ร้านดีกว่านีไม่มีอีกแล้ว

ร้านดีกว่านีไม่มีอีกแล้ว

StravaTracer — новый плагин для JOSM: щёлкните по тропе на тепловой карте Strava, и он нарисует недостающую линию.

Что он делает

• идёт по центру следа на тепловой карте, а не по его краю;
• подстраивается под популярность тропы, поэтому и малопосещаемые, и популярные тропы работают с одними и теми же настройками;
• перескакивает через прерывистые участки малопосещаемых троп и догружает тайлы, если тропа продолжается;
• не трогает то, что уже нанесено на карту, и соединяет концы новой линии с существующими;
• создаёт одну линию для выбранной тропы; ответвления можно добавлять по одному.

Всё это одна команда: Ctrl+Z отменяет её.

Как пользоваться

1. Установите stravatracer в JOSM: Настройки → Модули (JOSM 19613 или новее).
2. Откройте слой тепловой карты Strava. Проще всего это сделать с помощью расширения для браузера JOSM Strava Heatmap: оно само настраивает URL и cookies.
3. Выберите режим Strava trace на левой панели инструментов и щёлкните по тропе.

🎬 Видео с демонстрацией

Всегда проверяйте

Тепловая карта показывает, где ходят люди, но не то, существует ли там настоящая дорога и какого она типа. Сверяйте результат со снимками, ставьте правильные теги (по умолчанию highway=path) и отправляйте только то, в чём уверены.

Код, документация и сообщения об ошибках: https://github.com/erickdeoliveiraleal/josm-strava-tracer. Буду рад отзывам!

Плагин основан на идее и алгоритме osm-strava.

StravaTracer est un nouveau greffon JOSM : cliquez sur un sentier de la carte de chaleur Strava et il dessine la voie manquante.

Ce qu’il fait

• il suit le centre de la trace de la carte de chaleur, pas son bord ;
• il s’adapte à la fréquentation du sentier : les sentiers peu et très fréquentés fonctionnent avec les mêmes réglages ;
• il franchit les parties discontinues des sentiers peu fréquentés et télécharge d’autres tuiles quand le sentier continue ;
• il ignore ce qui est déjà cartographié et raccorde les extrémités de la nouvelle voie aux voies existantes ;
• il crée une seule voie pour le sentier cliqué ; les embranchements peuvent être cliqués un par un.

Tout est une seule commande : Ctrl+Z l’annule.

Comment l’utiliser

1. Installez stravatracer dans JOSM : Préférences → Greffons (JOSM 19613 ou plus récent).
2. Ouvrez la couche de la carte de chaleur Strava. Le plus simple est l’extension de navigateur JOSM Strava Heatmap, qui configure l’URL et les cookies pour vous.
3. Choisissez le mode Strava trace dans la barre d’outils de gauche et cliquez sur un sentier.

🎬 Vidéo de démonstration

Vérifiez toujours

La carte de chaleur montre où les gens passent, pas s’il existe une vraie voie ni de quel type. Vérifiez le résultat avec l’imagerie, mettez les bons attributs (highway=path par défaut) et n’envoyez que ce dont vous êtes sûr.

Code, documentation et rapports de bugs : https://github.com/erickdeoliveiraleal/josm-strava-tracer. Les retours sont les bienvenus !

Le greffon s’appuie sur l’idée et l’algorithme d’osm-strava.

StravaTracer es un nuevo plugin para JOSM: haz clic sobre un sendero del mapa de calor de Strava y dibuja la vía que falta.

Qué hace

• sigue el centro del trazo del mapa de calor, no su borde;
• se adapta a la popularidad del sendero, así que los senderos poco y muy usados funcionan con el mismo ajuste;
• atraviesa los tramos entrecortados de los senderos poco usados y descarga más teselas cuando el sendero continúa;
• ignora lo que ya está mapeado y conecta los extremos de la vía nueva con las vías existentes;
• crea una sola vía para el sendero en el que hiciste clic; los ramales se pueden trazar uno a uno.

Todo es un único comando: Ctrl+Z lo deshace.

Cómo usarlo

1. Instala stravatracer en JOSM: Preferencias → Complementos (JOSM 19613 o posterior).
2. Abre la capa del mapa de calor de Strava. La forma más fácil es la extensión de navegador JOSM Strava Heatmap, que configura la URL y las cookies por ti.
3. Activa el modo Strava trace en la barra de herramientas de la izquierda y haz clic sobre un sendero.

🎬 Vídeo de demostración

Revisa siempre

El mapa de calor muestra por dónde pasa la gente, no si existe una vía real ni de qué tipo es. Comprueba el resultado con las imágenes, pon las etiquetas correctas (highway=path por defecto) y sube solo lo que tengas claro.

Código, documentación y reportes de errores: https://github.com/erickdeoliveiraleal/josm-strava-tracer. ¡Las sugerencias son bienvenidas!

El plugin se basa en la idea y el algoritmo de osm-strava.

O StravaTracer é um novo plugin do JOSM: clique numa trilha do heatmap do Strava e ele desenha a via que falta.

O que ele faz

• segue o centro do traço do heatmap, não a borda;
• se adapta à popularidade da trilha, então trilhas pouco usadas e muito usadas funcionam com o mesmo ajuste;
• atravessa os trechos picotados das trilhas pouco usadas e baixa mais tiles quando a trilha continua;
• ignora o que já está mapeado e liga as pontas da via nova às vias existentes;
• cria uma via só para a trilha clicada; os ramos podem ser clicados um a um.

Tudo é um único comando: Ctrl+Z desfaz.

Como usar

1. Instale o stravatracer no JOSM: Preferências → Plugins (JOSM 19613 ou mais novo).
2. Abra a camada do heatmap do Strava. O jeito mais fácil é a extensão de navegador JOSM Strava Heatmap, que configura a URL e os cookies para você.
3. Ative o modo Strava trace na barra de ferramentas da esquerda e clique numa trilha.

🎬 Vídeo de demonstração

Revise sempre

O heatmap mostra por onde as pessoas passam, não se ali existe uma via de verdade, nem o tipo dela. Confira o resultado com as imagens, coloque as tags certas (highway=path por padrão) e só envie o que você tiver certeza.

Código, documentação e relatos de erros: https://github.com/erickdeoliveiraleal/josm-strava-tracer. Sugestões são bem-vindas!

O plugin é baseado na ideia e no algoritmo do osm-strava.

StravaTracer is a new JOSM plugin: click on a trail of the Strava heatmap and it draws the missing way for you.

What it does

• follows the centre line of the heatmap trace, not its edge;
• adapts to the popularity of the trail, so rarely and heavily used trails work with the same settings;
• crosses the broken parts of rarely used trails and downloads more tiles when the trail goes on;
• ignores what is already mapped and connects the ends of the new way to the existing ways;
• creates a single way for the clicked trail; branches can be clicked one by one.

Everything is one command: Ctrl+Z undoes it.

How to use it

1. Install stravatracer in JOSM: Preferences → Plugins (JOSM 19613 or newer).
2. Open the Strava heatmap layer. The easiest way is the JOSM Strava Heatmap browser extension, which sets the URL and the cookies for you.
3. Select the Strava trace mode in the left toolbar and click on a trail.

🎬 Demo video

Please review

The heatmap shows where people go, not whether there is a real way there, nor its type. Check the result with the imagery, set the right tags (highway=path by default) and only upload what you are confident about.

Code, documentation and bug reports: https://github.com/erickdeoliveiraleal/josm-strava-tracer. Feedback is welcome!

The plugin is based on the idea and the algorithm of osm-strava.

Disclaimer: Do not try this at home!

There is an ongoing DRC Ebola campaign where mappers are asked to update residential areas. All newly published projects follow the same pattern. There are a lot of small tasks to be mapped. The tasks are so small that no new residential areas need to be mapped in them. Only the existing mapping needs to be updated (move or delete buildings based on the imagery required by the project). Often the task area is completely empty.

Since the deployment of the v5.4.1 release and the panel rearrangement, completing a task takes more clicks than in the previous version. Even if you’re an experienced mapper who read the instructions before you started, the Instructions tab still opens first, so you have to switch to the Completion tab and scroll past the additional instructions to submit the task. Considering the small tasks in the campaign, the time it takes to submit a single task is more than half of the total time spent on mapping.

This is where laziness kicks in. And so does the Tasking Manager API.

The goal? Find patterns and use whatever means to speed up the process.

Prerequisites that must be met:

1. No other mappers are active on the project. This matters because you work within the area defined by the project’s task grid without locking the tasks.
2. You upload regularly to prevent conflicts (a mapper who locks a task in the Tasking Manager always takes priority over any changes you made there without locking it).

Validators may be suspicious when so many tasks are marked as mapped within seconds of each other. This diary documents the process and explains why these tasks met all the requirements to be marked as mapped.

The technical workflow in JOSM:

1. Download the project’s task grid (using the TM API). Each task boundary has its ID and status.
2. Using the search function, find the right number of small unmapped tasks with the query taskStatus=READY waylength:-300 (only the unmapped tasks with a perimeter under 300 meters).
3. In the Tags/Memberships window, right-click the <X different> value of the taskId key and copy the list of values into a text editor for later.
4. Use Download along to download all OSM data for the selected tasks as a new layer.
5. Now add the task boundaries to the TODO list.
6. Inspect the tasks one by one and mark each one as done in the TODO list.
7. Upload the data to the OSM server (don’t forget to fill in the project’s changeset comment).

The Python script (outside JOSM):

1. Use the project ID and the saved taskId list as input.
2. A small script iterates over the taskId list and calls the TM API to lock each task and mark it as mapped (two API calls per task).
3. If the script fails to lock a task, it skips it and moves on to the next one.

That completes the first iteration, and you can start over. The project’s task grid needs to be downloaded again to get the updated task statuses. Change the search query from waylength:-300 to waylength:-620. The rest of the steps remain the same. Don’t forget to update the taskId list for the script. The third iteration uses waylength:-950.

The result

After three iterations, 70% of the project was mapped and I saved roughly 5,000 mouse clicks and a great deal of time. At the time of writing, I had already used this workflow on five projects and mapped over 4,500 tasks. I didn’t encounter any merge conflicts.

Notes

I found that, for me, the sweet spot is around 200–400 tasks per batch. You can tweak the waylength value in the search query (all tasks smaller than…) to achieve the right number of tasks in the selection. The biggest slowdown was the OpenAerialMap imagery used in the Ebola campaign because its tiles load quite slowly.

When I only deleted features in a task, I just moved to the next task and uploaded the data every 100 tasks. If another mapper who locked the task had already deleted the same object, JOSM showed a warning that it no longer existed on the server, and the upload continued. If I added any features to a task, I uploaded the data immediately so my changes were already on the server in case someone else locked the task.

Conclusion

On every project, I stopped once all tasks matching waylength:-950 were done. Larger tasks take longer to update, so bypassing the Tasking Manager brings little benefit, and I suggest returning to the regular workflow with task locking.

Právě vznikla tištěná turistická mapa Prahy, na základě aktuálních dat OpenStreetMap. Je určená lidem, kteří do Prahy přijeli na pár dnů a chtějí se rychle zorientovat v tom nejzajímavějším, co Praha nabízí.

Mapový podklad je záměrně jednoduchý. Obsahuje síť ulic a jen nezbytné množství dalších informací. Díky tomu zůstává přehledný a dává prostor tomu dalšímu. Přibližně stovce zajímavých míst, která jsou na mapě vyznačena pomocí malých ilustrací a popisků. Vedle známých historických památek jsou tu i ty méně známé, moderní stavby, veřejné umění nebo technické zajímavosti.

Asi vás napadne, proč ještě dnes tisknout mapu, když máme telefony i encyklopedie v kapse. Odpověď je jednoduchá. Nejde o náhradu digitálních map. Ty používáme všichni. Papírová mapa jen nabízí jiný pohled na totéž.

Rozložená ukazuje celé historické město najednou. Vidím vzdálenosti mezi místy, představím si kudy se vydám na první pohled - a nechám oči chvíli bloudit po ulicích. Je to trochu pomalejší způsob, jak se zorientovat. A právě v tom je kouzlo map, na které už tak trochu zapomínáme. Na ostrém slunci zůstává čitelná, nepotřebuje baterii a můžete si do ní poznačit tužkou místo, které vás zaujalo. Po návratu domů se mapa promění ve vzpomínku na navštívená místa. Na zadní straně jsou stručné informace o nejvýznamnějších pražských památkách v devíti světových jazycích. Je to základní přehled bez nutnosti je hledat.

Trochu se chlubím. Graficky jsem ji připravil, vyzkoušel si, jak na každém milimetru, na každém odstínu záleží. Vydali jsme ji ve vydavatelství, v kterém se turistickým publikacím už nějakou dobu věnujeme. Je tu vidět síla čerstvých mapových dat, za nimiž stojí komunita a tak trochu i moje znalost rodného města. Míst je hodně, ale vybrat z nich sbírku vzpomínek které mám v srdci, na to už databázový dotaz nestačí. Chtěl jsem ukázat Prahu jako rozmanité a přitom ne zas tak veliké město. Nejen jako ukazovač tras od startu do cíle.

Pokud vám během návštěvy Prahy mapka pomůže jen jednou, splnila účel. A možná se tak připomene, že pomalý analogový svět ještě neřekl poslední slovo. S pomocí nových zkušeností je později můžeme propojit s budoucností.

A new printed tourist map of Prague has just been published, built directly on up-to-date OpenStreetMap data. It is designed for visitors who arrive in the capital of the Czech Republic for a few days and want a quick, clear orientation to the very best the city has to offer.

In static cartography, the base map is intentionally kept minimal. It features the street network alongside only the essential geographic elements. This clean background leaves ample room for what matters most: roughly one hundred curated points of interest, brought to life with small custom illustrations and brief labels. Beside iconic historical landmarks, the map highlights lesser-known sights, modern architecture, public art, and unique engineering points of interest.

You might wonder why anyone would print a physical map today, when we all carry navigation apps and encyclopedias in our pockets. The answer is simple: it isn’t meant to replace digital tools. We all use those daily. A paper map simply offers a different perspective on the same space.

Unfolded, it presents the entire historic city at a single glance. You can feel the true distances between places, plot out a walk visually, or simply let your eyes wander across the streets. It invites a slightly slower pace of orientation—a classic form of spatial magic we sometimes forget in the digital age. It stays perfectly legible in bright sunlight, requires no battery, and lets you mark your favorite spots with a pencil. Long after you return home, it turns into a tangible keepsake of your journey. On the back, concise overviews of Prague’s major sights are provided in nine languages, offering quick context without needing to search online.

To be a bit personal: I had the privilege of working on the graphic design and cartographic preparation for this project, testing firsthand how much every single millimeter and color nuance matters in print. It was published by our team, where we’ve been crafting travel publications for years. The finished map really showcases the strength of fresh, community-driven OSM data combined with a lifetime of personal knowledge of my hometown.

While database queries can easily return thousands of locations, filtering them down to a meaningful collection of memories requires a human touch. I wanted to show Prague as a rich, diverse, yet walkable city—not just calculate the fastest route from point A to point B.

If this map helps you navigate or discover something new during your visit, even just once, it has fulfilled its purpose. And perhaps it serves as a gentle reminder that the slow, tactile world still has plenty to offer—especially when powered by open data and brought forward into the future.

After integrating OpenStreetMap data into my own application, I noticed inaccurate or missing business information, so I started correcting it directly on OSM.

Транспортная компания «Возовоз» сократила сроки грузоперевозок в Пятигорск из нескольких крупных городов России. Обновлённые условия позволяют быстрее доставлять коммерческие и частные отправления, планировать поставки и оптимизировать логистику между регионами.

Новые сроки доставки в Пятигорск

Теперь доставка сборных грузов в Пятигорск занимает:

• Москва — Пятигорск: от 3 до 5 дней;
• Санкт-Петербург — Пятигорск: от 4 до 6 дней;
• Ростов-на-Дону — Пятигорск: от 1 до 3 дней.

Сокращение сроков особенно актуально для компаний, которым важно своевременно пополнять складские запасы, отправлять товары покупателям и поддерживать регулярные поставки. Частные клиенты также могут быстрее пересылать мебель, технику, личные вещи и другие разрешённые к перевозке грузы.

Перевозка сборных грузов по России

«Возовоз» специализируется на автомобильных грузоперевозках, в том числе на доставке сборных грузов LTL. Отправления нескольких клиентов объединяются в одной перевозке, поэтому для доставки небольшой или средней партии не требуется заказывать отдельный автомобиль целиком. Такой формат подходит для товаров, оборудования, комплектующих и других коммерческих грузов.

В зависимости от задачи можно оформить межтерминальную перевозку или заказать доставку от двери до двери. Стоимость грузоперевозки рассчитывается с учётом маршрута, веса и габаритов отправления, а также выбранных дополнительных услуг.

Рассчитайте стоимость перевозки

Чтобы узнать стоимость и срок доставки в Пятигорск, воспользуйтесь онлайн-калькулятором и рассчитайте доставку. Укажите город отправления, параметры груза и подходящий формат доставки — система поможет рассчитать стоимость перевозки и спланировать отправку.

Сокращённые сроки на направлениях из Москвы, Санкт-Петербурга и Ростова-на-Дону делают грузовую доставку в Пятигорск удобнее.

양도소득세 너무 많이 나와요..

We had an awesome, hop-py time with the UPRI YouthMappers! The other day, I had an opportunity to facilitate a mobile-first workshop where we got hands-on with Vespucci, swapped mapping tips, and learned to read topographic maps for clues about where watercourses might be. We also tackled tagging questions and talked about ways to join our #ChasingWaterways campaign.

Icebreaker participants launching themselves forward. Can you guess how this exercise is relevant to our theme?

Kudos to our hosts

A big thank-you to Feye and the lovely UPRI OSM mapping team—Erika, Raf, Steph, and Ureil—for hosting and organizing the day. I’m glad to finally tie faces to familiar, waterway-chasing usernames. It was also great to meet both current YouthMappers and a bunch of hopeful new applicants.

Everyone already knew their way around iD/Rapid, and the more experienced mappers were using JOSM, so we skipped the beginner stuff and dipped our toes into Vespucci. sometime ### Mapping from your pocket

Vespucci was a great fit for the day: it’s made just for Android, but gives mappers an option for editing on the go, and has powerful tools for more complex tasks. It can also handle MapRoulette tasks, though a recent security incident temporarily took the MapRoulette API offline. That meant awkwardly switching apps, which could get tedious when you’re on a roll.

We spent the morning exploring the app basics – plus some of the more advanced features, answering questions, and sharing ways to use of other resources alongside aerial imagery to spot waterways and check flow directions.

One of the tools we had fun with was visualizing waterways with #WaterwayMapOrg, and how all rivers flow to the sea. Or not.

Some questions—like whether Vespucci can “square” buildings or draw round shapes—also got us talking about the little editor features we all get attached to.

After a hearty lunch, it was time for a mini mapa-thon! We worked on #TulayTuloy, a beginner-friendly bridge-mapping project and a fun side quest to our bigger waterway campaign. Bridges are important structures—and useful landmarks right over the water.

How far can you jump?

We were curious about the familiar OSM rule of thumb that a stream is something an active, able-bodied person can jump across. Our project guidelines use 2 meters as the cutoff, so we put it to the test.

Most jumps landed around 1.3 meters, and the longest was 1.8 meters. No one cleared 2 meters—and there were a few laughs when people realized just how wide that is!

Afterwards, I heard somebody made a pun #TalonTalon, after the #TulayTuloy hashtag.

My favorite part of the day was exploring DEMs, contour lines and hill shading. Topographic maps can be especially useful when imagery is cloudy or unavailable, and participants were amazed that they can spot features they’d missed before once they knew what and where to look.

After all that hopping, we dove into waterway mapping, where we discovered the limitations of using small screens, explored and tried workarounds, and still managed to complete tasks, giving everyone a chance to polish their new Vespucci editing skills.

Want to try to map a waterway near you? Find a #ChasingWaterways task and give it a try!

Hop-py folks, happily posing for a group-fie.

We’ve already penciled a date for another mapa-thon next month, and we’d be very happy to see you join us, whether you map with Vespucci, or the more usual suspects: iD/RapiD or JOSM.

We’ll post a message as soon as we nail down the details. Watch for announcements in the local communities’ channels.

P.S. I’m pleased to share that many of the issues we faced with the Maproulette mobile interface has been addressed in the upcoming version 4, hopefully, that means we’d have a smoother workflow for Vespucci users in the next mapa-thon.

Ludell is a small township in Rawlins County, Kansas. I’ve mapped every building, road, the stream that goes through it.

1. OBSTACLE osm.wiki/Key:obstacle Celem tego znacznika jest oznaczanie przeszkód, które nie wynikają z właściwości drogi (nawierzchni, materiału, szerokości itp.), lecz z jej otoczenia lub właściwości lokalnych; podobnie oznacza miejsca, w których droga (najczęściej drogi wodne) napotyka przeszkody środowiskowe. Ten znacznik może być używany w aplikacjach nawigacyjnych do omijania obszarów lub wykorzystywania części drogi o niższym priorytecie podczas obliczania tras, podobnie jak w przypadku progów zwalniających, przepraw promowych lub dróg nieutwardzonych, ale może być również używany na ścieżkach przeznaczonych dla pojazdów.

Tego klucza używa również zespół Humanitarian OSM .

1. overgrown=*- Oznacza, że ​​dany obiekt, zwykle autostrada, jest porośnięty roślinnością.

If you hike, ski, or drive in North America, your OsmAnd terrain may already be much sharper than you think. Since spring 2026, terrain maps and contour lines for the United States (including Alaska), Canada, and Mexico are built from high-resolution national elevation data. If you have not updated these maps since then, you are still looking at the old, smoother relief.

What Changed​

The new maps use elevation data with about 10 m resolution in the mainland United States and about 30 m in Alaska and most of Canada and Mexico. In practice, that means smaller ridges, narrower gorges, and steeper cliffs show up where the map used to smooth them out.

The update covers two map types:

• Terrain maps (3D) — the base for 3D relief, Hillshade, and Slope layers.
• Contour lines — regenerated from the same new data, so they match the relief exactly.

More detail takes a bit more space: updated maps are up to one and a half times larger than before.

Data: USGS 3D Elevation Program (via The National Map and OpenTopography), including data from Natural Resources Canada (NRCan) and INEGI (Mexico).

Updated Regions​

• United States, including Alaska
• Most of Canada and Mexico

See It in the Grand Canyon​

Few places test a terrain map like the Grand Canyon. Seen from above, the side canyons branch out in fine detail, and the contour lines follow every bend of the walls down to the Colorado River.

Tilt the map into 3D, and the canyon rises off the screen: Plateau Point, Skeleton Point, and the trail down to Phantom Ranch sit right where the terrain says they should.

Works Offline​

Terrain maps are stored on your device, just like the rest of your OsmAnd maps. Once downloaded, the relief, contour lines, and 3D view keep working without an internet connection, which is handy at the bottom of a canyon, where signal is rarely part of the scenery.

How to Get the Update​

Terrain maps downloaded before May 2026 still contain the old data. Open the Updates tab in Maps & Resources: if terrain or contour line maps for these regions are listed, update them. There is no need to delete the old files first. If you do not have them yet, download the Terrain map (3D) and Contour lines for the regions you need. Terrain and contour line maps require OsmAnd Maps+ or Pro; 3D relief requires OsmAnd Pro.

Questions or Issues​

If something looks off or you have questions, contact OsmAnd support at support@osmand.net, or visit the Support page for more help options.

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Every night across southern Iraq, hundreds of gas flares burn over some of the largest oil fields on earth. They torch associated gas that could light millions of homes — in a country where those same homes get a few hours of grid power a day and the rest from diesel generators. The gas is burned because capturing it was never built. The flames are visible from space, yet on the ground almost no one is counting them.

So I built Iraq Flaring Watch to count them in public — a live map of Iraq’s flaring, what it’s wasting, and who it’s affecting. This diary is about how it came together, and why OpenStreetMap ended up at the centre of it.

What it is

Iraq Flaring Watch is a single-page map that pulls open scientific data together in one place:

OpenStreetMap

the flare locations themselves — every flare on the map is an OSM man_made=flare node, so what you see is what mappers have put on OSM. There are two modes: a preloaded layer (a saved Overpass snapshot committed to the repo) that keeps load off Overpass and gives me a stable baseline to spot vandalism against, and a Live OSM option that pulls the current data straight from Overpass in real time.

NASA FIRMS (VIIRS)

near-real-time satellite fire detections, so you see what the satellites saw in the last few days, not a static snapshot.

Carbon Mapper

satellite methane and CO₂ plume detections (Tanager), showing which flares are leaking as well as burning.

World Bank

global flaring data, for the volumes and the national baseline.

WorldPop

the population raster, intersected with flare buffers to estimate the people living within 5 km of a flare.

Leaflet.js

the open-source engine that draws it all, with no proprietary basemap and no API gatekeeper.

Not one of those sent me an invoice. A single person, working evenings, can take open satellite data, open demographic rasters and open economic datasets, put them on an open map, and hold an oil industry’s waste up to daylight. That’s the part that still amazes me.

Where OSM comes in

Building the map made me confront how blank Iraq’s industrial layer is on OSM. Some of the largest oil fields on earth sit in the south, and large stretches of them are, on the map, empty desert. Gas-processing plants, flare stacks, oil gathering stations, storage depots — huge, permanent installations — simply aren’t there.

Iraq Flaring Watch turned out to be the perfect fix for that, because a persistent flare is a facility announcing its own coordinates every night. So the project became a mapping engine as much as a monitoring one:

1. A flare shows up as a persistent hotspot over a spot OSM thinks is bare.
2. I cross-check it against what’s already mapped. OpenInfraMap is my first lens — it renders OSM’s power and oil/gas layer beautifully, so I can see at a glance whether anything near the flare already exists. Overpass Turbo is the audit next to it, querying the area to see exactly what’s tagged and how.
3. I open the spot in satellite imagery, find the facility that’s obviously there, and trace it into OSM — or fix what’s already there and mistagged.

The flaring data and OSM correct each other: the fires point me at infrastructure to map, and the infrastructure I map turns an anonymous heat signature into a named, located, correctly-tagged thing anyone can use.

You can see the effect in OSM’s own history. The number of flares tagged man_made=flare in Iraq sat in the low tens for years; through the Iraq Flaring Watch work it has climbed to 438 today, and most of that recent jump is flares I traced after a satellite detection pointed me at them.

Count of man_made=flare within Iraq over OSM history. Source: ohsome (HeiGIT).

Open all the way through

I could have kept this private. But a flaring map built on a proprietary basemap and a closed dataset is a dead end — nobody can check it, nobody can extend it, and the day I stop maintaining it, it’s gone. So the project is open at every layer:

• The data in is open — OSM (the flare locations themselves, via Overpass), NASA FIRMS, Carbon Mapper, World Bank and WorldPop.
• The infrastructure I discover goes into OSM, the one layer I contribute back to and the one that outlives the project. A gas-processing plant or gathering station I add because of a flare detection is there for a transport mapper, a humanitarian team, an air-quality study, an OpenInfraMap user — whoever needs it next.
• The code out is open too. Iraq Flaring Watch is on GitHub under the MIT licence at github.com/rawazrauf/iraq-flaring-watch. The map itself is a serverless index.html — no backend; it reads OSM flares either from a preloaded Overpass snapshot or live from Overpass — but behind it sits a small pipeline of open queries I wrote to turn raw data into the figures on the map. A Google Colab script buffers every flare by 5 km, clips the WorldPop raster and sums the population to get who lives nearby; another script pages the Carbon Mapper API for Tanager methane and CO₂ plume detections over Iraq; a notebook matches NASA VIIRS fire detections to individual flares; and the World Bank GGFR volumes feed the national economics. Every query, and every JSON output it produces, is committed to the repo, so the whole chain from open data to published number is auditable and reproducible — not a black box.
• There’s nothing Iraq-specific about the machinery. Swap the bounding box and the national figures and the same stack becomes Flaring Watch for Nigeria, Libya, Algeria, Turkmenistan — anywhere gas is burning and nobody’s counting. If you want to stand one up for your country, please do; that’s what the licence is for.

How you can help

Iraq’s energy infrastructure is one of the most under-mapped layers anywhere, and there’s a clear, high-impact order to work in. If you map in Iraq — or want to — here’s where to start:

1. Add man_made=flare for flares that aren’t mapped yet. Iraq Flaring Watch shows you exactly where they’re burning; cross-check against satellite imagery and OpenInfraMap, then tag the flare stacks that are still missing. This is the single most useful thing, and the chart above is literally the scoreboard.
2. Add industrial=wellsite polygons around existing man_made=petroleum_well points. Iraq has over 3,000 oil wells mapped as points, but only around 1,000 have their wellsite drawn as a polygon (you can see the gap on OpenInfraMap). Tracing the wellsite footprint around a well point turns a dot into a real, measurable facility.
3. Add the rest of the missing oil, electricity and water infrastructure. Open OpenInfraMap over Iraq and fill in what’s absent — refineries, gas-processing plants and pipelines on the oil-and-gas side; power plants, substations and transmission lines on the electrical side; treatment and pumping stations on the water side. For the oil and gas facilities, the flare data is a free, precise guide to where to look.

Take a look

The site is live at iraqflaringwatch.com, and the source is on GitHub under the MIT licence at github.com/rawazrauf/iraq-flaring-watch — fork it, adapt it, and point it at your own country.

The fires are easy to see from space. Getting them onto the map is the part that needs mappers.

🔥 iraqflaringwatch.com

De aanleiding

Op mijn mapping tochten kom ik ook plekken tegen die ik wel van een foto zou willen voorzien. Maar hoe doe je dat nu, dit is het resultaat van mijn zoektocht over hoe dit te doen met Wikimedia Commons en wikidata.

de lokatie

De lokatie is een oude brug vlakbij Mirthos op kreta (Gps volgt) https://geohack.toolforge.org/geohack.php?pagename=File:Stone_bridge_near_Mirthos_01.jpg&params=035.019564_N_0025.585883_E_globe:Earth_type:camera__&language=en

De handleiding

• Om dit te kunnen doen heb je een account nodig bij een wiki onderdeel. (Bv wikimedia of wikidata)
• en natuurlijk foto(s) van het poi

Stap 1: Foto uploaden naar commons wikimedia

1. Ga naar https://commons.wikimedia.org/wiki/Main_Page en log in
2. Klik op de knop “Upload”
3. Lees de voorwaarden goed door en zet het vinkje bij “skip this step in the future” klik nu op “Next”
4. Selecteer de foto die je wilt uploaden, en kies toevoegen. (Je hoeft de foto(s) niet een makkelijke naam te geven, dit wordt automatisch gedaan in stap 7)
5. Als de foto(s) zijn ingeladen kun je verder door op “Continue” te klikken.
6. Beantwoord de vragen over de rechten van de foto(s) en klik op “Next”
7. Vul per foto gedetailleerde informatie in over de foto(s)
8. Als je meerdere foto(s) van de poi hebt kun je het beste een nieuwe categorie aanmaken die duidelijk weergeeft waar de poi zich bevindt en wat het is. ( bijvoorbeeld: Stone arch bridge near Mirthos)
9. Voor de lokatie moet je kijken in je foto app (Ik gebruik hiervoor google foto) om in de info de gps coordinaten te vinden.
10. Bij meerdere fotos kun je de gegevens van de eerste foto kopiëren naar de andere fotos.
11. Klik op “publish files” om het af te ronden.
12. Je krijgt nu de links naar de foto(s), bij 1 foto is deze link handig, bij meerdere fotos gebruik je beter de aangemaakte categorie.

Writing the script or speech then heading out station. I need hotel for two night. At the one you bring your guests. New York, Manhattan’s wherever my senses go. I boarding pass please? I will be at Atlanta Airport tomorrow before noon

KonGeoS - Konferenz der Geodäsie-Studierenden

Die KonGeoS ist die Konferenz der Geodäsie-Studierenden der Hochschulen im DACH-Raum und findet zweimal jährlich statt. Ziel ist es die Studierenden der 24 Geodäsie-Fachschaften aus Deutschland, Österreich und der Schweiz in einem fachlichen und auch persönlichen Austausch miteinander zu vernetzen. Die mehrtägige Veranstaltung ermöglicht aktuelle Themen aus Studium und Beruf zu diskutieren, Fachvorträge zu hören, Erfahrungen zwischen Hochschulen auszutauschen, in Arbeitsgruppen an Themen zu arbeiten sowie das Exkursionsangebot zu Unternehmen, Behörden und Forschungseinrichtungen zu nutzen, um Kontakte zu potenziellen Arbeitgebern und Berufsverbänden zu knüpfen. Das Programm ist auf der Webseite zusammengefaßt. Die KonGeoS tourt, ähnlich wie die FOSSGIS-Konferenz, durch den DACH-Raum. Vom 15. bis 17. Oktober 2026 fand die KonGeoS an der Hochschule Mainz statt.

Beim Ausstellerforum am Freitagnachmittag informierten FOSSGIS-Mitglieder über Open-Source-GIS und OpenStreetMap und den FOSSGIS-Verein. Zahlreiche Studierende kennen schon QGIS oder OpenStreetMap, hatten jedoch noch keine Berührungspunkte mit FOSSGIS e.V., das Interesse an der FOSSGIS-Konferenz war hoch sowie auch die Sticker auf großes Interesse stießen.

Danke an Anja Eisert (Konferenzorgateam, Team Vernetzungstreffen), Robin Durner (OpenTransportCommunity, OSM), Kai-Christian Bruhn (Hochschule Mainz) und Thomas Bentler (BKG) für den Einsatz am FOSSGIS-Infostand.

FOSSGIS e.V. Infostand auf der KonGeoS an der Hochschule Mainz

FOSSGIS-OSM-Communitytreffen Nr. 26

OpenStreetMap und FOSSGIS sind das Zugangstor zu nachhaltiger Geoinformation. Um noch mehr Menschen davon zu begeistern, trafen sich
vom 02.-04. Oktober 2026 wieder 25 Aktive aus der deutschsprachigen OpenStreetMap- und FOSSGIS-Community zum FOSSGIS-OSM-Communitytreffen im Linuxhotel in Essen. Diesmal erwies sich die Mobilität der Deutschen Bahn als besonders nachhaltig, indem sie die Ankunft einiger Teilnehmenden nach erlebnisreichen Rundreisen besonders weit in die Zukunft verlegte. So erreichten die letzten Teilnehmerinnen das Treffen gegen Ende der Geisterstunde. Nichtsdestotrotz (oder gerade deshalb) wurde auch dieses Treffen wieder ein voller Erfolg!

Das Besondere an diesen Treffen, welches eine Mischung aus Hackathon, Vereinsarbeit, Netzwerktreffen und Ideenwerkstatt ist, war der erfreulich hohe Anteil von Teilnehmerinnen. Einige waren zum ersten Mal dabei, wie Nora, die ihre persönlichen Eindrücke im Wiki beschrieben hat. Fränze Kellig hat mit ihrem Besuch beim Arbeitstreffen ihren Dienst angetreten und das Wochenende genutzt, um sich zu informieren und die Einarbeitung zu starten. Wir freuen uns, dass wir Euch, wie die anderen neuen Teilnehmerinnen, für den FOSSGIS und OpenStreetMap begeistern konnten!

Vereinsarbeit

Die AG Öffentlichkeitsarbeit dess FOSSGIS e.V. traf sich zu einer Session, in der verschiedene anstehende Aufgaben beleuchtet und besprochen wurden.
So ging es um die Ausgestaltung und Umsetzung des CartoHack - ein Format, welches zusammen mit der DGfK weitergeführt wird, indem regelmäßig in einer Onlinesession etwas Kartographisches demonstriert wird.
Die Smart Country Convention stand unmittelbar bevor. Torsten Friebe hatte mit seinem Unternehmen lat/lon einen Stand im OpenSource Park der OSBA gebucht und wollte bei dieser Gelegenheit den FOSSGIS e.V. bewerben und um eine Präsentation gebeten. Die zu präsentierenden Inhalte wurden besprochen. Die Unterstützung für OSM-Stammtische/ in Form von Werbung über Mastodon und Vorlagen für eigne Werbung wurden besprochen sowie dass eine Anleitung zur Organisation solcher Treffen aufgeschrieben werden möchte. Weitere Themen waren die Optimierung der Social Media Interaktion des FOSSGIS e.V und seiner Community sowie die Diskussion um die Idee des OSM-Maskottchens.

Unterstützend für die Einarbeitung von Fränze war die Session “FOSSGIS e.V. visualisieren” sowie eine Diskussionsrunde um die Werte, die wir mit dem FOSSGIS e.V verbinden, welche von Katja angestoßen wurde.

Die AG Öffentliche Ausschreibung mit FOSS besprach Ideen zum Thema des Panelgesprächs auf der nächsten FOSSGIS-Konferenz und startete eine Runde zur Zusammenarbeit von FOSSGIS mit BKG und ZenDIS. Ziel soll sein, die Open Source Geocommunity besser zu vernetzen und zu informieren. Insbesondere soll das Repository OpenCode.de für Geotools eine vom FOSSGIS und BKG unterstütze Kuratierung sowie zusätzliche Keywords erhalten. Die soll öffentliche Verwaltungen bei Beschaffungsprozessen zu unterstützen. Eine Strategie des gemeinsamen Vorgehens wurde besprochen.

Passend hierzu diskutierte eine andere Gruppe zur Frage “Wie unterstützen wir Projekte beim Wegzug von GitHub & Co” darüber welche Repositories die Souveränität für FOSSGIS-Projekte gewährleisten und wo und wie der FOSSGIS e.V. unterstützen sollte.

Community-Themen

• Das BKG hat für Produkte der VG25 den Ergänzungstext Addendum der “CC-BY 4.0 - Namensnennung” ergänzt.
• Der Erfahrungsaustausch zu aktuellen Entwicklungen und zur Panoramaxinstanz wurde fortgesetzt. Marc schildete seine Vorgehensweise und gab nützliche Hinweise.
• Hartmut macht sich Gedanken um den Nachbau der OpenSeaMap im Mapnik, um den OpenSeaMap-Stil auch für den Kartendruck mit print.get-map.org anbieten zu können.
• Die Idee, OpenStreetMap als beste Karte für den Nico Rüpke-Kartographie-Preis, der im Rahmen der DGfK verliehen wird, vorzuschlagen, wurde diskutiert.
• Florian bereitet eine Präsentation für Menschen vor, die nicht mit Open Source vertraut sind und sammelt Input.
• Paul hat seinen Job als GIS-Koordinator ein einer Stadtverwaltung begonnen und die Gelegenheit genutzt sich von den Anwesenden hilfreiche Tipps und ein Update zu aktuellen Themen zu holen.
• Peter präsentierte im Thema " Vom Schlagloch zur offenen Karte" seine Ideen und Fragen und besprciht weiteres Vorgehen mit der Gruppe.

Auch wenn das Wochenende gefühlt kurz war, wurden viele Themen besprochen und vorangetrieben. Die Anwesenden wissen die offenen und konstruktiven Gespräche sehr zu schätzen. Gearbeitet wurde im großen und kleinen Seminarraum, Kaminzimmer oder einfach im Garten auf der Wiese. Dazu kamen die traditionelle Pizza am Freitagabend, gemeinsames Kochen und Essen mit spontanen Gesprächen über allerlei Themen. Samstag gab es noch einen Kinoabend mit einem unterhaltsamen Vortragsvideo von den Datenspuren über die Untersuchung von Drohnen in der Ukraine.

Wir danken den Teilnehmerinnen und Teilnehmern für die tollen Beiträge und die tatkräftige Unterstützung bei der Organisation. Ganz besonders danken wir dem Linuxhotel für die Gastfreundschaft!

Wikiseite mit ausführlicher Dokumentation der Ergebnisse des Treffens:
https://www.fossgis.de/wiki/FOSSGIS_OSM_Communitytreffen_2026_Nummer_26

The problem

I’ve recently found myself with a lot of free time without internet access, and what better to do than improve OpenStreetMap!

JOSM has the capability of “editing offline”, that being that it can download and upload OpenStreetMap data whenever you’d like so if this was simple POI editing then I’d be fine: download the OSM data beforehand in JOSM, make my edits on a blank background and then upload when I have an internet connection again.

But this leaves out aerial imagery, by default JOSM streams this from tile servers, you can look at these URLs in Edit -> Preferences -> Imagery.

Others’ work

The method I have found to get offline aerial imagery is based off of an old forum post which recommends using KDE Marble to download tile data, and then point JOSM at that downloaded data using a file:// link.

This method works! And is the inspiration to mine but there is one fatal flaw in KDE marble that makes it unsuitable for this - it maxes out at zoom 16, inadequate for most mapping activities. I looked in to changing this arbitrary limitation in their source code, but I instead found a much simpler solution…

The breakthrough

Someone has (quite possible vibe-coded) a tool called MapTilesDownloader that fits the bill quite nicely. It can download to arbitrary zoom levels and, as it’s a Python script, it can be easily modified to download from imagery sources other than the ones it comes with.

It’s usage is simple: git clone the repository (git clone https://github.com/AliFlux/MapTilesDownloader.git) then install it’s dependencies: Pillow and Pyvips using pip and run it with python src/server.py and open the displayed URL in your browser. If you want to download Bing or Esri imagery then this is all you need to do, but I needed more obscure imagery.

To add custom imagery to this tool you can modify the sources dict in src/UI/main.js with an imagery URL obtained elsewhere, I got mine from the aforementioned JOSM preferences. The format used for pre-existing ESRI imagery is what most tile servers will use but you can use any of the imagery sources there as an example.

Using this imagery in JOSM

To use the imagery obtained using MapTilesDownloader in JOSM, you simply go to the JOSM imagery settings (Edit -> Preferences -> Imagery) and add a TMS source (plus button on the right) filling in the max zoom that you downloaded and then the URL is the path to the images prefixed with file://. This path is output in the console while the maps are being downloaded, for example on Linux it might be file:///home/<yourUserName>/Downloads/MapTilesDownloader/src/output/1792334342142/{zoom}/{x}/{y}.png with the last three arguments being automatically replaced by JOSM. Save and then your new imagery will be available under Imagery -> <the name you entered>

I hope this information will be of use to someone! Please don’t download too big of a bbox using the imagery downloader tool… And happy mapping!

In Hünstetten wurde der neue Radweg “TaunusRunde Hünstetter Herzen” beschildert. Die Route verbindet die östlichen Hünstetter Ortschaften.

• Der GPX Track der Runde kann bei Waymarked Trails mit der Referenz HsH geladen werden.

• Die Beschilderung erfolgt durch ein rotes Schild mit zwei Herzen.