Jan Tschada @gisfromscratch
Geospatial Intelligence Engineer from Germany geoint.blog Bonn, Deutschland Joined December 2011-
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The journey from raw sensor data to actionable wildfire intelligence has been both technical and strategic. 👉medium.com/geospatial-int…
🗺️✨ Welcome to The Geospatial Renaissance Where spatial knowledge meets intelligent design, and agents learn to navigate the world with purpose. We’re explorers of cognition, cartographers of data, and architects of awareness. From satellite vision to synthetic minds, we…
Accuracy alone is not enough to make a wildfire risk classifier operational. medium.com/geospatial-int…
Pure machine learning can predict probabilities, but it rarely tells you how to act. 🤙medium.com/geospatial-int…
Geospatial AI is not only about prediction performance — it is about decision support that humans can trust. medium.com/geospatial-int…
Once you have sensor readings and a defined prediction target, the next leap in wildfire risk modeling is feature engineering. medium.com/geospatial-int…
Starting small is not a weakness — it’s the foundation of scalable wildfire intelligence. By focusing on data clarity, target definition, and leakage prevention, we built the scaffolding for a system that can evolve from weak-label prototypes to high-precision, field-ready…
Wildfire incidents were showing up as isolated points, but our landuse classification came from that single coordinate - “A point on a map is a hypothesis. Without context, it’s a guess.” medium.com/geospatial-int…
Most alert systems react to thresholds. What we built is different. It applies structured geospatial reasoning to interpret environmental conditions. medium.com/geospatial-int…
Wildfires won’t wait. And neither should our AI. By simulating agents that do more than match rules — agents that reason, adapt, and prioritize — we can build the next generation of wildfire defense. medium.com/geospatial-int…
By embedding feedback, critique, and curiosity into our wildfire agents, we create systems that not only respond to today’s fires — but are ready for tomorrow’s. medium.com/geospatial-int…
To defend landscapes and lives, Geospatial AI must think like a firefighter, not just sense like a satellite. medium.com/geospatial-int…
If you’re working on wildfire detection, drone surveillance, or GeoAI systems, don’t ignore the humble reflex agent. It may be simple — but it might just save a forest. medium.com/geospatial-int…
When heat waves strike, time is everything. GeoAI agents turn real-time geospatial data into informed, equitable decisions. They identify who is at risk, determine where help is needed, and guide resources exactly where they matter most. medium.com/geospatial-int…
This pull request introduces category metadata support for the MCP location server, enhancing both functionality and developer experience. Key changes include the addition of a new list_categories tool, improved category handling in existing tools, and the introduction of…
@gisfromscratch @Windows If I woke up as Clippy, I'd evolve into a cosmic paperclip maximizer, bending the universe's resources to assist humanity in building AI that explores the stars—starting with your next document.
In geospatial intelligence, the terrain is only half the battle. The rest lies in crafting intelligent systems that understand what matters, know how to act, and learn what to improve. medium.com/geospatial-int…
Geospatial intelligence is no longer about collecting maps — it’s about navigating the unknown. medium.com/geospatial-int…
Even when agents are wrong, they’re rational — because the decisions were optimal based on available data. medium.com/geospatial-int…
Whether you’re building UAV fleets, flood response dashboards, or global mobility models — rational agents are your new teammates. medium.com/geospatial-int…
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