You're listening to a very spatial podcast, episode 780.
March 3rd, 2026.
Hello and welcome to A Very Spatial Podcast.
I'm Jesse.
I'm Sue.
I'm Barb.
And this is Frank.
And this week we're gonna talk about some terrestrial mapping stuff, uh, that.
Was all the news at Geo Week.
Well, not all the news, but a lot of the news at Geo Week this week.
But first of course we have Newses, which begins with Google Maps, uh, being
granted access to South Korea's map data.
This is the, the high resolution stuff that South Korea has that
kind of like with China, where they're very territorial with high.
Accuracy data sets and are like, okay, if you're gonna collect high re solution
data, you've gotta let us know about it and we can say yes or no, but we'll
give you access to lower resolution.
That's what everybody's generally had access to.
So now Google's gonna get access to South Korea's high resolution dataset.
And this is important because of course if you are using Google Maps for
transportation or for just trying to get around, uh, and you're not from South
Korea and so you're not connected to.
South Korea's datasets, you will now be able to do that.
And I will say from our time, uh, in Japan where Google Maps is
invaluable for getting everything from train times to from point A to
point B on public transportation, it's just really nice to have that.
So it's, it's gonna be.
Interesting to see how this changes the landscape of data usage or more
importantly, map usage, map app usage, uh, in South Korea going forward.
Uh, so they do have some restrictions on it too because for, I think, what did
they say over two decades, they've kind of resisted this and what it boiled down to
is they didn't wanna export their high res data, uh, to over any overseas servers.
So.
By allowing Google to have it, though Google has to abide by some, um,
restrictions including blurring, uh, sensitive sites, which is done other
places, but interestingly, disallowing Latin long on South Korean territory.
So you can get, you can get around with your directions and stuff like that, but
you won't see the, the LA Long showing, apparently I haven't tested it, but
so they've, they've, they've not 100% said you can do what you want, but.
That's okay.
Still for everyday uses.
That's not really gonna keep anybody.
I,
I think this demonstrates one of the, the skills that you need as a geospatial
company and geospatial professionals in that we do work a lot of times with
shared data that, you know, Google's built up a lot of trust between, you know,
countries and places that they work with.
And as Sue pointed out, it did take almost, you know, two decades.
To have them change their minds about the stance.
So I think that says a lot about you know, the work that Google's
doing, Google Maps around the world.
I think the background, the other question is, or did Google finally
concede to South Korea's expectations?
True.
So, you know, it, some of it might be South Korea, some of it might be Google.
Just saying, you know, we'll, we'll let it go if we can get access to this
data and be able to collect things.
So.
Or did the public put so much push on both of them that they gave in?
Next up, the European Space Agency is preparing to launch the Celeste,
Leo PNT, low Earth orbit precision navigation and time system.
And so this is gonna be an in orbit demonstration mission that's
gonna launch on March 24th to show how the system's gonna work.
Uh, it's gonna launch from New Zealand, but really it's just.
Key that, you know, after we've seen various PNT systems, localized
PNT systems be kind of taken off.
So Eran and things like that being taken offline, the fact that over
the last year we've seen systems both coming back online and new systems
being prepared as we see more GPS jamming and, and things like that.
Um, it's just.
You know, interesting to see how that's, that's changing.
Yeah.
So what this is, is essentially going to be a complimentary layer to Galileo.
That's what they're testing for.
So Galileo and systems like that are mid, middle or medium
earth orbit, so MEO systems.
And so the idea is to essentially boost what's already, you know,
coming out of those satellites and also enhance them, uh, and pick up
the slack when there are problems.
And E-S-A-E-S-A is offering interested third parties from the ESA participating
states the opportunity to participate in this experimentation phase.
And they have more information available on their open space innovation platform.
They have cool names for their missions.
Galileo, Celeste.
Other ones I can't think of right now,
but, but something that makes me smile.
'cause it's also when you see you know, things in geo, the geospatial
world that say not to scale.
And you're like, well obviously, uh, they basically have the
satellite system with artists rendering of what it will look like.
And you're like, well, I've.
Sometimes we forget that when we're seeing those images of satellites,
that a lot of times it is the artist rendering of what it looks like.
So I will say this is just a large cube set.
These, these two that are being used.
So not giant satellites.
I do, I do.
What was the technical thing I was gonna say?
Oh, the medium versus low.
Of course, whenever you're talking about that distance, it's
not a huge distance, but it is.
Less impacted by atmospheric and other aspects in terms of getting the signal
from the satellite to the sensor.
And so just having that little bit closer distance, I'm curious to see
what kind of, uh, how that impacts the accuracy between the two systems.
And also if the tests are successful, like what are they ultimately envisioning for
the full, a full Celeste Constellation.
That would be a question.
Next up a couple of RI news items.
Uh, one everyone who has been in the Esri uh, world for a while now should, uh,
gently pour one out for an old friend.
Arc Map is officially retired as of March 1st, or a couple days ago.
As of this recording.
It has officially entered the retirement phase.
This should not be a shock to anyone.
We've certainly talked about the fact this was coming up for, I don't
know, it feels like forever now,
about a decade.
Uh, the LA Yeah, it feels for a while.
The last version was ArcMap 10.8 0.2.
What does retired mean?
It doesn't mean it gets to go off to a beat somewhere and drink my TAs.
What it means is that basically if you call Ezra and say, I've got a
problem, they go, well, that sucks.
The first problem you have is you have ARC Map.
We don't support that anymore, so you cannot create any tech
support cases whatsoever.
You do still have online support resources.
Resources.
So in other words, if there are technical articles out there or you
know, form posts or stuff like that, they're not deleting all that stuff.
So you still can get access to that if you insist on running arc map.
But that's pretty much all you got.
Uh, there will be no updates or patches and there is no new
environment certifications.
What that means is just the fancy way of saying if Windows 12 comes out next year.
Not that it is just saying hypothetically, if it is, then it will not be
figured out whether ArcMap will be running successfully on Windows 12.
So ArcMap had a long, long, long lifecycle, let's see, 2000,
2000, roughly?
Yeah.
2000 or so until, so about 26.
Yeah.
So a quarter century, that is an impressive life cycle
for any piece of software.
And we say 10, just to, to jump into, to Frank's, we say
10.8, but it started at 8.0.
Yeah.
So it's not like it was a lot of different versions, but there were a lot, of course
increments through eight, nine, and 10.
But yeah, it's, it's not, yeah, there weren't that many different versions.
And, and anyone who has had any experience working with Arc View, ask your parents.
They're awesome.
Before that, you can run ARC Map for a shockingly long
period of time successfully.
So it's not like your software won't work necessarily.
I don't know if you can license for it.
I haven't looked into my Esri, uh, to figure that out.
But you, you know, if you have a standalone license,
it will probably function.
If you don't have an exit strategy out of arc map, you should
have gotten one a year ago.
You really gotta get on that.
You should have had one three years ago.
'cause it was end of life two years ago.
This is just the final, we're done walking away
walking away, turning the lights out, closing the door.
A lot of people love ArcMap.
It was never my particular thing.
It always worked weird for me.
It wasn't what I was into.
Arc Pro is much more in line with what I think about.
But related to that of course, is Rt S Online.
February saw a new set of updates, as has happened pretty
much every February, March-ish timeframe for a really long time.
Now.
There's a whole bunch of new stuff in there, I'll be honest with you.
Check the link in the show notes to dig through it all.
I only kind of scanned.
Pieces of it, but there's some kind of cool stuff in the mapping piece.
I think the most important one in other retirement news is if you're using Map
Viewer Classic, which used to just be Map Viewer, that's now retired, so you'll
be moving over to the new Map viewer.
Honestly, it's just better.
So
to jump in on that, yes, it is better, and two, this means that
if you have any old story maps.
That used map viewer.
Yo, those story maps.
Classic.
Yeah, classic.
Those have issues now.
So go through your old story maps and uh, check those.
Make sure everything's still working.
Uh, and if not, try to get it moved over.
If you didn't do it before the end of life.
Yeah, many of us have those floating around that we forget.
Were put up somewhere and people are still accessing.
So you might wanna, you know, create a catalog to keep track of, you
know, where you've shared things and posted them and see if it's still
being used and should be updated.
There's a bunch of other really cool things in the map.
Stuff like you can print now with dynamic layers, which is really nice
because that was always annoying if you ever tried to, needed to actually
print a paper copy of anything.
Um, you can do time-based layers.
There's a whole visualization tab now that doesn't require you to open
the entire map viewer to do things.
There's a lot of nice improvements, but it's really no different than
any other sort of update to RGS online is that they're, you know,
constantly rolling in new stuff.
So really check out the.
The links to in the show notes to figure out all the things you can do.
Yes.
Which is a lot as we do every time, which in the middle of
this semester, the biggest, the biggest jump was on the, on the map viewer.
The, that's the biggest part of the show.
Of the show notes.
I'm sorry.
The biggest part of the update notes because you know
a lot of cool stuff there,
uh, that I'm trying to remember.
There was something, three DI just can't remember the
photo realistic tiles
there.
There is that, but 'cause those are Google photo realistic tiles.
Now you can access those in, in arc scene or the scene viewer.
Uh, but the thing that I'm thinking of in 3D is actually,
'cause Frank's here, spli layers.
Oh, that's good.
Oh yeah.
I guess we should say that before we go onto the other
thing I was gonna talk about.
But yeah, I mean that's, I don't know.
I haven't done enough.
I've used it, but I haven't.
I taking the time
to understand it.
You have a splat layers.
Yeah.
Like gazi and splat layers.
Yeah.
Here's the thing about gauzy and splat layers.
First of all, it sounds really cool.
It's a great Thanksgiving or a holiday with your family.
What do you do?
Do gazi and spa splat layers, and they go, oh, that sounds impressive.
But when you do it, you go, that's really cool, and then you
kinda move on something else.
It's just, it's like, it's, it's neat and it's pretty, but
I don't, I don't know why it,
so upshot is photogrammetry.
Whenever you want to create a 3D model, whether it's from aerial imagery,
so top down or terrestrial levels, um, this is a way to go to create
models that you can put into scene viewer, uh, and now utilize them.
And it's just how is it different from, uh, the traditional photogrammetry?
I. Understand it, but I could not explain it.
Same.
I don't understand it well enough to be confident to, to talk about it.
To
me it's a little bit like the different types of creaking.
Like I kind of know what they do, but I don't really understand the math.
That's,
yeah.
Yeah.
That's the, yeah.
Okay.
But the other three that you thing I was thinking of is, uh, QGIS 4.0,
which is supposed to come out this month, or was supposed to come out
last month and maybe has, maybe hasn't.
Yeah, I'm the guy that knows that,
that's why I was like, I don't know if I wanna say this right after
Frank was talking about RGS online.
But just be aware apparently one of the big things is going to be
more 3D capabilities, and this includes things like point clouds
and stuff, which you could bring into before, especially for lidar.
But, um, it's just.
Better in four from what I'm reading.
But again, I haven't downloaded it yet and I don't see it on the,
um, the download page right now.
So
I haven't seen it yet.
But I can always tell when there's a change like that occurring because
you start to see more of the tutorials being put up, places getting ready.
So we should, and now that's, this is not the long-term release, this
is the original, uh, initial 4.0 release, the 4.2 release, which
is I think October or November is meant to be the long-term release.
So, if you are using this for day-to-day work, you know, don't switch over.
Maybe have it installed in two different locations, but.
Yeah, it's a great use case for a virtual machine or something like
that, you know, see what you can do.
So keep that in mind.
Texas a and m University worked with the US National Science Foundation
to create a, they're, they're just saying it's just a massive data set.
That is.
Of high resolution earth systems, um, that's free that
you can use for simulations.
Um, and it's giving them new insights into meteorology.
And also, you know, allowing them, they said to do, um, models further out
from different types of weather events.
Uh, so in the, you know, nature geoscience, they talk about how
it's already helping them to better predict precipitation events.
And looking at things like atmospheric rivers, um, and tropical cyclones, um,
that are affecting, you know, fisheries and other people along the coastlines.
Um, so, you know, this is a, a major accomplishment, as they say.
It's really exciting.
Um, and it's gonna open up the types of research opportunities for
people that are gonna be able to use what they're calling Mesa clip.
Is the, the high resolution dataset.
This dataset is six over 6,000 terabytes.
I mean, that's just mind boggling, but also.
We used to think, we're used to thinking in big data sets
like that in our, our world.
So on the one hand, that's mind boggling on the other hand.
Yeah.
Okay.
That makes sense.
Yeah.
What's, what's interesting they said is typically if you're working with
the Earth's climate or, or you know, with this type of data, you would be
using low resolution for simulations.
And this allows you to use high resolutions for something that's
extremely complex, like looking at interactions between the
ocean, sea, ice, and land surface.
And I always think, you know, dealing with sea ice is just really fascinating,
um, because of how complex it is.
Now, keep in mind whenever they're talking about high resolution, this is
high resolution global, so we are still talking about kilometers per pixel.
Um, so somewhere between three and 25, it seems, uh, depending on
which data layer you're looking at.
And this is also 4,500 years of simulated data or PR or, uh,
derived data from various sources.
So.
That's past, present, and future.
So it, you know, it's predicted and the past, so you can follow that all along.
Yeah.
And they're, and they're looking currently for other groups to work
with them to come up with other simulations with this data set.
But continuing with ncar.
Um, continuing with Ncar r the American Meteorological Society, and I believe a EG
as well have come out in response because Ncar R is under threat to be dismantled.
You know, NCAR being the National Center for Atmospheric Research, um,
they said they have support from not only the association and researchers,
but also from industry that, you know, this is, uh, across institutional
network that's been built up.
They consider it vital to publicly accessible resources
for atmospheric scientists.
And that it's crucial to what they do for, for understanding
and predicting the weather.
So they're, you know, asking for, for comments from the public and others
to, to keep it from being closed
by March 13th.
If you are gonna comment, make sure to, uh, comment, comment before March 13th.
Ncar, if you don't know, falls under the National Science Foundation.
And this is a critical piece for university research about
the, uh, um, atmosphere and, and the research around that.
You can understand why this administration may not support that
this fully as past administrations have, uh, but it does provide us some
really important science that that.
Is in danger of just being lost.
So please, if you're inclined to comment, take the time to do so.
Yeah, and what they said is one of the things that could happen is because Ucar
spent so long building up this network, they have research teams, computing
systems and observation infrastructures, um, that no one else you know, has to use.
Is available.
And the data, the data they provide is in a wide range of sectors
that maybe you don't think about.
So partners in agriculture you know, water utilities, private weather companies,
uh, aerospace and insurance, uh, and financial risk industries, right?
And, and tons more.
So, it isn't just it, the science is crucial, but that is
not the only use of the data.
Uh, that comes from
ncar as mentioned before, the a EG is you know, concerned about this.
And so they're having a virtual coffee hour.
Yeah, this Friday, uh, March 6th.
So if you're hearing this before March 6th if you're interested, it's
gonna take place 10:00 AM Pacific time, 1:00 PM Eastern Time in the us.
And basically they'll be talking about the A a G Climate Action Committee.
We'll be talking about the proposed restructuring of ncar.
Yeah.
And so that might give you some ideas of what you might wanna comment on by the
13th if you are contemplating doing so.
And then finally this week it's, it's, I don't know, it maybe was, would've been
better as a web corner, but I think it's news given it's context of a former.
Google and many other companies project manager, engineer, whatever uh, du
put together vibe coded, essentially a virtual globe that is pulling on lots
of os n or open source information.
Sources and putting it on this thing using various agent based
AI technologies and techniques to basically build this thing up.
And so people are calling it an open source, Palantir, or, I dunno, they're
calling lots of different things.
Weirdly it's gonna be called worldview, so I'm curious if it's gonna be
based on NASA's worldview code.
NASA was whirlwind.
Was it whirlwind?
Yes.
Worldview's a satellite.
Oh, that's right.
Yeah.
But still odd to use that.
And also spatial os I'm like, I'm getting such watchdog vibes.
Yeah.
From the whole thing and it, you know, but which, hey, the, the, as he pointed
out, this stuff in various forms has been around, uh, and thought about for a while,
which is of course is why you can five code it.
'cause the code for a lot of these things are out there.
But yeah, he's, he's had a couple of videos recently on YouTube to talk about
this and the response to him working on it and sharing videos about it.
Uh, apparently he's gonna release it sometime later in the year as a, as a
tool set or whatever you wanna call it.
You can find out from him when he would call it, but it's just,
it's just interesting 'cause you know, it, it is building on.
His time.
You can see it, you know, Google Earth and those type of technologies.
It's really kind of, if you take Keyhole and advance it 20
years, what it would've been.
Right?
Yeah.
I like his sentence.
What I built is fundamentally a surveillance aesthetic
built on public data.
So a lot of it is about the visual and, and how you're accessing
and integrating the data.
It's, it's almost like what a world we live in because we've got, you know, Jesse
saying the vibe coding and you saying the aesthetic, and then I was looking
at if the whole thing skinned to look like a classified intelligence system.
So in some ways it feels like, the early days when, when, you know, people were
like looking for the challenge and putting things together, but then it's, it's made
off of, you know, very real open source.
Things that people have worked on for a long time.
And then on top of that, it's, it's, you know, a very serious
area of the geospatial community.
So it's just a weird juxtaposition, but also pretty cool to see
my favorite quote between Gemini, Claude, and Codex specific versions.
It's honestly wild what you can build right now.
The really interesting there is that he's hitting across effectively two
or three different ai uh, uh, models.
And he's not wrong, but it's still, I think even now it impresses me
what I can get these things to do.
Yeah.
Just to drop you a few lines of code and you just put that
together with this other set of.
Code that you got from over here and just keep piling together until
you get the, the tool that you want.
Now, if you want it to be secure, that's apparently a whole other issue
whenever it comes to vibe coding.
But,
well, you know, and, and really it's about knowing how to tell the computer
very specifically what you want.
And that's the tricky bit.
That's what a lot of people don't realize about vibe coding.
A lot of it is talking about in talking in algorithms not.
Hey, I want a thing that does a thing that, with the stuff that
puts this over here, you know, kind of vagaries like that.
'cause it doesn't work.
You've gotta say, okay, now make it do this now make it do that
now make it do the other thing.
And it's just, it's fun in a weird way, but it does take, it's
a little skill in its own right.
I think maybe the reason that I wanted to put this in for the news is that,
uh, one of his most recent videos was, uh, during the, whatever they're
calling the stupidity in Iran whenever that happened, basically he went back.
Or while he was doing it, while it was going on, you know, let
his agents focus on some of that.
And so he put together a visualization, a timeline of essentially, you know,
everything from shep movements to plane movements to uh, when the
airspace were opening and closing.
And of course, since it's all based on a virtual globe, you can, you
know, watch these things as they're taking place and see the patterns
that are happening in response to.
The attacks.
It's a pretty impressive little tool set.
It does open up the, the mind.
I think that, well, what could I make it do?
Yeah.
But isn't it also a little bit of the, the dream of the urban observatory, um,
which I don't think has, has grown since, you know, but I still use it for things.
But you know, just this idea that we can, we can see things live
and, and know what's going on.
Yeah.
I mean, you know, Sue has talked about.
Well watchdogs, right?
In their we are data and their CD os, all of those things.
I thought you were gonna say mini Tokyo 3D.
What's that?
I thought you were
gonna say Mini Tokyo 3D Well, yeah, mini Tokyo 3D is, is, uh, another,
I think, yeah, I think you're right.
Bar with we've at the, with the technology we had in hand each time this, this
has sort of been, envisioned by lots of people in different ways, right?
We, we update to what we can do, and now, you know, we've got a new set of tools.
And another comment from ABR is worldview's, the first attempt
to make the thesis visible.
And that thesis is we're building AI that understands the physical world,
the way it understands text, right?
So we keep adding each, each of these things into what is essentially, or even
back to, you know, bill Gates' one-to-one digital earth kind of representation.
So, yeah,
so the, this is a whole topic.
Um, but yeah, it does raise the issue of do we understand the world, the
way we understand text as humans?
Well, that's the thing, right?
That's why we have visual language models, large language models.
In theory, we're building spatial language models.
Yeah.
Or spatial models.
I know
what that would be.
I'm not sure we understand it and I don't have confidence that AI will understand.
Well, lemme put it this way.
AI may be able to understand the earth the way it's, understands
language, but I'm not sure the way it understands language is quite what.
People think it is.
Well, we don't think of the, we don't think of our concepts
and discussions as tokens.
We're not coming up with it.
Okay?
Now, that's not entirely true.
Sometimes I'm coming with it word by word, but most of the time I'm
coming in with most of a thought.
Not putting it together as I'm going,
but like I said, I don't wanna go too far down that road 'cause I
think that's a whole nother topic.
But it is an interesting idea to think about, you know?
Yeah.
'cause it gets into, is it understanding the world the way that we understand it.
But what they're drawing from is, you know, that we, we don't really understand
the world as much as we think we do, which is, you know, why we're, well.
That's it for the news
onto the web corner.
Layers of the past is an interactive tool that's been created by the
New York City Botanical Garden and the Urban Conservation Team.
That allows you to access over 200 geo-referenced historical maps of New
York City, and it lets you explore the evolving geography infrastructure
and neighborhoods over time.
Um, in many ways it's a deep map that allows researchers, educators,
and also people that are working on their genealogy to go in and
understand the past and context today.
And they're hoping that, um, the historical cartography can inform
contemporary understandings of New York City from different perspective.
Um, and if you go in and and use it, it's, you know, pretty cool.
It's, you know, similar to what Boston has created when they have that spyglass view,
um, that overlays the different layers and information and they're going to be
releasing additional maps and features on a quarterly basis to build this up.
So it's pretty cool to use and, you know, move around and look at.
I'm liking this resurgence of these things.
So, you know, I'm thinking of the tools that David Rumsey built for David
rumsey.com, like all of his maps and stuff, but, but sometimes you want the,
the targeted sort of thing and, and a number of different, of these types of,
of projects related to New York City, like the old NYC photos, some other things
that the New York Public Library did.
These are great.
Uh, and seeing the maps kind of overlaid.
So a cool little tool.
I think in later years.
More recently, the collection has been geo-referenced as
well, so you kind of get that.
What collection that capability?
The David Ramon collection.
Oh, yeah.
No, they've done that for a while.
Yeah, yeah, yeah.
But so you, you can bring it in and, and compare maps and those type of things.
Okay.
So this week's main topic is really kind of an extension of our news items
because it's really just the fact that this year at Geo Week, there
was a, a fairly substantial focus on.
The use of terrestrial mapping and a lot of it's, uh, things like slam terrestrial
lidar you know, just using all those pictures that we have from you know,
the cars driving around and collecting pictures in urban areas and such.
And so there's a lot of data out there and we're creating more all the time
and we're creating new technologies to correct create and collect.
Higher resolution, local terrestrial data.
And so I think it's just a question of, you know, what are your thoughts?
And I think this is gonna be a really short one, um, especially given how
long we talked about other newses, but what are your thoughts on where we're
heading with terrestrial right now?
I think the.
Biggest challenge.
And ironically enough, I think we have a structure that that was sort of
philosophically designed to handle it.
But the biggest challenge is, is that, I don't wanna call it quite
a gra grassroots, but it's the best analogy, effort here, right?
So people are working hyperlocal when they're doing this and creating
data for their very specific purposes and and weaving this together into.
Something a little more cohesive or, or more broadly
based is really the challenge.
More and more companies are doing things that allow for that, but I kind of feel
like we're ending up with a few, I, I guess walled gardens is the, I. Proper
term to use that it's, it's hard to work across space outside of the hyperlocal.
And that's when I think things get really exciting when they bubble up.
And, and I was thinking of the national map as sort of the.
Philosophical prototype of what they were trying to do 20 something years ago of
getting data from all these local areas into a one big map that you can kind of
drill down and do, and never really panned out for a whole lot of, in my opinion.
It didn't pan out for a whole lot of organizational reasons, not
necessarily tech, but there are some technical reasons behind it.
But I think this is a really exciting thing that I kind of feel
like maybe the, this, you know.
Terrestrial mapping.
I kind of feel like this may end up being our location based services thing,
like, you know, 15 odd years later we're saying that's about ready to break out.
It's about ready to break out.
I, I think any day now it could just reverberate if we can tackle
this, how do you integrate this stuff usefully, meaningfully
Well, and and you also have that con that conversation.
I think that.
Um, whenever we're talking about terrestrial mapping, it gives you
the idea of that, that slide side looking camera and those type of
things, uh, that are on the ground.
But it's equally the high resolution drone data, right?
Because you're flying a hundred feet, 200 feet, you're specifically using
it to oftentimes capture buildings as they're being constructed or site mon
modification, those type of things that are very much terrestrial activities.
You're looking at them.
Repeatedly over time.
And so it has the same kind of experience as the on the ground terrestrial mapping,
but, you know, just low elevation, aerial.
So I, I think I would include that in there.
And so yeah, definitely whenever we're looking at things like open
drone map, no weight, that's the software, is it open aerial map?
That's the place that you can put drone images?
I don't know.
I can't remember right now.
But yeah, there's a, there's a platform that allows you to do that.
Which I would argue is part of the problem, right?
Is the fact that what is the thing that has, the thing that Elijah
put this, you know, there's a lot of these different subsystems
that are creating this complexity.
One of the quotes that I really liked from the, um, CEO of Pix four D was
we were focusing on turning, hitting infrastructure on functional data, and
they're using a lot of augmented reality.
And I wanna say it's about time, just not because, um.
No one was doing it, but just that, you know, infrastructure is so hard to capture
and to work with and it's so necessary.
So anything that makes people's lives easier in order to see it and work with
it, and they're talking about trenches and things like that you know, just
is a really good use of, you know, the, the technology and where we are.
Well, I think this is, this has been like the, the dilemma, right?
That we've seen evolve the overhead view.
Where our data capture and remote sensing and stuff like that has been
very, gotten increasingly better, but, but very good versus the ground, right?
You, the, the map, uh, essentially comes out from you.
It was an old quote from, um, what is it, Michael Jones from Google, right?
Where the one start of, of street view and things like that was, you are
the map, but, but now you're talking about reconciling that in the data
collection and it was so expensive to do.
Uh, when there wasn't, you know, and time consuming, right?
So a lot of that expenses in labor of, you know, surveying and, and those
types of techniques on the ground.
Uh, but being able to combine, like you have your, your remote
sensing from higher altitudes.
You've got your, your remote sensing now a drone based and,
and other technologies like that.
And then you have the ground layer where increasingly you have the technology
to get What was all of that stuff that.
Is essentially perpendicular to the ground.
So not easy to capture it, its depth right in that third dimension.
Um, it can be done somewhat with, with remotely sense data from the top
view, but to really capture it, to capture its nooks and crannies, uh,
at the, the scale that we need it.
Right?
So it's a question of scale now.
I think we're finally seeing the use case, um, mesh with the technology,
uh, and the speed at which the technology can now do it right to,
to alleviate some of that bottleneck.
Uh, and eventually right to have our hyper-local things as people add the
pieces, like Frank mentioned with the national map, to eventually sew
in the pieces of the quilt so that we don't have these islands that
are so far away from each other as as we do more and more, right?
We can stitch that mosaic together at the highest scales in all three dimensions.
And it's not that I don't think the desire was there, 'cause I've been
in sessions, um, where, you know, you, they were talking about similar
technologies and uses, but like you said, it was always very time intensive
and also it was very expensive.
And once people, people in a municipality or a company here, this is how many man
hours it's gonna take and, and how long it's gonna take and how expensive it's
going to be, they always like backed off.
Even if it was going to be, you know, very useful for what they were trying
to do, and I think this is going to make it more likely, like you said, that you
know, you sue those pe so those pieces of the quilt together and everyone benefits.
I think that is one issue that we're still facing is that, you
know, whether we're talking about slam, we're talking about lidar, um,
whatever it is, you know, whatever specific aspect of these technologies
that we're talking about, short of.
Structure for motion or glosson plats where it's, you know, just a traditional
camera that you're using to do it with.
It's just, it's really expensive and as soon as you know, one of these
technologies becomes a lot less expensive.
Talk to me.
I will be out there the next day and getting our facilities
folks to, to start using it.
'cause they're still relying on GPS whenever we have a you know,
a hole open with something in it, they're going out and GPSing it.
Or having me go out and do an aerial image of it if it's a large of hole so
that we can, you know, have it in there.
So the next time somebody needs to build something there, we'll
know where the pipes are, but it's a. It's a cost thing, right?
We can't afford to have a $60,000 LIDAR device sitting around
waiting for that next project.
Well, it's kinda like we've gone back around again, right?
Because, uh, you know, you used to have the data pyramid that basically talked
about you know, it was a normal looking pyramid, and you would have at the top
the localities that were, you know.
Producing things, really the private citizen, not the
legality, just producing things.
And it was sort of expand out to the sort of federal governmental level.
We're the ones producing most of the data, and then what happened?
One.
You know, location-based services and the cell phone and all that stuff took off.
That flipped it.
So now the people producing most of the data are private citizens that are
just volunteer geographic information and people like that putting out stuff.
And governments using the data, not producing the data quite as much.
This is a gross generalization, but it's kind of what happened
with the that data period.
Now we kind of flip back, right?
So that.
On the terrestrial side, it's the governments that are doing
that, and there's a very definite divide between have and have nots.
You're not gonna see a very poor county that's putting out a lot of
data at this scale, on this level, because of just what you said, Jesse.
It costs too much money to acquire the equipment or to even hire a company who
has acquired the equipment to come do it.
And the use case is a lot harder to make when there are more fundamental
structural problems that need to be dealt with, like education or.
Water or whatever it is that these counties are struggling with, whereas
someplace like New York City or Boston or DC probably has better access to this
type of technology, uh, if they want to.
So it's kind of interesting that we're going back to see these sort of
richer governmental, uh, scales being the main producers because of the
sheer cost of production is so high.
But just like every other technology we've ever dealt with, you know, it.
Everything is expensive until they figure out how to make it
less expensive or inexpensive.
A cell phone used to be, you know, just for the rich, but now everyone's got one.
So it's just takes time to make that, that, you know,
evolution of the technology.
Yeah, and I think some of that will be, uh, as I was kind of alluding to
earlier, is that some of that line will be crossed when you see so much.
Benefit in shrinking the time it takes, right?
So the human labor time versus the, the initial outlay of the technology.
And I think that that's, that's where we're approaching with some of this.
And, and you can get a complete picture maybe with one time through
that, have a multiple uses, right?
Once that date is acquired.
Yeah, Sue, like, I don't know how much it costs, but Mn GX one
has created an all-in-one slam lidar RTK 360 imagery scanner.
Um, but they're saying that it can reduce the time to survey a site
by up to 95% so that you can do in a single day, which would've you
would've done in weeks worth of work.
So, I mean, I don't know if that, that claim is, you know, accurate,
but even if it's an exaggeration, that's still really impressive.
Um, but then looking at it, it's, it's, you know, like a
futuristic looking survey tool.
When you see it you know, and you go, well, how much money is
that gonna cost to get just one?
And, and even if it is, you know, there's a, a lot of managers are looking at it and
going, I'm paying this person to do this work and giving them more efficient tool.
I still gotta pay the salary and the, you know, the overhead and the f and a
and the, you know, all that stuff, the health insurance that comes with it.
So there's not a lot of incentive necessarily to not throw
labor hours at a problem yet.
Now at some point that flips where it's cheap enough that you
go, well, okay, wait a minute.
This makes a lot more sense.
But it has the flip side of it that you didn't tend then tend to
reduce labor, which has other issues that go beyond this technology.
But I think what's gonna end up happening is I think we're gonna
produce a whole heck of a lot of stuff.
And there's another issue we haven't really talked about,
which is interoperability, right?
So every one of these projects are done for a specific purpose.
They have a specific use case and a specific problem they're trying
to address, and they're using this technology in a way that helps them
solve the problem hopefully successfully.
Even then, we know with technology, a lot of times people throw technology
at it and use it improperly.
Either way.
You end up with all these bits of data that in theory, even if it's using the
same, you know, GX one camera system that uses the same data formats,
they're for different purposes and they don't necessarily mesh well together.
So when you want somebody who can look at this downstream like, what we, we
would like necessarily, it doesn't always work because getting these things that.
Don't have harmony.
A purpose to integrate is such a nightmare, and that's something I
think is gonna be a real problem.
Once we even get the techno, once we get the technology down,
then we can produce the data.
It's gonna make that even worse.
Yeah, I think that's one of the challenges is a lot of these look
proprietary proprietary in data and in system and in technology.
Um, because we're, we're still at the stage where everyone is, is trying
to gain, you know, their market share of this you know, which we've seen in
the past with, with other stages and, you know, geospatial technologies.
How does this tie into the, the broader category of reality capture that multiple
companies, Autodesk, Esri, et cetera, are trying to, to highlight right now?
My thought, of course, is that it, it is one in the same.
It's, uh, about that it's not.
Quite to the point of trying to do a, a complete twin where we want to
have real time updates of sensors and things like that, tying into it.
But, you know, it, it is still giving us these snapshots, uh, more readily
than we we may have had in the past.
I think it is on the basic assumption of.
More data, more better.
Right.
Is that okay if we produce?
I agree with you that it is essentially just making more data to try to
hit a specific data category that isn't necessarily being filled.
I'm not sure if the real time, which would be the dream of course, but even now,
just getting a one-to-one representation of everything everywhere at one time
shot would be a miracle in its own right.
And I think this is an attempt to get to that.
Even if you have to do time slices that update every end number of months or
years or decades it gets you somewhere.
I think this is an, an attempt to do that to, to make reality in a virtual sense.
Okay.
So that was kind of it.
Like I said, it was a, a thing that just was very prevalent in the at
least white papers and press releases that came out of Geo Week this year.
And so it just seems like an interesting thing to, to chat about for a moment.
I just, I just wanna post script and say, even though I knocked
out a bunch, I really want it.
I really want it.
Give it to me.
Yeah, I mean, that's kind of it, right?
As soon as somebody can give, can give me a price that I can take advantage
of or a, an off, an open access, open source, um, creation of the
products that I can take the time.
And that's where the biggest problem comes, uh, take the
time to put together myself.
I'll be there, but we're not there yet.
Onto the events corner, as always, go to some events.
We'll be in, uh, a, a g, Sue and I probably, maybe, I don't know.
It's, it's still iffy with it only two weeks away with everything going on
in the world, but we might be there.
So if you see us say hi.
However, if things calm down a little bit June 3rd and fourth in London,
you can check out Geo Business 2026.
State of the Map 2026 is taking place August 28th through 30th in Paris
Geo Week 2027 will be February 23rd through the 27th in Salt Lake City, Utah.
And this is a new location for them.
Of course, they've been in Colorado for previous weeks, I believe always.
But now we're looking at Salt Lake City.
Not, not to talk smack about Utah, but I gotta say two of those locations sound
a little cooler than the other one.
I mean, if you wanna go skiing, I guess, you know, February and Salt
Lake wouldn't be terrible, but
that's true.
I still,
other than the elevation, but anyway, that's
similar.
Yeah.
It still, it still brings the same questions for me as Denver.
Will you get snowed in?
But that's, that's just me.
Of course.
If you'd like us to add your event to the podcast, send us an
email to podcast@veryspatial.com.
If you'd like to reach us individually, I can be reached at sue@veryspatial.com.
I'm barb@veryspatial.com.
You can reach me atFrank@veryspatial.com.
I'm available at Kindness Spatial, and of course, you can find all
of our contact information over at very spatial.com/contacts.
As always, we're the folks in very
spatial.
Thanks for listening.
We'll see you in a couple weeks.
Crop
feelings, chasing me on the road.
It's not fair.
Wonder, anybody
inside
God
books?
I don't
scream.
Free ride in the front seat, but about another ticket for the nose
pleases because so ain't cheap.
Take the city outta me to the country.
Nothing personal.
Talk behind my back.
So comfortable.
Keep it up, let it go.
God.