For over half a century, the geospatial industry has operated on a foundational, largely unchallenged premise: the physical world is an absolute reality, and the goal of technology is to measure, index, and represent it with ever-increasing fidelity. Data giants like HERE, TomTom and of course Google built empires by deploying fleets of sensor-laden vehicles …
As Chair of the Board of Directors of the Open Geospatial Consortium (OGC) it was a pleasure to once again attend a Technical Committee meeting this week in Philadelphia, and while no longer participating in the technical work of the organisation it was an opportunity to take a step back and evaluate the role of …
I had the I had the pleasure of taking part in a discussion over dinner on the topic of Trust when it comes to GeoAI (don’t get me started) at the Royal Society last week, sponsored by InnovateUK as part of their GeoAI Festival. While I think everyone agreed this was very much the …
It’s simply Geospatial! Happy New Year! Remember “WebGIS”? The term itself feels a little anachronistic now, doesn’t it? It conjures images of a distinct, almost revolutionary movement, a time when putting maps and spatial analysis on the internet was a novel and exciting frontier. I know I was there… Today, the very idea of differentiating …
Inspired by an excellent post on LinkedIn by Sam Meek on the problems of the Machine – Man interface with reference to AI, I asked the purely fictional Mayor Vaughn to write a guest post on this very topic.. A Guest Blog by Larry Vaughn, Former Mayor of Amity Island You know me. I’m the …
Read more “The machine-man interface : Notes from Amity Island !”
The sheer volume of Earth Observation (EO) data today—a planetary deluge of multi-spectral, radar, and LiDAR feeds is overwhelming traditional remote sensing techniques. For decades, analysts relied on meticulous, band-by-band spectral science, but this approach is simply unsustainable at scale of “new space”. Enter the hot term of the moment, geospatial embeddings, a core innovation …
The Model Context Protocol (MCP) addresses the fragmentation of AI training data by providing a standardized interface for data acquisition. This open-sourced solution simplifies data integration and enhances compliance by ensuring clear data access and tracking. While promising, MCP’s early-stage adoption raises security concerns and challenges related to interoperability.
Imagine a world where you never have to worry about buying the right train ticket again. Ok I know this does not sound like much of a problem, but then how well do you know the UK’s now mostly nationalised Railway system… No more fumbling for change, wrestling with a complex app, or trying to …
It’s the end of summer so I give you a light hearted experiment in the application of Generative AI. My quest to recreate the cinematic masterpiece The Battle of Britain, but with a twist, has hit a slight snag. The twist, you ask? Cats. Yes, I wanted to harness the power of GenAI to create …
Read more “The Cat-astrophic Battle of Britain: My GenAI Film Fiasco”
The geospatial industry has long been on a quest for a universally accepted system to identify real-world entities like buildings, roads, and businesses. Such a system promises seamless interoperability, but its pursuit has been fraught with challenges, often clashing with the commercial realities and vested interests of powerful data owners. Let’s explore this journey through …
Read more “The Quest for a Universal Geospatial ID: From the One Ring to the Holy Grail?”
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