Train Custom Deep Learning Models Without Coding using QGIS, Roboflow and Ultralytics
#geoAI #gis researchers in my feed, I failed to see how this https://research.google/blog/mapping-the-modern-world-how-s2vec-learns-the-language-of-our-cities/ is "a significant step toward foundational intelligence for #Geography "
Rasterizing data (how did they handle support change?) and reducing dimensionality is nothing new (is innovation here that llm are good at "analyzing" some kind of "eigenvalues"?).
Also is "embedding" overused?
what I am missing?
The Call for Abstracts for the Open-Earth-Monitor Global Workshop 2026 is closing soon ‼️Don’t miss your chance to be part of the final event of the project.
Join us 7–9 October 2026 in Barcelona, Spain, to share your work on #EarthObservation, #GeoAI, and #openData across key themes:
🌿 Forests & Biodiversity
🌾 Soil, Water & Agriculture
🌡 Climate & Health
🔗 Submit your abstract: https://pretalx.earthmonitor.org/global-workshop-2026/cfp
🌐 Learn more: https://earthmonitor.org/global-workshop-2026/
New 📚 Release! GeoAI with Python: A Practical Guide to Open-Source Geospatial AI by Qiusheng Wu
Find it on Leanpub!
Link: https://leanpub.com/geoai
#books #newrelease #python #geoai #ai #satellite #technology #opensource
New 📚 Release! GeoAI with Python: A Practical Guide to Open-Source Geospatial AI by Qiusheng Wu
Satellites capture massive volumes of imagery every day, but turning pixels into insight requires AI. This book teaches you to build, train, and apply deep learning models to real satellite imagery using Python and open-source tools, with 23 chapters of executable code you can run today.
Find it on Leanpub!
GeoAI with Python: A Practical Guide to Open-Source Geospatial AI by Qiusheng Wu is the featured book on Leanpub!
Satellites capture massive volumes of imagery every day, but turning pixels into insight requires AI. This book teaches you to build, train, and apply deep learning models to real satellite imagery using Python and open-source tools, with 23 chapters of executable code you can run today.
What role does the human-in-the-loop play in AI-assisted mapping?
In a recent experiment with YouthMappers in Ghana, we explored how editors interact with AI-generated roads in #OpenStreetMap. Do human edits refine the data or simply pass it through?
Understanding these actions helps improve trust, validation, and quality. It also guides how the community works with growing AI-generated data. What is your take on AI-mapping?
🔗 https://heigit.org/ai-assisted-mapping-insights-from-the-community/
Review of the AI Segmentation by TerraLab plugin for QGIS
Review of the QGIS GeoAI plugin
Hans van der Kwast
hansakwast
Olivier Leroy
OpenGeoHub Foundation
Leanpub
HeiGIT