zürich	Mapathon @ UZH DSI 2025		2025-03-28
Münster	FOSSGIS 2025 – OSM-Samstag		2025-03-29
Seropédica	Green Open Data Day 2025 (ou Dia Verde dos Dados Abertos 2025)		2025-03-31 – 2025-04-01
	Green Open Data Day (ou Dia Verde dos Dados Abertos)		2025-03-31 – 2025-04-01
Saint-Étienne	Rencontre Saint-Étienne et sud Loire		2025-03-31
Santa Maria Maior	Missing Maps Lisbon Mapathon with MSF		2025-04-01
Salzburg	OSM Treffen Salzburg		2025-04-01
	Missing Maps London: (Online) Mapathon [eng]		2025-04-01
San Jose	South Bay Map Night	✓	2025-04-02
Stuttgart	Stuttgarter OpenStreetMap-Treffen		2025-04-02
	OSMF Engineering Working Group meeting		2025-04-04
City of Canning	Social Mapping Saturday: Rossmoyne		2025-04-05
	OSMF Affiliation Focus Group Discussion: Thematic and non-geographical groups		2025-04-05
Delhi	15th OSM Delhi Mapping Party (Online)		2025-04-06

Note:
If you like to see your event here, please put it into the OSM calendar. Only data which is there, will appear in weeklyOSM.

This weeklyOSM was produced by HeiGIT, Raquel Dezidério Souto, Strubbl, TheSwavu, barefootstache, derFred, mcliquid.
We welcome link suggestions for the next issue via this form and look forward to your contributions.

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