The MapScaping Podcast - GIS, Geospatial, Remote Sensing, earth observation and digital geography

Republished Episode - I wanted to resurface this episode because positioning is everything, and it's a great overview of how it works.

 

Right now you are being bathed in radio signals from about 35 satellites, each one 20,000 km away, and every one of them is weaker than the noise floor of the receiver trying to hear it. That is GNSS, and it is the only technology on Earth that can tell you where you are in an absolute sense.

Sandy Kennedy runs applied research for autonomy and positioning at Hexagon. In this conversation she walks through how satellite positioning actually works, why centimetre accuracy is so hard to get, and what the next generation of positioning looks like. We cover low earth orbit constellations, visual positioning, Wi-Fi, 5G and ultra wideband, and the one thing every one of those systems still quietly borrows from GPS.

If you have ever wondered whether visual positioning is going to replace GNSS, or why nobody has just put GPS satellites in low earth orbit already, this one is for you.

Show notes

Sandy Kennedy is the Vice President of Innovation for Autonomy and Positioning at Hexagon. Her group does applied research: finding better ways to do what Hexagon's positioning products already do, and finding new things they could do in the future.

This episode is a tour of positioning from the top down. We start 20,000 km up with the GNSS constellations, look at what a low earth orbit constellation would change, then come back down to Earth for visual positioning, Wi-Fi, 5G, ultra wideband and the private networks used in mines and warehouses. The through line is that none of these technologies replaces the others. They each have environments where they are strong and environments where they fall over, and the real work ahead is making them hand off to each other seamlessly.

What "better positioning" actually means
Sandy's old grad supervisor used to ask "better in which parameter?" Better depends on the job. For positioning it usually comes down to availability (how often you can get a fix), whether that fix is accurate enough to be useful, and then accessibility: can the receiver be made small enough, cheap enough and cool enough to go where it is needed. Power is not just power, it is also heat.

How GNSS works
Every constellation (GPS, Galileo, BeiDou, GLONASS) is a state-owned, state-operated set of synchronised satellites in medium earth orbit. Your receiver measures the time a signal took to arrive, multiplies by the speed of light, and gets a distance. Four satellites give you four unknowns: X, Y, Z and your clock offset from system time. More satellites give you redundancy, and in this case redundancy is a good thing. In open sky today a receiver can see about 35 satellites at once, each broadcasting on around three frequencies.

Why centimetre accuracy is hard
- The signal is below the noise floor of your receiver. There nto. You have to fish it out.
- Broadcast orbits are only accurate to metres. That is remarkable for something 20,000 km away, but if you want centimetres you need precise orbits from
  a correction service.
- The troposphere delays the signal and changes with water vapour. The ionosphere is dispersive and tears code and carrier apart, and it follows the solar
  cycle. Multi-frequency receivers can observe and remove mostally.
- Multipath. In a prairie there is nothing to bounce off. Over water there is more. In a city you are surrounded by hard metal and stone, and the receiver
  has to work out which arrival was the direct line of sight.

Why not just put GNSS satellites in low earth orbit?
Daniel pitches it as a startup idea and Sandy takes it apart, fairly. LEO is cheaper to launch to, satellites need less radiation hardening, the signal
arrives stronger and cuts through foliage better (not buildingte slices through the atmosphere in a way that helps separateorbital, atmospheric and multipath errors quickly. LEO satellites can also position themselves using the existing GNSS constellations above them. The
catch: a LEO pass is about 10 minutes horizon to horizon versuorbits are more disturbed by gravity variations and solaractivity, and if you want to broadcast inside the protected L-band there is a very large amount of spectrum paperwork ahead of you. Going to a higher band
gives smaller antennas and jamming resilience but brings back te TV owners know well.

Would we design GNSS differently today?
Sandy is careful here. There were good reasons for MEO, for L-band and for the signal structure. The one thing newer constellations like Galileo are
adding is authentication. GPS is a one-way broadcast with an o means unlimited passive users who never reveal themselves tothe system, and also an easy target for spoofing and jamming. Two-way systems like 5G can authenticate, but at the cost of a user limit and the user
having to identify themselves to the network.

Visual positioning versus GNSS
Daniel raises the LinkedIn claims that visual positioning is "killing GPS". Sandy's answer: visual positioning is how humans navigate, and it is excellent
at the immediate surroundings, which is exactly the dense urba But it has to be tied to a database of known coordinates tomean anything in an absolute sense, it is useless in the middle of the ocean, and it still needs a master clock, which almost always comes from GNSS. Her
framing: GNSS gives you a coordinate, visual positioning givesordinate does not mean you are not lost.

Terrestrial positioning
Wi-Fi is good enough to get you to the right city block or building, but decentralised access points with unverified coordinates make it neither precise
nor secure. 5G can do angle of arrival, which turns positionin problem instead of a resection, but the solution is computedat the network operator, not on your device, and only for members of the network. Ultra wideband and GNSS-like ground transmitters work well in warehouses
and mines but they are proprietary, someone has to install andsation always lags the first proprietary wave.

The future
Not one breakthrough technology, but seamless combination. A logistics vehicle that moves from the truck into the warehouse and back out again is still
hard to position across that boundary. Centimetre positioning rticularly small last-mile and warehouse robots that sharespace with people. Sandy also points out an inversion: reality capture treats moving objects as noise, while navigation treats them as the most important
thing in the scene.

Why positioning gets overlooked
Position is the given quantity in every physics problem, so nobody thinks about it until it is missing. Computer vision is intuitive because it emulates
what Sandy calls our "meat circuits and eyeballs". GNSS and innd estimation, but they are computationally light, need notraining data, and offer a capability humans do not have. And the thing that most surprises Sandy compared with ten years ago is that space is now a
legitimate topic. It is not just Star Trek anymore.

Connect with Sandy on LinkedIn
https://www.linkedin.com/in/sandy-kennedy-569a6a4/

Related episodes
SBAS, a base station in the sky
https://mapscaping.com/podcast/satellite-based-augmentation-system-a-base-station-in-the-sky/

Navigating the past, present and future of GNSS
https://mapscaping.com/podcast/navigating-the-past-present-and

Where does Google's blue dot come from?
https://mapscaping.com/podcast/how-google-calculates-your-location/

Alternate short description, if you prefer a question-led hook

Is visual positioning going to kill GPS? Why hasn't anyone just put GNSS satellites in low earth orbit? And why does every "GPS alternative" still need
GPS for its clock?

Earlier this year I ran a small experiment called the Geospatial Launchpad — six weeks of working closely with a couple of people to help them push their geospatial projects forward. West was one of them.

His project is Sentinel Bird (sentinelbird.com): an archive of every Sentinel-2 visit over the Gaza Strip since 2015, with 10-meter resolution imagery for each district, interactive comparison sliders, change-over-time timelapses, and a downloadable press pack — all free, no accounts, no paywall, licensed for anyone to use for anything.

In this conversation, we get into what Sentinel Bird is, why West built it, and everything he ran into along the way — the marketing, the SEO, the feedback, all the stuff that has nothing to do with the tech but everything to do with whether a project actually goes anywhere.

We talk about:

How frustration with English-language media coverage after October 7th turned into a geospatial side project

The foundation models West is training on Sentinel-1 SAR and Sentinel-2 optical data for damage detection

Making the pipeline location-agnostic, and why tiling across orbital passes is harder than it looks

"The agenda is in the data" — building something opinionated without saying a word

Why URL structure is the thing you should think hardest about before you hit publish the first time

Watching a real human use your site, and how humbling that is

Using AI to audit your own site — what was useful, and what advice to ignore

The ethics of monetizing a project you'll never put behind a paywall

What worked and what didn't in the Geospatial Launchpad, and what I'd change next time

West is currently open to work opportunities. If you check out Sentinel Bird and think there's something there, email him at hello @ sentinelbird.com

If you're working on your own project and a bit of structure and accountability sounds appealing, there's a link in the show notes — register your interest, and if enough people are keen, I'll run the Launchpad again.

Sign up for the next Geospatial Launch Pad

 

 

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Where does one field end and the next one begin? It sounds trivial right up until you try to answer it.

In this episode, I'm joined by Hannah Kerner — Assistant Professor at Arizona State University, AI Lead for NASA Harvest and NASA Acres, and Research Advisor for Taylor Geospatial — to talk about Fields of the World.

 

This episode is sponsored by the Cloud Native Geospatial Forum. The CNG Forum 2026 runs October 6–9 at Snowbird, Utah — three days of real-world cloud-native geospatial (STAC, COGs, GeoParquet, Zarr, and more) with the teams actually building this stuff at scale, plus a hands-on workshop day to kick things off. Register at https://2026.cloudnativegeo.org

In this episode I'm joined by Apurva Shah, co-founder and CEO of Duality AI, a company building virtual worlds — or "world models" for robots and physical AI systems.

Apurva's path here is an unusual one. He spent most of his career in animation, first at Pacific Data Images (which later became DreamWorks) and then over a decade at Pixar. His co-founder, Mike Taylor, comes from the other end of the spectrum entirely: a controls engineer who led field robotics at Caterpillar, deploying house-sized haul trucks at Australian mines. As Apurva puts it, if he's the pixels, Mike is the atoms.

We talk about why real-world data, as valuable as it is, is never enough on its own — and how synthetic data can be used to deliberately fill the gaps and biases that creep into any collected dataset.

Some of the things we get into:

The difference between digital twins and 3D assets and why Duality treats twins as modular building blocks you compose into scenarios, rather than as one monolithic environment

How they build environments from the ground up using DEM data, satellite imagery, photogrammetry and biome catalogues and why building them this way means everything is annotated from the start

Calibrating virtual sensors against real ones, including synthetic aperture radar, and why sensor noise characteristics matter as much as physics

Predicting how a material will behave across the spectrum (infrared, SAR) just from its visual response — and when that prediction breaks down

Why "clutter" only becomes clutter once you know what you're looking for, and why it doesn't need to be perfect

Modelling star fields for localisation in space, where there are no roads or buildings to navigate by

Explicit versus generative world models, and why you need both

A project with AWS simulating emergency ambulance routing through a city, complete with autonomous vehicles, traffic control and teleoperated human agents

Where Duality is not the right tool molecular scale, virtual patients, drug discovery

And yes, a story about robotics companies renting Airbnbs, trashing them, and leaving

Towards the end we get into the bigger questions: whether AI takes our jobs or makes us better at them, where the line sits between "good enough" and slop, and why Apurva — a self-described humanist — thinks virtual environments are the one place where human and machine intelligence can genuinely learn from each other.

Find out more at duality.ai, or dig into their technical writing at duality.ai/blogs

My guest today is Tyler Reid, co-founder and CTO of Xona, a company building the first commercial satellite navigation system.

We get into why Tyler and his team are moving satellites into low Earth orbit and what that unlocks. Stronger signals that can penetrate indoors, more resilient timing infrastructure, and better security against jamming and spoofing.

GPS sits 20,000 kilometres out. Xona sits at 1,100, with signals around 100 times stronger and a planned constellation of 258 satellites. Tyler came at this from the autonomous vehicle world at Ford, where the problem was simple enough: ten meters gets you to the store, but it doesn't keep a car in its lane.

We also talk about time, and how much of the world quietly depends on GPS to keep its clocks honest. Why countries are suddenly so interested in owning their own infrastructure. And the question Xona gets asked constantly: if you're broadcasting that close to GPS, aren't you the jamming problem?

If you're interested in what the future of GNSS might look like, you're really going to enjoy this one.

More at xonaspace.com, or reach out to Tyler on LinkedIn.