É oficial! É com muita alegria e entusiasmo que confirmo minha participação no FOSS4G 2026 em Hiroshima! 🇯🇵

Para quem não está familiarizado, o FOSS4G é o maior evento do mundo dedicado ao software livre geoespacial. Organizado pela OSGeo, é o lugar onde desenvolvedores, usuários e entusiastas se reúnem para moldar o futuro das geotecnologias.

Antes de falar das apresentações, quero expressar meu profundo agradecimento à comissão organizadora. Sabemos que realizar um evento desta magnitude exige uma dedicação quase sobre-humana. O o trabalho de vocês é fundamental para fortalecer o ecossistema global de software livre geoespacial. Obrigado por tornarem isso possível!

At OPENGIS.ch, we believe that the long-term health of the QGIS ecosystem depends on more than just adding new features. Critical work like bugfixing, code reviews, codebase maintenance, and quality assurance often goes unnoticed, yet it is essential to delivering the stable, reliable software that thousands of organisations depend on every day. That is why we launched the QGIS Sustainability Initiative (#sustainQGIS). For every support contract of more than 10 days, we donate development time to the initiative. In addition, all unused hours at the end of the year of each contract are also donated. This ensures that buying an OPENGIS.ch support contract directly helps enable the long-term, sustainable development of the QGIS and QField ecosystem.

At OPENGIS.ch, we believe that the long-term health of the QGIS ecosystem depends on more than just adding new features. Critical work like bugfixing, code reviews, codebase maintenance, and quality assurance often goes unnoticed, yet it is essential to delivering the stable, reliable software that thousands of organisations depend on every day. That is why we launched the QGIS Sustainability Initiative (#sustainQGIS). For every support contract of more than 10 days, we donate development time to the initiative. In addition, all unused hours at the end of the year of each contract are also donated. This ensures that buying an OPENGIS.ch support contract directly helps enable the long-term, sustainable development of the QGIS and QField ecosystem.

Warning It was discovered after the PROJ 9.8.0 release that several EPSG updates introduced after EPSG v12.033 – notably the introduction of national realizations of ETRS89 (ETRS89-XXX […] where XXX is the 3-letter ISO country code) – caused backward...

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It’s my pleasure to announce the release of PROJ 9.8.1!

The release includes a few updates, bug fixes and a major regression fix for ETRS89-related coordinates operations.
See the release notes below.

Download the archives here:

At OPENGIS.ch, we create open-source software.
We are contributors, maintainers, and in the case of QField, the team that builds it.

That comes with a responsibility we take seriously: giving back.

“Give back” is not a slogan. It is our first core value, and the very reason the sustainability initiative exists.

Open-source is a garden. If you eat from it, water it, and keep seeding.

QGIS.org is pleased to announce that we will be using some of the funding that is donated to us by our users and sustaining members to fund a dedicated administrative role for the project. 

Principle duties:

David Bann and Liam Wright have put together a great guide to Generative AI Tools for Quantitative Research on the NCRM resources site. This is a great overview of what Generative AI is, how it works and all of the potential different models available, both commercial and open source, as well as how to run some models locally rather than relying on the cloud.

They are also very focused on the practical elements of how to actually use the tools in your work, discussing the different approaches as well as highlighting the importance of making sure you do not share sensitive data with cloud services.

They also have a great selection of videos for setting up both cloud based and local LLMs for working with Stata and R scripts in a number of tools including VS Code:

In week 12, I started to get things back on track after being sick. I ran five days, biked one day, and took Saturday off to take my family to a Nuggets game in Denver.

• 12 hours, 9 minutes all training

• 34.8 miles running

• 5,800 ft D+ running (and treadmill)

My energy level was low to mid until Friday, when I rallied for a good interval workout on a 12% incline treadmill indoors and a sauna session after. My fitness didn't advance much in week ten, but I didn't lose a step. According to the machine, I went "up" beyond any of the Quad Rock climbs, and at a pace that I'd love to hit on race day.

Listening to the news about the impact of the current war and the closure of the Strait of Hormuz, I was prompted to think about critical minerals that could also have massive disruptive impact in geopolitical turmoil.

I asked Claude “Can you build a dataset of the most critical minerals, where they are mined (mine sites or countries), shares of world production, price changes over 5-10 years, main usages so that we can build a map of these commodities. Build it in a way that we can extend if we find more data” and it found me some data using these sources:

Cloud masking is one of those steps you cannot really avoid when working with satellite data. Yet, it is often more cumbersome than it needs to be: different sensors come with different workflows, tools, and preprocessing requirements.

That is why I like OmniCloudMask. It is a Python library for cloud and cloud shadow detection in high to moderate resolution satellite imagery. Instead of relying on sensor-specific approaches, it uses a single model that generalizes across platforms.

According to the documentation, it supports resolutions from 10 m to 50 m and works with imagery from Sentinel-2, Landsat, PlanetScope, Maxar, and other sensors with Red, Green, and NIR bands. In practice, however, it also performs well on higher-resolution data, such as the 1.2 m Pléiades NEO imagery used in this example.

Having knocked up a simple fuel finder based on a csv download from the government site at the beginning of the week I thought “How difficult could it be to make something more functional and elegant and connect to the government fuel finder API?” Answer – the “more functional and elegant” not too difficult – about 3 hours of vibe coding, Connecting to the API and refreshing regularly – pretty damn hard even with Claude helping me.

For comparison here is the first version using a downloaded file

The map pins are simple, the pop-up has limited info and worst of all there are all those miscoded petrol stations in the North Sea.

This morning there was a lot of amused banter amongst my geo-pals about the UK Government’s Fuel Finder API based on an article in The Times (possible paywall) on the problems with the data. You can download the data or access the api from the gov.uk site.

I was thinking about what map to make next and I thought about flags, national symbols like birds or animals.

I started out with a very simple prompt to see what Claude would come up with:

I want to make an interactive map of national symbols: Flags, Trees, Flowers, Animal, Symbols,Anything else you can suggest?

It chundered away for a few minutes and came up with this monster

Yes it is truly awful! You can click on the map above to see it in action, it sort of works but the map part is rubbish (but probably represents Claude’s limited sense of world geography) and the linked data is pretty flaky as well. When I challenged Claude it explained that it was using “training data” I guess that means “any old crap that I could scrape.

El pasado webinar organizado por KAN Territory & IT reunió a la comunidad geoespacial de habla hispana para presentar las principales novedades de GeoNode 5 y explorar cómo evoluciona el ecosistema hacia arquitecturas modernas basadas en la nube.

En este artículo, resumimos los principales conceptos y avances compartidos durante el encuentro.

GeoNode es una plataforma open source diseñada para la gestión, publicación y análisis de datos geoespaciales, ampliamente utilizada para construir Infraestructuras de Datos Espaciales (IDE) y sistemas SIG.

Permite a organizaciones:

Non è facile cominciare a raccontare questa storia, quindi comincio da dove mi viene in mente. Avete presente un gasometro? Avete mai visto un gasometro dal vivo o in foto, in video, in televisione? Fino ad alcuni anni fa per me era una parola un po’ strana eppure è diventato uno dei luoghi con cui ho a che fare più spesso nella mia vita quotidiana. A Ventimiglia, dentro un’area archeologica romana abbastanza famosa e importante, ci sono due gasometri. Alcuni anni fa ho iniziato a occuparmi di questi due gasometri e di tutto quello che ci sta intorno che si chiama Officina del Gas è un impianto abbastanza grande, di 12.000 m² che dal 1906 al 1993 ha funzionato per dare il gas alla città.

Prima di iniziare a lavorare veramente alla realizzazione del progetto, con alcune persone molto preparate ho iniziato a studiare la storia di questo luogo e a farmi raccontare dalle persone che ci vivono accanto che cosa rappresenta per loro.

La Asociación gvSIG pasa a formar parte de la Red Iberoamericana de Observación Territorial (RIDOT), una iniciativa que reúne a instituciones y profesionales comprometidos con el análisis, la gestión y la comprensión del territorio en el ámbito iberoamericano.

Esta incorporación refuerza el compromiso de la Asociación gvSIG con la colaboración internacional y con el impulso de infraestructuras de datos espaciales, estándares abiertos y tecnologías basadas en software libre como pilares para la toma de decisiones y la gestión territorial.

Open data is only as useful as it is discoverable. Finding datasets, whether it’s satellite imagery, scientific research, or cultural archives involves navigating dozens of siloed portals, each of them with different interfaces and APIs. Project Matadisco tries to solve this by using ATProto to create an open, decentralized network for data discovery. Anyone can publish metadata about their datasets. You can then pick the records that matter to you and build views for the specific needs of your community. By focusing on metadata rather than the data itself, the system works with any dataset format, keeps records lightweight, and remains agnostic about storage.

Spoiler Alert: This is a pretty geeky post that may only appeal to Dead Heads!

I had an idea to go back to my Dead Reckoning project to look at the frequency that different songs were played by the Grateful Dead over the 31 years of gigging. I had already extracted the set lists for nearly all of the 2,313 shows the band played between 1965 and 1995 from JerryBase so I thought this would be relatively simple (it never is).

I asked Claude to parse the 31 years of gig files and make a table ranking the top 100 songs played over this period and showing the number of times played in each year and what percentage of gigs it was played as an indicator of the band’s favourites over time. This was nice and easy and after one small tweak I had a nice table.

QField’s first release of the year comes packed with new features as well as a bundle of improvements and polishing. Let’s jump right into it.

This new version of QField comes with a shiny 3D map view, giving users the ability to render their map content on top of a three-dimensional terrain.

Users can rotate the terrain geometry to get a better understanding of elevation profiles, while also adjusting the plane’s extent by panning and zooming with drag and pinch gestures. When the GNSS positioning service is enabled, the user’s current position, as well as ongoing tracking sessions, will be overlaid on top of the 3D terrain geometry.

I was looking for a simpler project to build after my last couple which had proved more complicated than I had anticipated. I came up with the idea of mapping airports and finding some data on their environmental impact – good idea, but not so easy.

Finding a dataset of airports was relatively easy, the OurAirports dataset has excellent coverage but sourcing open data about passenger numbers or emissions associated with specific airports was challenging to say the least. Eventually I settled for US, UK and EU airports where there was good passenger data from the US FAA, EU Eurostat and UK CAA. Maybe I will come back to this project in the future and try to build out to cover more regions.

Hace ya algunos años nació gvSIG Batoví, una iniciativa orientada a acercar los Sistemas de Información Geográfica (SIG) al ámbito educativo en Uruguay, especialmente en educación primaria y secundaria.

Su objetivo sigue siendo plenamente vigente: facilitar a docentes y alumnado la comprensión del territorio a través de herramientas geoespaciales abiertas.

gvSIG Batoví es una distribución de gvSIG Desktop adaptada al entorno educativo, pensada para que el uso de los SIG en el aula sea accesible, práctico y motivador.

QGIS 4.0 is now available! But yes, you have read my title correctly - I would recommend many people don’t upgrade…. yet.

QGIS 4.0 is an ‘Early Adopter’ version - which means that there are new things in there that may break. I would also say for many basic users (and some intermediate users) there isn’t much new that’s changed, so you are not missing out on much (see below for some new things coming up).

Many of the changes for 4.0 are under the hood, so that’s why you won’t see many differences. These changes are important - and will make the software more reliable and easier to maintain.

Rather than upgrading now, I would recommend waiting until 4.2 is released (about July 2026) and by this point QGIS will be more stable, and it will be fine to upgrade then.

It is with great pleasure that we would like to welcome COSS as our latest flagship sustaining member!

The COSS National QGIS collaboration launched in Finland to safeguard the sustainability of critical geospatial technology.

COSS aims to ensure the sustainability of the open source QGIS geospatial software that is essential to many public organizations’ operations, maintaining up-to-date security updates, and realizing productivity benefits from coordinated development. The collaboration is based on coordination among public authorities and on supporting the international QGIS community.

TorchGeo 0.8 includes 28 new pre-trained model weights and a number of improvements required for better time series support, including a complete rewrite of all GeoDataset and GeoSampler internals, encompassing 8 months of hard work by 23 contributors from around the world.

You may have noticed that https://github.com/microsoft/torchgeo is now https://github.com/torchgeo/torchgeo. This is not an accident!

Note

TorchGeo now belongs to YOU, please join our monthly Technical Steering Committee meetings!

Dados raster estão entre os datasets mais pesados do mundo GIS. Ortomosaicos, imagens de satélite e modelos digitais de elevação frequentemente possuem dezenas ou até centenas de gigabytes.

Historicamente, trabalhar com esses arquivos sempre foi um desafio para profissionais de geotecnologia. Entre os principais problemas estão:

• Leitura lenta de arquivos grandes
• Alto consumo de disco
• Necessidade de armazenamento local
• Dificuldade de uso em ambientes cloud
• Baixa escalabilidade em servidores GIS

Foi nesse cenário que surgiu o Cloud Optimized GeoTIFF (COG).

Hoje o COG é considerado um dos formatos mais importantes para infraestruturas modernas de dados geoespaciais, permitindo trabalhar com rasters gigantes de forma muito mais eficiente.

Neste artigo vamos entender:

Quando trabalhamos com ortomosaicos ou rasters muito grandes, um dos principais desafios é como armazenar e publicar esses dados com boa performance, sem sobrecarregar o servidor GIS.

Uma arquitetura moderna que vem sendo cada vez mais utilizada é baseada em:

• Cloud Optimized GeoTIFF (COG)
• MinIO ou Google Cloud Storage ou Amazon S3 (Object Storage)
• GeoServer

Essa combinação permite que o GeoServer leia diretamente rasters armazenados em object storage, sem precisar copiá-los para o servidor.

Neste post vou mostrar um passo a passo simples e prático para implementar essa arquitetura:

Hoy tengo el placer de impartir el webinar “Geomática hoy: del levantamiento al gemelo digital con datos abiertos, IA y estándares”, organizado por la Delegación Territorial de la Comunidad Valenciana y Región de Murcia del Ilustre Colegio Oficial de Ingeniería Geomática y Topográfica (COIGT).

La idea de la sesión es compartir una reflexión sobre el momento tan interesante que vive la geomática. Nunca antes habíamos tenido a nuestra disposición tantos datos, tanta capacidad de procesamiento y tantas herramientas para transformar la información geoespacial en conocimiento útil para la toma de decisiones.

In recent days, the Roadmap to Accelerate Digital Sovereignty in Spain has been presented, a document that reflects something that has been becoming increasingly clear for some time now: digital sovereignty has ceased to be an abstract concept and has become a strategic issue. We are no longer talking only about innovation, but about decision-making capacity, resilience, technological autonomy, and control over critical infrastructures. Technological dependence is a structural vulnerability.

En los últimos días se ha presentado la Hoja de Ruta para acelerar la soberanía digital en España, un documento que refleja algo que desde hace tiempo resulta cada vez más evidente: la soberanía digital ha dejado de ser un concepto abstracto para convertirse en una cuestión estratégica. Ya no hablamos solo de innovación, sino de capacidad de decisión, resiliencia, autonomía tecnológica y control sobre infraestructuras críticas. La dependencia tecnológica es una vulnerabilidad estructural.

La nueva versión gvSIG Desktop 2.7 incluye la herramienta de Swipe o Cortinilla. Con esta herramienta es posible comparar cartografía diferente de forma sencilla, como por ejemplo dos ortofotos de años diferentes.

El funcionamiento de esta herramienta es a partir de dos vistas diferentes, donde en cada una de ellas se deberá tener una de las capas a comparar. El usuario podrá elegir la opción de realizar cortinilla de forma vertical u horizontal, y se aplicará sobre las capas que se tenga visibles en ese momento en las dos vistas. Una vez seleccionadas ya solo deberá desplazar la barra central horizontalmente o verticalmente para poder ver las diferencias.

En este vídeo te mostramos el funcionamiento:

• Softwares
  • Examind Suite
  • Apache-SIS
• Lire la suite →

The call for papers is now open! We welcome proposals for talks and workshops from all levels of expertise, end users, technical developers, academics, and community contributors alike.

Deadline: 12 April 2026 at 23:59 (Europe/Zurich)

Submit your proposal: https://conference.qgis.org/presenting/

Submissions can cover any topic relevant to the QGIS community, for example:

My previous blog post reviewed the concept of the Hausdorff distance (which more descriptively could be called farthest distance.) Despite its usefulness in matching geometric data, there are surprisingly few open-source implementations, and seemingly no efficient ones for linear and polygonal data.  This even includes CGAL and GRASS, which are usually reliable for provising a wide spectrum of geospatial operations.

TorchGeo 0.7 adds 26 new pre-trained model weights, 33 new datasets, and more powerful trainers, encompassing 7 months of hard work by 20 contributors from around the world.

Note

The following model and dataset descriptions were generated by an imperfect human, not by an LLM. If there are any inaccuracies or anything else you would like to highlight, feel free to reach out to @adamjstewart.

The Hausdorff Distance is a useful spatial function which can appear slightly mysterious. Partly this is due to the name.  It honours Felix Hausdorff, one of the founding fathers of topology, and a polymath who was creative in music and literature as well as mathematics.    

“You can’t always get what you want
But if you try sometimes, well, you might find
You get what you need” (Rolling Stones, You Can’t Always Get What You Want, Album: Let it Bleed, 1969)

I had an idea for a map – where did all of the non native plants in Britain come from? I thought there might be something interesting there if I could find the data and map it.

I called up my new friend Claude and asked for some help with the data “is there a dataset that shows common flower and shrub species found in great britain and their country of origin (possibly with some historical narrative of how they arrived in the uk)?” That took me to the Royal Botanical Gardens Kew’s “BIFloraExplorer” with over 3000 species in Britain and the Botanical Society of Britain and Ireland’s “Plant Atlas 2020” – loads of time saved, I had some authoritative and relevant data in minutes.

Unusually mild weather helped make week five productive. I can feel the benefits as I write this, a week later.

• 11 hours, 37 minutes all training

• 19.3 miles running

• 1,890 ft D+ running

Tuesday I did hill sprints on the "Wallenberg Wall" in my neighborhood. My cadence has increased, and I was a second faster on average. 23 seconds instead of 24. Getting faster is one of my goals, and I'm making measurable progress.

This new version is compatible with QGIS 4 (based on Qt 6 framework). 

Until QGIS 4 is officially released, in order to try the new Semi-Automatic Classification Plugin you can install the prerelease (QGIS 3.99 master).

The NDFF (Nationale Databank Flora & Fauna) holds over 200 million verified observations of plant and animal species from the Netherlands. These data are contributed by volunteers and professionals from hundreds of organizations. Together they contain a wealth of information about the occurrence of plant and animal species in the Netherlands.  Since 2025, the database is accessible to everyone free of charge. That means that one can download all data for 5 × 5 km grid cells (certain restrictions apply). 

Observations are provided as polygons. This post provides an example of how to quickly create summary raster maps showing the total number of observed species. Non-native species are excluded to focus on native biodiversity patterns. Moreover, each record is treated as a single observations regardless of the reported number of individuals.