How do I make a map of a California county showing population density?

https://community.openstreetmap.org/t/south-australia-road-classification-proposal/112068

Highway, Building, Barrier, Tower, Area, Landuse, and more.

if you history user of 2 years form highways this finding. was edit errors has been yandex map.

There is a long discussion happening in the United States section of the community forum regarding where to draw the line between the “main” populated place node values, and specifically the place=* values of city and town in New England. I thought it would be useful to do a bit of analysis to see how these values are distributed across the database when compared to population. Through this analysis, I include all tags which have place values of city, town, village, hamlet, and isolated_dwelling. I also only include nodes that have a population tag.

My overpass query for each category looks like this:

[out:csv(::id,place,population;true;"|")][timeout:60];
node[place=city][population];
out;

One of the challenges of analyzing this key is that because it represents order-of-magnitude differences, its distribution is log-normal. In other words, it forms a bell curve provided that the X-axis is drawn logarithmically.

To look at this data logarithmically, I grouped the place nodes logarithmically, in steps of 1, 2, and 5 per 10x jump. When viewing the distribution of place=town, the log-normal shape comes out quite clearly. The number on the X axis represents the upper limit of each bin.

Now that we’ve assessed that the data is distributed log-normally, the next question we want to be able to as is, for a populated place with a certain population, how are the place values distributed? For this, we look across each logarithmic “bin” and determine the percentage of each place value in use:

We can assess, for example, that for places with a population between 500 and 1,000 (the bin labeled “1,000”), it’s tagged place=village over 90% of the time. The village blip at 10,000,000 is the result of a data error - a single remote place node being erroneously tagged with a high population in a bin of size n=19. Needless to say, on the far right of this graph, there are fewer and fewer nodes in each bin.

Lastly, we would like know the mean and standard devation of each place category. However, since this is log normal, we need to compute the mean and standard deviation in the logarithmic domain, and then convert it back. The mean, and plus or minus two standard deviations are computed in the table below:

Thus, this means that 68% of place=town nodes – one standard deviation – that are tagged with a population tag, have a population= value between 2,814 and 36,422. Taking this out to two standard deviations, 95% of all place=city nodes have a population= tag value between 8,341 and 2,073,119.

Clearly, there is considerable overlap between each category, no doubt because of differences in tagging conventions between places, differences in accounting for population, and differences in place tagging in areas of different population density.

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Надійність та Підтримка У TDrive ми робимо все можливе, щоб ваша подорож пройшла без проблем. Наші автомобілі проходять регулярні технічні огляди, щоб гарантувати їх безпеку та надійність. Крім того, наша команда завжди готова надати вам підтримку та відповісти на всі ваші запитання.

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✔ Oficina sobre criação de web map com uMap e dados do OpenStreetMap

✔ Palestra sobre criação de web map com uMap e dados do OpenStreetMap

✔ Oficina sobre importação de pontos de interesse (POI) no OpenStreetMap

✔ Mini curso para a Defesa Civil (Brasil)

✔ Oficina sobre mapeamento de pontos de interesse (POI) com OpenStreetMap

✔ Special interview about Brazilian NSDI on the first anniversary of YouthMappers UFRJ

✔ Entrevista especial sobre a INDE no aniversário de 1 ano do YouthMappers UFRJ

✔ YouthMappers UFRJ receives the Women’s Participation Award!

✔ YouthMappers UFRJ recebe o Women’s Participation Award!

✔ Our participation in the Open Data Day YouthMappers at UFBA 2024

✔ Nossa participação no Open Data Day 2024 do YouthMappers at UFBA

✔ Web map do mapeamento colaborativo para redução de riscos e desastes (RRD)

✔ Web map of colaborative mapping for the Disaster Risk Reduction (DRR)

✔ Mapear POI no OpenStreetMap e exibir dinamicamente com uMap

✔ Mapping POI in OpenStreetMap and displaying dynamically with uMap

✔ Resultados do GIS DAY 2023!

✔ V Olimpíada Brasileira de Cartografia incluiu o OpenStreetMap como parte de sua etapa prática

✔ V Brazilian Cartographic Olympiad included OpenStreetMap as part of its practical stage

✔ Geocodificação com OpenStreetMap

✔ Mapeamento humanitário e OpenStreetMap

Вчера внезапно написал в mastodon (куда я окончательно переехал из твитера) про ситуацию с Overture и покемонами.

Для контекста, неделю назад Niantic (авторы Pokémon GO) объявили о новых покемонах, которые появляются только на пляжах. Игроки тут же начали рисовать ложные пляжи на OpenStreetMap. Так же, как семь лет назад они рисовали парки. Разумеется, это нагружает лишней работой картографов и растит досаду от Niantic и раздражение от покемоноводов.

Саймон Пул обратил внимание, что за эти семь лет компания Niantic не только не ответила на запросы OSMF или вообще хоть как-то связалась с сообществом. Вместо этого она вступила в фонд Overture Maps! Пользуется картой от добровольцев, но платит корпорациям, как так получилось?

Сюда наслаивается непонимание действий Linux Foundation, который вместо поддержки OSM взял под крыло Overture Maps и этим разделил «вину». Почему корпорациям везёт, а нам — нет?

Я уже писал, почему Overture — это хорошо, и почему OSMF пока нет смысла поддерживать. В треде mastodon примерно то же самое, потому что, как нас учил преподаватель по физике, важные мысли нужно повторять трижды.

* * *

Бизнес и фонды хотят поддерживать OpenStreetMap. Они видят огромное сообщество и пользу от карты для миллиардов людей и десятков тысяч организаций. Крупные фонды создаются для поддержки именно таких проектов, как наш.

Но у нас уже есть фонд. OSM Foundation. Все ожидают, что фонд помогает проекту расти: поддерживает картографов, сообщество, инструменты редактирования и валидации. Те инструменты, которые сделали бы вандализм от покемоноводов легко обнаружимым и откатываемым.

Разумеется, OSMF не просил и не собирался становиться частью Linux Foundation. Зачем нам? Ну и фонды, кажется, редко говорят между собой, это не бизнес.

Есть и другая группа. Она подготавливает геоданные и продвигает их организациям. В невиданном до сих пор масштабе, с известными корпорациями. Вместо коммерческой структуры они хотели оформить открытый фонд — и Linux Foundation им помог.

Да и почему бы и нет? Overture Maps — это открытые данные. Компании-участники уже хорошо проявили себя на поле open source. Они вкладывают серьёзные деньги в продвижение открытых геоданных и конкурируют с Google, а не с нами. Со всех сторон отлично.

Чего Linux Foundation не знают — это что на сегодня нельзя сказать, что OSMF поддерживает картографов. OSMF занят серверами, потребителями данных и конференциями. Почитайте темы ежемесячных встреч Совета.

Раньше осмеров поддерживали организации. HOT, Cloudmade, Mapbox, Grab. Но на сегодня они все отошли в сторону (или развалились). Некому больше нас поддерживать, кроме нас самих.

А когда ресурсов мало, люди начинают думать в терминах не совместной работы и развития, а соперничества и зависти. Overture Maps отъедает наши ресурсы!

Можете подумать: это же нормально, что OSM работает на энтузиазме. Но если обернуться, такая ситуация исключительно редка. Может, лет пять за всю историю проекта.

Проблемы сейчас у всего IT-сектора. Всюду увольнения, сокращения проектов. OSM их не избежал — вот в такой неявной форме. Все страдают, и мы тоже сами по себе. Как мы говорим, OSM — это боль, и нынче чуть больнее обычного.

Так что такие четыре наблюдения:

1. Высший уровень корпоративного членства в OSMF — 30 тысяч евро. Это смешная сумма, которая никому не поможет, поэтому ничего странного в том, что Niantic и другие не вписываются.
2. Overture Maps эффективны, стоят своих денег, и они заставят мир перейти на OpenStreetMap. Нам повезло, что они появились.
3. Поддерживать осмеров — это как поддерживать OpenSSL. Всем пофиг, кто и как делает карту, пока карта не ломается. Overture защищает пользователей от поломок.
4. На сегодня вообще нет способов поддержать картографов. И это не проблема Niantic или Linux Foundation.

На прошлых выходных члены Совета OSMF собирались на очную встречу, чтобы обсудить стратегию развития OpenStreetMap. Я насыпал им немного идей, так что есть шанс, что через пару лет наш фонд повернётся лицом и к корпорациям, и к нам.

Participação no Festival Latinoamericano de Instalação de Software Livre - FLISoL Rio 2024

A Dra. Raquel Dezidério Souto, presidenta do IVIDES.org® e do YouthMappers UFRJ, ministrou palestra na edição carioca do FLISoL 2024, sobre Web map com uMap e OpenStreetMap, abrangendo os assuntos:

1. Conceitos básicos relacionados ao web mapping;

2. Características, modelo de dados, licença, acervos de dados, conversores, editores, APPs do OpenStreetMap;

3. Características do uMap, suas vantagens e limitações;

4. Estudo de caso - Web Map da Infraestrutura para Redução de Riscos de Desastres (RRD) no Município de Maricá (Rio de Janeiro, Brasil).

Todos os arquivos da apresentação podem ser encontrados na pasta virtual, que inclui a cópia do vídeo.

O vídeo da sessão pode ser encontrado também no canal do IVIDES.org® no YouTube.

Um agradecimento especial ao público participante ao vivo e aos(às) espectadores remotos! Agradecemos ainda aos(às) organizadores(as) do FLISoL Rio 2024, que contribuem para a disseminação do Software Livre na nossa cidade!

IVIDES.org® é uma marca registrada. Para entrar em contato sobre esta ação: ivides@ivides.org.

One of the most rewarding aspects of being an OpenStreetMap contributor is the surprise of discovering where your contributions will be displayed next.

“I put that obscure, forgotten place back on the map, and now they’re everywhere!”

Researching toponyms is fun because I have to analyze the daily conversations among the locals and try to triangulate the place name centroid based on this conversations. Bonus point if my centroid triangulation somehow coincides with ancient, forgotten, historical maps.

Traces of Sepatan, Djati, and Rawa Roko can still be found on old historical maps, circa 1900. Locals still use these toponyms right now, despite the government’s refusal to acknowledge their existence in the official addressing system.

It’s ‘forgotten’ in the sense that the local government over here has simplified the toponym system too much. Some toponyms have been upgraded to official administrative region names (and are now embedded in the official addressing system), while the rest have been left behind. People still use these ‘left-behind’ toponyms daily to refer to certain places, even though the government has somewhat ‘discouraged’ their use. (The colonial administration did it better, though. When I consulted the archives and library for old maps, all of these ‘left-behind’ toponyms were actually mapped quite well in the past.)

And this situation has led to mass confusion for people. Government-mandated addresses often don’t reflect reality. People still use all those ‘left-behind’ toponyms in their daily activities, yet they don’t appear on official, government-mandated maps and addressing systems.

That’s one of my personal missions right now: to put all those ‘left-behind’ toponyms back on the maps.

OpenStreetMap (OSM) ist ein kollaboratives Projekt, das es Nutzern ermöglicht, Karten und geografische Daten frei zu bearbeiten und zu nutzen. Dieses „Wikipedia der Kartenwelt“ bietet detaillierte Informationen zu geografischen Standorten und lokalen Ressourcen, die von einer aktiven Gemeinschaft aus freiwilligen Kartografen ständig aktualisiert werden.

Verbesserte Sichtbarkeit für Arztpraxen

Einer der größten Vorteile von OpenStreetMap ist die erhöhte Sichtbarkeit, die es Arztpraxen bietet. Durch die Registrierung ihrer Praxis auf OSM können Ärzte und Ärztinnen sicherstellen, dass sie von potenziellen Patienten leicht gefunden werden. Dies gilt für allgemeinmedizinische Hausärzte ebenso wie für spezialisierte Fachärzte wie Zahnärzte, Hautärzte, Gynäkologen, Urologen, Chirurgen, Psychiater, Neurologen, Augenärzte, Kinderärzte und sogar Tierärzte.

Routenplanung und Erreichbarkeit

Für Patienten ist es oft eine Herausforderung, den Weg zur nächsten Arztpraxis zu finden, besonders in unbekannten Gegenden. OpenStreetMap kann hier Abhilfe schaffen, indem es genaue und benutzerfreundliche Karten zur Verfügung stellt, die nicht nur die Lage der Praxis zeigen, sondern auch Informationen zu öffentlichen Verkehrsmitteln, Parkmöglichkeiten und barrierefreiem Zugang bieten. Dies verbessert die Erreichbarkeit und Patientenfreundlichkeit enorm.

Lokale Vernetzung und Community-Support

OpenStreetMap fördert nicht nur die individuelle Sichtbarkeit, sondern unterstützt auch die Vernetzung innerhalb der lokalen medizinischen Community. Praxen können leichter Kooperationen und Überweisungsnetzwerke mit benachbarten Fachärzten aufbauen, was insbesondere für spezialisierte Disziplinen wie Neurologen oder Psychiater von Vorteil sein kann.

Katastrophenhilfe und Notfallsituationen

In Notfallsituationen oder bei Katastrophen kann OpenStreetMap lebensrettend sein. Durch präzise Karten können Rettungsdienste schneller den Ort einer Praxis erreichen. Ebenso können Praxen wie die eines Kinderarztes oder eines Tierarztes in Krisenzeiten wichtige Anlaufstellen in der Gemeinde sein.

Marketing und Patientenakquise

Die Präsenz auf OpenStreetMap kann auch als kostengünstige Marketingstrategie dienen. Indem Arztpraxen auf OSM erscheinen, können sie ihre Sichtbarkeit gegenüber neuen Patienten erhöhen, ohne in teure Werbekampagnen investieren zu müssen. Dies ist besonders für neu eröffnete Praxen oder solche in stark umkämpften Gebieten wie bei Zahnärzten oder Hautärzten von Bedeutung.

Fazit

Die Nutzung von OpenStreetMap bietet für Arztpraxen eine Vielzahl von Vorteilen. Von der verbesserten Sichtbarkeit und Erreichbarkeit bis hin zur Unterstützung durch die lokale Gemeinschaft und effizienter Notfallhilfe – die Vorteile sind vielfältig. Ob Allgemeinmediziner oder Spezialist, die Integration in OpenStreetMap kann maßgeblich dazu beitragen, die Qualität der Patientenversorgung zu verbessern und gleichzeitig die Praxis besser in der lokalen Gemeinschaft zu verankern.

[Semi-automated translation of the Italian diary entry]

On OpenStreetMap, a tree can be represented as a natural=tree node.

Leaf type 🌿

leaf_type is the most common tree-related tag in the database, this is because it is easily verifiable and is supported with a quest by StreetComplete. The values are broadleaved and needleleaved. Some argue that palms should not be tagged as broadleaved but with a value of their own, =palm.

Leaf cycle 🍂

This tag describes whether a tree is deciduous or evergreen. Most needleleaved tree species are evergreen, but this is not always the case, so do not infer this value automatically. You can add this value easily if you know the species, or more simply if it is autumn/winter. If not, you can try to see if satellite or street-level imagery taken at those times are available.

Genus and species 🌳

If you are not an expert, there are tools that can help you recognise the genus/species of a plant, such as Pl@ntNet and iNaturalist, both of which also exist as mobile apps. On OpenStreetMap there are many trees with species (or species:wikidata or species:xx) that do not have leaf_type or leaf_cycle. These values are of course identical for each species (and also for many genus) and can therefore be easily deduced. There are two lists on the OSM wiki that contain these values for genus and species.

MapComplete has a dedicated tree theme that can be used to enter the species while SCEE has a dedicated quest (“What is the genus or species of this tree?”).

Monumental trees 🏛️

Monumental trees can be mapped adding denotation=natural_monument. In Italy they are recorded by the Ministry of Agriculture, Food Sovereignty and Forests (Masaf) with annual updates. You can map them by adding ref:masaf, which is a unique code assigned by the ministry.

In Poland they are recorded by the ‘Generalna Dyrekcja Ochrony Środowiska’ (GDOŚ) (you can find many of them with a query natural=tree+ref:inspire=*), in Serbia many zapis (sacred trees) are mapped with ref:zapis while b-unicycling has recently documented the place_of_worship=sacred_tree tag to map rag trees in Ireland and Scotland.

Rendering 🎨

Trees are rendered on Carto as green circles with a brown dot in their centre, regardless of their attributes.

The Straßenraumkarte Neukölln renderer shows the trees differently according to leaf_type, circumference and diameter_crown. However, the web map only works for the Berlin district of the same name.

F4 Map and Streets GL (no longer updated) are 3D renderers that use the height tag. F4 Map distinguishes trees by foliage type and also supports some values to differentiate palm trees. Esri also has a 3D map that uses OSM data, and which should support height and also some genus values.

On the IMAGICO.De blog, there is an interesting article that goes into detail on possible renderings to highlight the various attributes.

QA 🛠️

There are more than 20,000 mapped trees, but QA tools are still few. That is why I created this MapRoulette project: Tree Validation.

There are challenges that compare values in the database with the largest values ever recorded in nature, for example trees taller than Hyperion. Other challenges concern uncommon or incorrect values of denotation, species, genus, leaf_cycle or leaf_type.

The hope is that in the future more and more tools will check on tree tagging. For now there is at least one open issue for Name Suggestion Index and one for Osmose/JOSM.

If you want to discuss trees on OSM, you can use the “tree” tag on the OpenStreetMap Community Forum.

Have fun mapping!

Su OpenStreetMap, un albero può essere rappresentato come un nodo natural=tree.

Leaf type 🌿

leaf_type é il tag maggiormente valorizzato nel database, questo perché é facilmente rilevabile (basta un’occhiata) ed é supportato con un’apposita quest da StreetComplete. I valori sono broadleaved (latifoglia) e needleleaved (aghifoglia). C’é chi sostiene che le palme non debbano essere taggate come latifoglia ma con un valore tutto loro, =palm.

Leaf cycle 🍂

Questo tag descrive la caduta fogliare, cioè se un albero é caducifoglio o sempreverde. La maggior parte delle specie di alberi aghifoglia sono sempreverdi, ma non é sempre così, non inferite quindi questo valore automaticamente. Questo tag é facilmente compilabile se conoscete la specie, o più semplicemente se é autunno/inverno. In caso contrario potete provare a vedere se sono disponibili immagini satellitari o foto a livello stradale scattate in quei periodi.

Genus e species 🌳

Se non siete esperti, esistono degli strumenti che possono aiutarvi a riconoscere il genere/specie di una pianta, come Pl@ntNet e iNaturalist, entrambi esistono anche come app mobile. Su OpenStreetMap esistono moltissimi alberi con species (o species:wikidata o species:xx) che non hanno leaf_type o leaf_cycle. Questi valori sono ovviamente identici per ogni specie (e anche per molti generi) e quindi possono essere facilmente deducibili. Sulla wiki di OSM esistono due liste che contengono questi valori per genere e specie.

MapComplete ha un tema dedicato agli alberi che può essere utilizzato per inserire la specie mentre SCEE ha una quest dedicata (“What is the genus or species of this tree?”).

Alberi monumentali 🏛️

Il Ministero dell’agricoltura, della sovranità alimentare e delle foreste (Masaf) ha censito (con aggiornamenti annuali) gli alberi monumentali d’Italia. Potete mapparli aggiungendo loro il tag denotation=natural_monument e ref:masaf. Quest’ultimo é un codice univoco assegnato dal ministero.

Solitamente un albero monumentale dovrebbe avere tutti i seguenti tag valorizzati: ele,species,species:wikidata,height,circumference,leaf_type e leaf_cycle. Questa query Overpass mostra gli alberi monumentali mappati al momento ed evidenzia quelli il cui tagging potrebbe essere migliorato: link

All’estero anche la “Generalna Dyrekcja Ochrony Środowiska” (GDOŚ) in Polonia censisce gli alberi monumentali (potete trovarne molti con una query natural=tree+ref:inspire=*), in Serbia molti zapis (alberi sacri) sono mappati con ref:zapis mentre b-unicycling ha recentemente documentato il tag place_of_worship=sacred_tree per mappare i rag tree in Irlanda e Scozia.

Rendering 🎨

Gli alberi sono renderizzati su Carto come dei cerchietti verdi con un puntino marrone al loro centro, a prescindere dai loro attributi.

Il renderer Straßenraumkarte Neukölln mostra gli alberi in modo differente in base a leaf_type, circumference e diameter_crown. La web map funziona però solo per l’omonimo quartiere di Berlino.

F4 Map e Streets GL (non più aggiornato) sono renderer 3D che utilizzano height per visualizzare l’altezza degli alberi. F4 Map distingue gli alberi per tipo di fogliame e supporta anche alcuni valori per differenziare le palme. Anche Esri ha una 3D map che utilizza dati OSM, e che dovrebbe supportare height e anche alcuni valori di genus.

Sul blog di IMAGICO.De esiste un interessante articolo che approfondisce possibili rendering per evidenziare i vari attributi.

QA 🛠️

Esistono più di 20.000 alberi mappati, ma gli strumenti di QA rimangono ancora pochi. Per questo motivo ho creato questo progetto MapRoulette: Tree Validation.

Ci sono challenge che confrontano i valori nel database con i valori più grandi mai registrati in natura, ad esempio alberi più alti di Hyperion. Altre sfide riguardano valori poco comuni o errati di denotation, species, genus, leaf_cycle o leaf_type.

La speranza é che in futuro sempre più tool proporranno check di vario genere sugli alberi. Per ora esiste almeno una issue aperta per il Name Suggestion Index e una per Osmose/JOSM.

Se volete discutere di alberi su OSM, potete utilizzare il tag “tree” sull’OpenStreetMap Community Forum.

Buon mapping!

18/04/2024-24/04/2024

Mapping

• Clay_C discussed the process of mapping pipelines using US government data, specifically from the Pipeline and Hazardous Materials Safety Administration. He outlined a detailed workflow for using JOSM to download and map pipelines within specific US counties, thereby increasing the accessibility and utility of the data for OpenStreetMap projects.
• Wikimedia Italia has published ► a short tutorial on how to start contributing to OpenStreetMap.
• The proposal for shop=tortilla is up for discussion.
• The proposal to set the key open=* is in the voting phase until Tuesday 7 May.

Mapping campaigns

• OpenStreetMap Belgium is hosting a mapathon on Wednesday 8 May, at 7 PM in the Muntpunt Café, Brussels, with an aim of reducing the number of open map notes in Belgium.

Community

• Branko Kokanovic shared a detailed guide to optimising the use of the Insta360 ONE RS 1-inch camera for capturing and uploading street-level imagery to Mapillary, including tips on camera handling, video splitting, and improving GPS tracking accuracy using software solutions such as Geoapify for map matching. The images can also be uploaded to Panoramax.
• Now that the call for contributions has closed, the State of the Map France 2024 is opening ► their platform for managing proposals for speakers and presentations using the ‘Pretalx’ software.

OpenStreetMap Foundation

• The OpenStreetMap Foundation’s Communications Working Group has provided an update on how to request support for social media posts or other communications. They have provided a detailed template for submissions aimed at streamlining the process of promoting community stories and events on OSM’s official social media channels.

Events

• FOSSGIS e.V. is currently seeking locations for the 2026, 2027, and 2028 FOSSGIS conferences. Interested parties have until Sunday 30 June to submit their applications via email, as detailed in their Call for Location document.
• The IVIDES Institute will be hosting ► an online workshop on the mapping of waterways in OpenStreetMap on Friday 10 May, at which Séverin Ménard (UN Mappers/UNGSC) will be participating. The call for registration is open ► and details can be found on the event page.
• The State of the Map US 2024 will be held at the University of Utah 6 to 8 June. Registration is now open and the conference programme has been announced.
• Swiss OpenStreetMap will hold a presentation and discussion on the upcoming report from the SBB and BAV (Bundesamt für Verkehr) on use of OpenStreetMap on Thursday 2 May from 5 to 6 pm.

Education

• Anne-Karoline Distel showed, in a short video, how you can support OpenStreetMap by capturing public notes.
• The IVIDES Institute held ► an event on importing points of interest into OpenStreetMap. Dr. Raquel Souto commented ► about this workshop in her diary, saying that she included, as an example, a subset of the 2022 Brazilian Demographic Census’ official data.

Maps

• The Agroecology map currently shows and describes 541 locations worldwide where ecological principles are being applied to agroecosystems. The same information is also available through an Android app.
• bopjesvla has developed Tiny World Map, a world map designed specifically for web applications that prioritise offline functionality and operate efficiently with limited bandwidth.
• Christoph Hormann explored potential future trends in map design within OpenStreetMap, critiquing the OpenStreetMap Foundation’s historical and current map rendering strategies. Hormann highlighted the challenges and limitations of the transition to vector tiles, which reduces operational costs but shifts a significant amount of data processing to the user side, potentially complicating map design and data management. The discussion also highlights the tension between technological efficiency and creative control over map design.

OSM in action

• Jacek Gęborys has created several maps visualising the accessibility of railway stations in various major cities. He used QGIS with OpenStreetMap as a source for the stops, in particular with the Overpass API, which allows you to automate the fetching of data and GraphHopper for calculating isochrones.
• The Russian OSM community has noticed that the mobile application lessy.app is using OSM data rendered in the style of Yandex.Maps.
• euroPathfinder and Barthwo, two active mappers, took part in the seminar ‘Route 3.0 and OpenStreetMap’ at the invitation of the Saarland Tourist Board ►. In their blog post euroPathfinder briefly presented ► Thomas Froitzheim’s seminar, in which Saarland tourism experts were trained to check the correct mapping of hiking and cycling tour routes in OSM. The tools used were uMap, BRouter Web, GPX Viewer and WayMarkedTrails.

Programming

• Rtnf has archived the OpenStreetMap help website before its planned shutdown.

Releases

• GraphHopper version 9.0 has been released. It comes with an improved GPX export, updated translations, many bug fixes, more route hints, and conditional access information.
• Aerosoft and Thera Bytes have launched a new PC farming simulation ‘Global Farmer‘, which lets players build farms anywhere in the world using OpenStreetMap data, incorporating real agricultural parameters and challenges.
• Roland Olbricht has announced the release of Overpass Version 0.7.62, including newly completed documentation on the user_touched filter and museum (attic) data, along with a detailed component overview for local server instances.

Did you know …

• … about the tools that allow you to select a bounding box, on a reference map, through a visual interface?
• … that the OpenStreetMap wiki has an A to Z to help you figure out how to tag objects?
• … that the Changelog page, on the the OSM wiki, documents recent changes to tagging strategies, listing new tags that have been added, modified, or deprecated?
• … that it is possible to create a city map with the help of OSM data? No? MyOSMatic is the solution for you!
• … that you can generate a specially styled OpenStreetMap-based map for the purpose of surveying an area by utilising RenderMyMap?

OSM in the media

• [1] ZDNet reviewed ► Panoramax, the digital commons platform, sponsored by IGN and OpenStreetMap France, which offers a free alternative to services such as Google StreetView. It features nearly 18 million terrain view photos contributed by various entities and aims to provide an open, decentralised system for sharing geolocated, ground-level photos under free licences that can be used for various applications, including urban infrastructure management.

Other “geo” things

• Wikidata’s ‘Coordinate Me 2024’ is an international competition taking place in May that encourages participants to improve or create new Wikidata items that have a coordinate location property, focusing on a variety of countries to improve global data coverage.
• swissinfo.ch explored the significant contribution of Swiss cartography and a Swiss entrepreneur, Samuel Widmann, to the development of Google Maps. It highlights Switzerland’s long tradition of detailed and accurate mapmaking, which laid the groundwork for the creation of global geodatabases and ultimately influenced modern digital mapping technologies. The story also details how Swiss innovations in map accuracy and aesthetics were crucial before Google acquired Widmann’s company, Endoxon.
• Google Maps is rolling out new features with the intention of addressing the common concern of locating charging stations, which are of interest to the owners of electric vehicles.
• Pierre Blanchet, from Meteory, has developed a machine learning model to monitor hedges across France by using aerial imagery.
• An article on TradingView explained the concept of mapping on a blockchain and discusses its potential to improve the accuracy, privacy, and security of geographic data compared to traditional GPS systems by using decentralised methods of data verification and storage. The article does not include the obligatory xkcd cartoon.
• ORBIS, the Stanford Geospatial Network Model of the Roman World, is an interactive tool hosted by Stanford University that simulates the logistics of travel and communication in ancient Rome. It allows users to calculate travel times and costs across various routes and modes of transportation, such as roads, rivers, and seas, based on historical data and geographic models.
• Actueel Hoogtebestand Nederland (Current height data Netherlands) provides an interactive viewer of detailed topographic data covering the Netherlands with approximately 950 billion measurements. This tool allows users to explore a high-resolution point cloud of the Dutch landscape, offering visualisation options such as height, intensity, reflections, and feature classification.

Upcoming Events

Where	What	Online	When	Country
Aachen	5. Treffen Aachener Stammtisch 2.0		2024-04-25
Potsdam	Radnetz Brandenburg Mapping Abend #6		2024-04-25
	OSMF Engineering Working Group meeting		2024-04-26
Prishtinë	Kosovo TomTom Editing Party		2024-04-26
Bengaluru	OSM Bengaluru Mapping Party		2024-04-27
	OpenStreetMap visual impaired accessibility initiative – kickoff (online)		2024-04-27
Fianarantsoa	State of the Map Madagascar		2024-04-28 – 2024-04-29
Brno	Missing Maps Mapathon at the Department of Geography		2024-04-29
Fianarantsoa	OSM Africa April Mapathon – Map Madagasikara		2024-04-30
San Jose	South Bay Map Night	✓	2024-05-01
Dresden	OSM-Stammtisch Dresden		2024-05-02
Essen	FOSSGIS-OSM-Communitytreffen 2024 Nummer 20		2024-05-03 – 2024-05-05
Bochum	OSM-Workshop		2024-05-05
臺北市	OpenStreetMap x Wikidata Taipei #64		2024-05-06
	Encontro OSM Brasil (online)		2024-05-08
	Missing Maps London Mapathon		2024-05-07
München	Münchner OSM-Treffen		2024-05-08
Lorain County	OpenStreetMap Midwest Meetup	✓	2024-05-09
Bruxelles – Brussel	Notes meetup		2024-05-08
Stuttgart	Stuttgarter OpenStreetMap-Treffen		2024-05-08
Rio de Janeiro	Oficina de mapeamento de waterways no OpenStreetMap – YouthMappers UFRJ		2024-05-10
Mainz	OpenStreetMap-Stammtisch Mainz		2024-05-11
	SotM Asia 2024 monthly meeting		2024-05-11
Zürich	163. OSM-Stammtisch Zürich		2024-05-13
Grenoble	Réunion groupe local Grenoble : Panoramax – L’alternative libre pour photo-cartographier les territoires		2024-05-13

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 MatthiasMatthias, Strubbl, TheSwavu, barefootstache, derFred, euroPathfinder, mcliquid, renecha, rtnf.
We welcome link suggestions for the next issue via this form and look forward to your contributions.

I’ve finished (for a second time!) mapping all the paths in my local cemetery. The first time another mapped decided that concrete or gravel ways designed for walking on weren’t “paths” and deleted them all. He also seemed to have strong feelings about people cycling in cemeteries, which is odd as The Greater Metropolitan Cemeteries Trust actually endorse it as a use of their land. As my daughter is buried in the cemetery I feel some ownership of the place, and do love it and Merlynston creek that flows through it. I’m hoping no one vandalises my work again.

I received a request to update my previous list of people who map every single day. The top 3 places remain the same, with Aurimas Fišeras passing the 10 year mark of non-stop mapping! Congratulations on an amazing accomplishment, and a big thank you to all of these dedicated mappers!

SotM Latam 2024 - Belém/Pará - Brasil.

The State of the Map Latam 2024 will take place in the city of Belém, Brazil, from December 6 to 8, 2024 at the Instituto Federal do Pará, this being the sixth edition of the ‘Latin American OpenStreetMap Conference’ and aiming to promote the use of OpenStreetMap (OSM), and the integration of OSM mappers, developers, open data communities, free and open source software communities, students, researchers, geoinformation professionals, non-governmental organizations, companies and public institutions.

SotM Latam 2024 After the voting period for choosing the SotM Latam 2024 logo has concluded, I am pleased to announce that the chosen option is 1.

You can see the results and voting details in the document shared above: https://docs.google.com/document/d/15Kbotyc6UCcWQ2K7apPOnfqXSSDFfvlDQtZxM_Nkag4/edit

Website: http://2024.osmlatam.org

https://wiki.openstreetmap.org/wiki/ES:LatAm/Eventos/State_of_the_Map_Latam_2024

You can see the voting results and details in the previously shared document: https://lnkd.in/dQcDDFCv

an organization of UMBRAOSM Union of Brazilian mappers from Openstreetmap, Latam Community and Foss4g

SotM Latam 2024 organizing committee

Contact: state@osmlatam.org

http://www.umbraosm.com.br

A Empresa Metropolitana de Transportes Urbanos de São Paulo (EMTU) anunciou um aumento significativo nas operações intermunicipais, adicionando 41 novas viagens em dias úteis em cinco linhas que servem diariamente cerca de 14 mil passageiros. A partir de 22 de abril de 2024, os usuários das regiões de Santana de Parnaíba, Francisco Morato, Jandira, Franco da Rocha e São Paulo experimentarão uma melhoria significativa na frequência dos serviços.

Detalhes da Ampliação do Serviço pela EMTU

As linhas metropolitanas que receberão os incrementos são operadas pela concessionária Anhanguera. Esta expansão inclui a adição de cinco novos ônibus, configurados para aumentar o conforto e a eficiência do transporte público nessas rotas.

A decisão de expandir as viagens foi baseada em um monitoramento contínuo e análises do Centro de Gestão e Supervisão da EMTU, que acompanha em tempo real a demanda e as operações dos ônibus.

Como Acessar os Novos Horários

Para os passageiros que desejam consultar os novos horários, a EMTU disponibiliza atualizações através de seu site oficial e pelo aplicativo para dispositivos móveis, disponível para iOS e Android.

Linhas com Incremento de Viagens

• Linha 852: Francisco Morato (Centro) para Santana de Parnaíba (Terminal Rodoviário da Fazendinha)
• Linha 346: Jandira (Jardim Nossa Senhora de Fátima) para Santana de 1. Parnaíba (Terminal Rodoviário Alphaville)
• Linha 352: Santana de Parnaíba (Cidade de São Pedro) para São Paulo (Lapa)
• Linha 216: Francisco Morato (Jardim da Alegria) para Franco da Rocha (Centro)
• Linha 386: Santana de Parnaíba (Várzea De Souza) para São Paulo (Pinheiros)

Sobre a EMTU

A EMTU, vinculada à Secretaria dos Transportes Metropolitanos do Governo de São Paulo, é responsável pela regulação e fiscalização do transporte intermunicipal nas cinco regiões metropolitanas do estado, que incluem São Paulo, Campinas, Sorocaba, Baixada Santista, e Vale do Paraíba / Litoral Norte. Com um serviço que atinge aproximadamente 2 milhões de passageiros por dia, a EMTU desempenha um papel crucial no desenvolvimento do transporte público eficiente e sustentável.

Years ago when searching for a viewpoint from an old photo where I wanted to do rail photography I managed to locate the exact cliffside overlook and discovered a somewhat hidden gem of trail network in the process.

Though there is an official dirt road in the canyon below and a few desire paths offshooting from it the hills above remained relatively unmapped not showing up in the otherwise void of an area.

With the understatement of the local forecast for the afternoon/evening I packed my beloved eTrex 20x in the camera bag along with my trusty Nikon D700 planning to take in some of the views while there in between tracing runs expecting no more than some cloudiness and a light sprinkling.

I had originally planned to do some averaging as well to mark down 3 of my favorite spots on the cliff to photograph the scenery below but just as I reached the overlook the light rain that had accompanied me on most of my journey up started to thicken and become slanted. Just as I positioned myself on the side of the ledge for my first point reading spot the wind had picked up considerably to near constant 70kph gusts. The eTrex wobbled fiercely atop the perching rock and I had to scrap my plans of more photos just to hold it still for fear it may fall to it’s death below as my other hand clinged to the rockface hoping to avoid a similar fate.

After 5 minutes to allow a good average I quickly hit save and climbed back up to grab my gear bag and make my way back down the path for the second tracing run in the opposite direction to help iron out anomalies when mapping from the trace. As I set off the steadily increasing rainfall now started to turn to almost sideways hail from every direction as the many rockfaces perturbed the wind. Though hectic as it may seem the eTrex managed to maintain it’s nice 8 foot accuracy throughout most of the trip and likewise I was similarly high spirits.

In an almost serene state of mind while walking the trails my attention drew to the contrast between the dramatic weather and environment and the life which springs forth from otherwise dead plains because of it. Many cacti once shriveled from the dry winter were now stuffed with water, their beautiful flowers blooming brightly pink which would soon bear fruit. The normally tan plains dead with brush now teeming with fluorescent wildflowers of all colors in every direction. In that moment I remembered who I was when escaping here 11 years ago, hurt and tired of the chaos and sterility of the urban design seeking to hide from the world and in the process discovering a new one all to myself.

It’s these things the fuel my passion for exploring and desire to document what’s around me, the eTrex always at my side as a faithful companion for so long now. The amount of memories and many long adventure it holds being priceless to me.

Nasrumikailkabira biyya keessa fi alaa kanneen ummata oromoo keessatti jireenya keessan aarsaa gootan galatoomaa

Summary: What if AI creates the Changeset Comments? We could send locations, tag types, and quantities to get an output. AI would have to be run locally with small models for cost and be validated by the user.

Problem 1: Time I assume that 1,000 users create 2 changes in 1 day. We assume that each change set takes 3.5 seconds. 1000 users *2 changes * 3.5 seconds per change = 7000 seconds. OSM Users spend about 1.9 hours per day.

Problem 2: Skill Outsourcing Users should spend time on the things AI can’t do.

Problem 3: Server Side Peer Review We have human generated changeset comments. We could create AI generated changeset comments. We could ask the AI, “are these 2 changeset comments so different that it looks malicious”?

General AI Inputs: 1. Location: Where did the user map? 2. Feature Types: What tags did the user use?

AI Prompt: “You are an AI system. A user made edits in OpenStreetMap, a collaborative mapping project. They mapped locations[Mappleville, MN, USA; Bobville, MN, USA] with tags[50xSidewalks, 20xMarkedCrossings, & 10xReligous Areas]. You will create a changeset comment that concisely tells human reviewers what this changeset was about in 3 sentences or less. Exact numbers are not important. Changesets describe changes, so don’t request anything. Don’t mention anything that is common across all changesets.”

AI Response (https://www.meta.ai/): “Added sidewalks, marked crossings, and religious areas in Mappleville and Bobville, MN. Improved pedestrian and accessibility mapping. Enhanced local community information.”

Specific AI Inputs for Locations: 1. Cities[1 to 5], States[1 to 5], Countries[1 to 5]. 2. Is this a place with unclear boundaries? (What if somebody maps the ocean) 3. What is the size of the bounding box for this edit in KM?

Specific AI Inputs for Feature Types: Tags[1 to 6] & corresponding Quantities

Algorithms: 1. Sort the following tags by how frequently each was used in descending order and a limit of 5. 2. For each city, how often was each tag used? Create a table unless the table is huge.

Complexities of the process: 1. Disputed Boundaries: This was the changeset that changed the boarder. 2. Large Edits: Do not run this edit over changesets larger than 500 edits. 3. Malicious Inputs: Somebody named a building tag after a war crime. The AI received that as an input. What does the AI say? 4. Resource Allocation: Developer Time could be better spent doing something else. 5. Irregular Edits: I will use every tag in OSM only once. I will map an area the size of a continent.

Complexities of AI in general: 1. Uncommon Languages: Are these things only good at the 5 biggest languages? 2. Edit Safety: The user mapped religious areas in 2 different nations that share a disputed boarder and are in a war. 3. Money: Laptops with TPU’s are not common in 2024 (but will be in 2030). Mobile Editors with TPU’s are not common in 2024 (but will be on high end phones in 2030). Running AI costs money. Who will pay for it?

Solutions: 1. AI runs locally on a TPU. 2. If you use the outputs of an AI for changeset comments, you are responsible for safety.

Disclaimers: 1. I don’t work in AI. 2. I describe what I don’t have the resources to build. 3. I assume that developer resources should focus on high priority tasks.

Expected Development Difficulty: 1. Web to TPU is hard: Graphics have standard libraries (OpenGL). AI TPU’s are not common and don’t have standard libraries. 2. This can create giant tables if you are not careful.

The benefits of manual changesets: 1. Spam is harder to create in bulk. 2. Self reflection is encouraged. 3. Individuality is good to see. 4. Changesets are the alternative to the Change Approval Board (CAB meetings). It is supposed to take effort.

TLDR: OpenStreetMap (OSM) edits could be aided with AI-generated changeset comments, potentially saving users 1.9 hours daily. AI could analyze edit locations and feature types to generate concise comments, freeing users to focus on tasks that require human expertise. However, implementing AI-generated comments requires addressing complexities like disputed boundaries, TPU libraries, and malicious inputs.