Why Are Maps Hard? - Interview with Cory Whittaker

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Maps...we use them almost every day of our lives.....but...what makes maps hard? From the paper maps we used to pull out on car trips to the digital and dynamic maps that we have our smart phones, the problems around making and maintaining maps have been with us for a while. Fortunately...we've got an expert to help us out here.

Cory Whittaker, a long time self professed "map nerd", takes Rob and PJ on a journey on maps and how they are used in the modern day.

Come and join us for our first interview episode!

Episode Transcript

(00:00):
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pj_1_02-01-2024_100239 (00:10):
All right, everybody.
Welcome back to Tricky Bits withRobin PJ.
Today we're really excited forour first interview with our
guest, Corey Whitaker, who'sgoing to help us, or more to the
point.
He's gonna answer the question,why are maps hard?

(00:31):
We've been using MapQuest, we'vebeen using Tom, Tom Google,
we've been using Apple Maps fora very long time.
Like what's what's left to bedone At this point in time, we
have GPS I think we're gonnacollectively find out, and this
ties back to what we talkedabout previously in augmented
reality, that maps are a lotmore difficult than you might
think, and is a whole lot morestuff to be done there.

(00:53):
So with that.
Corey, welcome to the show asour first guest,

Track 1 (00:59):
Appreciate it,

pj_1_02-01-2024_100239 (01:00):
Rob and I would love to hear a little
bit about your backstory, howyou got to where you're at, and
let's take it from there.

Track 1 (01:08):
the backstory with this is that, I've always been a map
nerd, if that's the best way Icould describe it, back in the
day before, you'd be taking roadtrips with your parents, you
know, you're sitting in the backof the station wagon, not
buckled in, broken glass andrusting ails around you because,
you know, that's how we wetraveled back then is we didn't

(01:29):
have anything to entertain usreally as we're driving down the
road and where I grew up inArizona, it, we were going to go
see relatives.
It was a four hour driveminimum.
So, you know, we spent a lot oftime in the car.
Well, I give my parents creditto keep me entertained.
They handed back the RandMcNally and all of those just

(01:52):
handed into the backseat.
I would sit there and look atthe maps for hours on ed.
So you would say that from ayoung age.
I, I just love looking at mapsand knowing all the intricacies
of them.
So really that love of maps iswhat took me into a career
first, starting in working for acity government, doing maps, and

(02:15):
then all the way to working forthe preeminent map company in
the world, Esri or ESRI, theyare involved in every major city
in the us every state, federalagency about anything that you
use maps for.
It started with that.

(02:36):
So anyway, that's kind of mybackstory of where where I came
to be, this map nerd, if youwant to call it that, and I'll
probably call myself thatthrough throughout this whole
thing.
Going from that to helpingeveryone utilize maps and even
if ways, like you had mentionedin directions and everything,
there's ways that those mapsthat I work on and help get

(02:57):
people to what they need to goand where they need to go to.

pj_1_02-01-2024_100239 (03:00):
So for folks that are younger than 30,
and that might even be generous,R McNally, was a map that was on
paper that was folded.
And one of the most complicatedthings was to fold it back into
place because of the complicatedinstructions.

rob_1_02-01-2024_100240 (03:18):
You can still buy these maps too.
If you go to the gas station.
They're still there.
They come in books too, I think.
I still have one in my truck andI just like the safety of having
the paper map and like Coreysaid, it gives people in the
truck something to do.

Track 1 (03:34):
Exactly.

rob_1_02-01-2024_100240 (03:35):
who've just flipped through the map
while you're driving on a longroad trip.
Rather than play with the phoneI mean, people just to look and
you can just see, I thinkthere's context.
You can see things that are nearyou.
It's like, oh, let's go here,let's go there.
And I think you lose some ofthat with the digital maps.
So the, uh, the paper maps arestill in full force.

pj_1_02-01-2024_100239 (03:54):
Other than folding them, what makes
maps a hard problem classically,Corey, and then what makes them
a hard problem today?
Because we've got a number ofcompanies that are doing this,
obviously, Esri, as I believe,the oldest and most preeminent
one, and then a whole host thatare also trying to solve these

(04:16):
problems.
But what problems are trying tobe solved and why are they so
difficult?

Track 1 (04:20):
Well, let's go back to those paper ones for a minute.
And I'm sure everyone has seen amap of the world.
You know, that's when we see allthe continents, everything in
there.
But have you ever noticed thatcertain maps look different than
others?
And where I'm going with this istake Greenland, as a matter of

(04:43):
fact.
Have you ever seen those mapswhere Greenland looks the same
size as South America?

pj_1_02-01-2024_100239 (04:48):
Sure.

Track 1 (04:49):
And there's others where it doesn't, where maybe we
see a, a stretch of see onestate.
Well, this comes from theproblem.
I don't wanna say a problem, butthe quandary.
Of taking a spherical surfaceand putting it on a flat map.
When I was going to collegetrying to explain this.

(05:09):
This is what we call projectionsis how we manipulate the map
itself to sit on a flat surface.
And we did this, experiment toreally help you understand this.
And that is take an orangespherical object just like the
earth, but peel it and take thatpeel and flatten it out.

(05:31):
What happens?
You have gaps in it.
you have to tear it open to getit going, but to lay it
completely flat, it doesn't gointo a rectangle.
It doesn't, it wants to stay in,its, spherical shape, so usually
have gaps in it.
That putting a spherical shapeon a flat surface, and that's
where these projections come in.
It's basically how we manipulatethose tears in the orange to be

(05:57):
able to fit onto a square mapand look somewhat decent.
Because if you were to take,like I said, that orange peel
and pretend it's a map, put itin there, on a table or whatever
it might be, and then youoverlay where the continents
are, you'll see a big tear in,in, especially around the polar
regions, you know, Greenland,the, Nordic countries,

(06:19):
especially, Antarctica.
You see some maps.
Antarctica looks massive, butthat's just because of this
projection issue.
So that's one problem

pj_1_02-01-2024_100239 (06:29):
This is not a new problem, right?
This is a problem that's beenaround for centuries at this
point in time.

Track 1 (06:35):
We're talking about the days of, you know, those early
maps of when, explorers werefirst coming to the new world,
where they are trying to drawthose out.
they were handmade then.
But once we started to be ableto see the world as a whole,
that's when we really run intothis problem of these
projections.
So that's one thing that reallymakes maps hard is not every one

(07:01):
of'em looks the same.
And the other part of this thatI really think makes meps, I
would say hard but difficult tounderstand the overall
complexity of them, isunderstanding all the aspects of
our life that have a, I'mputting in quotes where
component.
So this where component, I'mgonna take my example of my

(07:21):
house here.
We already talked aboutdirections.
Well, okay, how do I drive to myhouse?
Alright, we have a point on, onthe map.
I have an address that's anotherset of information about this
where component, but also I haveelectricity going.
How does that electricity get tomy house?
We have to map out where allthe, electric lines are and

(07:44):
sewer water.
Anyway, I'm, going over this asI want to instill on your minds
of we have this one location, myhouse, and what all kind of
items go into making that housefunction in a modern society
like today.
And that's just the example ofmy house.

(08:04):
Let's think about supply chainlogistics.
Of all the things that go intobringing my.
Keyboard that I'm looking atright here, from where it was
made to the manufacturer, to theretail store, to this or this.
Those are all where components.
So this, uh, almost dance of allof the things that make our life

(08:31):
today.
The where component is keythrough all of these.
So one of the things we hadtalked about earlier was, okay,
driving directions.
That's a tip of the iceberg,really with all the things that
come into, are modern lives.

rob_1_02-01-2024_100240 (08:50):
I think, one thing that people
don't realize is what you saidof like, directions at the tip
of the iceberg.
Everyone interfaces with GoogleMaps and Apple Maps and they
think that's it.
that's the mapping systems thatwe know.
But even those two systems arethe tip of the iceberg.
Like I said, the people you workfor are backend map providers
who feed data into this entirepyramid of mapping systems.

(09:13):
And there's other companies who,do that too.
Even open street maps does it ina communal, public sort of, way.
it is interesting.
That's just how big this, whereproblem is and how things get
from A to B and how, not evenpeople or things.
It's like electricity gets fromA to B

Track 1 (09:30):
mm-Hmm.

rob_1_02-01-2024_100240 (09:31):
the, the, uh, GIS databases that
governments keep for exactlywhat you said, utilities, roads,
whatever, and agreeing onanything is across those is
gonna be next to impossible.
So I assume there's a lot offuzz in all of this too.

Track 1 (09:47):
Oh, absolutely.
Keeping everything up tomaintaining it, making sure that
when a new road goes in, howdoes it get from the city?
Or state that paved that road tothose databases to Google and
Apple Maps, that whole processis key for that end user of who

(10:09):
will be utilizing these.
So the, the dance I, I talkabout that dance of how the data
flows through.
There is really a dance is thebest way to describe it because
there's so many ins and outs andeverything, so very, very much
so the last part I want to talkabout why maps are difficult is

(10:30):
when I went to college I had totake a cartography class.
This is basically how to make amap, but one of our required
readings, and this is the nameof the title of the book, is How
to Lie With Maps, and it's by agentleman by Mark Moner, I
believe, if I butcher his name,I'm sorry.
But it is really talking abouthow maps.

(10:53):
Can tell the story of what theMapmaker wants to tell.
So how to lie with maps is, isjust as easy as understanding
where an address is.
Because if you think about it,making that council district map
was telling a story.
These political districts aretelling a story., I was making a
map of it was transit ridershipbased off of certain population

(11:18):
characteristics.
Well, if I wanted to tell thestory of we're getting more,
minority ridership in certainareas, I can adjust the filters
and the parameters of my queryin a way that shows that more
than, okay, I'm just goingstraight.
this is the number of people.
So.
That story that you want to tellwith the map.

(11:40):
And that's what that book of Howto Lie With Maps is all about.
Is everyone has a story to tell,but is there a agenda behind
that story that you always haveto kind of weed through as you
do that?
So those are just several topicsof how you wanna take maps with
a grain of salt because therecan be a story behind it and you

(12:05):
need to make sure you're gettingyour maps and your information
from authoritative sources andthings along that nature.

pj_1_02-01-2024_100239 (12:10):
Backing up, since we are, you know, a
technical podcast, it's actuallyreally useful to dive into how
do we say where is where, likewhat is it that we utilize
there?
I mean, I can look on my phoneand I can look at latitude and
longitude.
I've got coordinates, obviouslythere's GPS, but you know, you
described earlier, you know, anaddress is some shorthand, but

(12:33):
it sounds like, there's so muchmore that goes into knowing the
address is the address.
So could you dive deep a littlebit into the technical side of
this in terms of, how do I saywhere something is?

Track 1 (12:45):
Yes.
That is a good question becausethere's, I don't wanna say
conflicting views, but there aredifferent ones along that line.
I look at it as, as twofold,first off, as a mapping
professional, I would prefer touse latitude, longitude for
about anything.
Because Apple, Google and who Iwork for with Esri do a great

(13:07):
job of, okay, I would needdirections to this latitude,
longitude that it takes youalong the street network.
And it's not like climb overthis mountain to get to it.
I come at it from the verytechnical professional, aspect.
Those people who, okay, I've gotmy phone and I just don't want
to get to the nearest Starbucks.
They're not gonna know alatitude, longitude.

(13:28):
So it's really those who wouldutilize it as a consumer versus
a professional.
But, since I know, and I'veworked on the creating the data
that flows into those mapprograms, it's really based on
latitude, longitude, and otherprojections, like we had
mentioned earlier, let's use theexample of my home here to map

(13:51):
out the property lines.
That's done through another typeof mapping.
So I guess there's another partof why maps are difficult is we
call it, direction and bearing.
So you would say, I find a brasscap, which is usually set up by
county assessor's offices orwhatever.
And then I go, so this bearing,you know, 270 degrees, walk for

(14:16):
45 feet, find a point ofbeginning, and then you go from
there and map out your actualparcel.
I would say that's really howeverything starts.
So if you take the example of myhome, it started with that,
pointing bearing.
To map out the actual property.
And then as the streets come in,then an address is assigned to

(14:37):
that from the city.
From that, then all of theutilities come into this
address.
And so it kind of starts withthat, pointing bearing is what
we call it to an address to nowmy house has a latitude,
longitude that Amazon or whoeveris delivering can drop it off
right there.
So it's a process reallybeginning and starting when

(15:01):
things are developed because ifyou're talking about raw land,
you're either gonna be talkingabout that point in bearing or
the latitude longitude.

rob_1_02-01-2024_100240 (15:10):
I have some of those point of bearing
markers on my property here in,Boulder County.
Aren't they placed like everydegree or something like that,
or some repetitive period.

Track 1 (15:19):
Yes, it's usually done by, quadrangles and, it depends
on the county that's working inlike Boulder County or wherever.
One that I had the mostexperience with was Maricopa
County down in Arizona.
They had, basically divided thecounty into grids, and so every
one of those grids had a pointof beginning.

(15:41):
And then subgrid, you know,there's Southwest corner of Grid
two, and then there's thenortheast corner of grid five.
And anyway, that's how itusually starts.
So that's really a surveyingtool as much as anything.

rob_1_02-01-2024_100240 (15:55):
So that's how we get from an
address back to a, a.
Latitude, longitude.
How does that vary acrossdifferent countries?
Because I assume all thecountries are completely
different, but ultimately therewas a system for everybody.
Maybe it's just literally youmake your own grid And it's,
it's you go from this address tothis longitude latitude.

Track 1 (16:17):
so I've would love to get your take on this too, Rob,
because I've heard ones in,especially these, property
boundary descriptions in theUnited States is pretty
straightforward because of thisgrid system.
I had a friend who was also, hewas from England, and he says
the property descriptions areall over the place because they

(16:39):
could go back to

rob_1_02-01-2024_100240 (16:40):
a, a thousand years old.
And it's like goes to this treeand that tree's been gone for
500 years.

Track 1 (16:47):
Exactly.
So maybe you'd start to talk ona global level.
I would say at least in the GISor the geographic information
system world that, I work in islatitude, longitude is really
kind of taken that over, butwhen you get down to the local
municipality level, that's whenyou need this more detailed

(17:07):
level because with, any kind ofGPS device, there is a decree of
error built into it.
So when I take my phone outthere, I can get within 15 to 20
feet of the actual location,where most of the time, hey,
well that gets me close enoughto the address that I'm going

(17:28):
to.
But we need to get down to thelevel of surveying quality.
You need hyper accurate.
We're talking sub centimetertype of GPS, and so that just
requires more equipment, butthat's when you crossover into
that professional level.

rob_1_02-01-2024_100240 (17:41):
Yes.
And then I guess the modern.
Version of the 2D map projectionproblem is the whole GPS data
problem as to how do we convertthese, I think GPS reports in
earth centric coordinates isit's bare basic system.
It's based on the center of theearth, and it's a spherical
coordinate system and convertingthat to latitude, longitude,

(18:05):
given that the earth isn'tperfectly spherical and
altitude's incredibly difficultbecause GPS isn't great altitude
to begin with.
And then we have obviouslyvarying ground altitude all over
the world.
So I think the one we use now isthe GS 98 or something like that
that everybody agreed on, on 94,

Track 1 (18:24):
the prominent one that, we utilize here at Esri is the,
WGS 84 standard, which is onethat, goes worldwide.
Again, when you're using thedevices, it can be a little, can
have a degree of error in there.
But for the most part that WGS84 is the one that we utilize
for all of our web-basedmapping, products.

rob_1_02-01-2024_100240 (18:46):
I think that became more or less the
standard.
I I do know in the past peoplehave been like, search and
rescue a missions have missedpeople because they've been
using a different data on theGPS than what the coordinate was
reported as.
And they went somewhere andmaybe close by, but not close
enough.
So these projections still existand we all have to agree on,

(19:07):
like I says, on the datu of whatwe're gonna use for GPS.
Otherwise your, lat long isn'tmy, lat long.

Track 1 (19:12):
Exactly.
So there's ones in, I've workedin ones from 19 27, 19 84, I
believe.
You're right.
There is one from 1998, but Idon't think it is as, adopted as
some of the ones from like 1984

rob_1_02-01-2024_100240 (19:24):
Yeah, I mean, mathematically, I guess
long longitude latitude is exactfor everybody.
It's this exact position on thesurface of,, the earth, but it's
technically the surface of asphere.
So that's where the error comesfrom.
And then obviously the,measuring error is due to GPS
and how, if we projects that,

Track 1 (19:39):
Yeah.
And how the satellites,coordinate and triangulate
between multiple in there.
So yeah, this is one of thoserabbit holes that I could tell
you we could go down becausethere's the built in
discrepancy, if you wanna callit that.
But then there's, one thatpersonally, I haven't worked
with it, but the, the militaryGPS is actually even higher
accuracy than consumer.
And so there's, to preserve thewavelengths, I can't remember

(20:02):
the exact terminology for myclasses that I took, but yes, it
was because the military needsmore accurate that the consumer
version of the GPS that we allaccess has that degree of, error
built in to preserve thatfrequency for the ability for
the military to have evenhigher, accuracy with your GPS.

rob_1_02-01-2024_100240 (20:23):
Yeah, going back, I think that was
called selective availabilityand it was, uh.
It was on for a long time.
The military one is still acompletely different system, but
selective availability wasturned off by the Clinton
administration.
And since then, everybody hashad the full accuracy of
valuable and they, I think theycan optionally turn it back on

(20:43):
again for certain areas andthings like that.
But I don't think they ever havedone, the military wanted its
own thing.
They have their own frequenciesand their own encryption keys
that they have, they need toaccess it.
But the civilian one is nowcurrently running a, the maximum
resolution that it can, run out.
And I think that's mostlycompetition too.
It's like if Europe and China arelease and Russia have
obviously glassner and ifthey're releasing all of theirs,

(21:06):
then why bother making GPSworse?
And most receivers today willreceive anybody's system.
So that's interesting that youget multiple satellites in view
and it, they can be differentsystems and it's all by the
magic of software.
All seems to work together.

Track 1 (21:21):
Exactly.

rob_1_02-01-2024_100240 (21:21):
So going back, we have these online
maps now, and obviously all thisis connected.
We have maps that are from GISdata.
We have maps that are fromsatellites.
We have maps that are from highaltitude, low altitude planes.
We have maps that, or imagesthat are from street view type
cars.
How is all that layered togetherto make that base map that you

(21:45):
see when you open Google Maps,for example?
And how do we know that the bitsthat are on the map are actually
in the correct place?

Track 1 (21:53):
I've heard multiple people bring up, how do we get
this information into the handsof consumers?
Know that, from my time workingin a local government, the city
was the authoritative source forespecially like the parcel
information, the streets, theaddresses.
How does that get into these,consumer products of Apple Maps,

(22:14):
Google, and so on?
From the GIS side, again, that'sthe one that I know the best is
these cities partner with thelarger organizations.
for instance, when I worked forthe city, we were partnered with
Esri to send them ourauthoritative data.
So let's say a new subdivisioncomes into the city to take that
information, we would put itinto our system in GIS process

(22:36):
that to where we'd send it outto other organizations, you
know, the state, the county, orso on.
But we also would send that to.
In this case, Esri, and if Iremember correctly, we sent that
to Apple as well.
So they worked with the localcities to get that authoritative
data.
So that's more of like the basemap, like you were saying is, is

(22:57):
getting the right information inthere.

rob_1_02-01-2024_100240 (23:00):
I was thinking about the other way of
what if the GI, I mean my landhere was mapped wrong, so I have
little faith that the GIS datais correct most of the time.
And what happens when asatellite image is obviously
correct?
The road is there.
I can see it pixel by pixel.
And the GAS data says it isn'tthere?

(23:21):
What happens there?
Do you just move the road towhere it visibly is of like how,
how is that?
I can just imagine thishappening thousands of times
every single time a day of likesomething's changed and
whatever.
And at least initially when wefirst mapped the world with
satellites and gave it to Appleand Google and people like that,
and people like yourself of justthat massive correlation job of

(23:46):
making sure we have a masterbase map that we can all kind of
agree is correct.

Track 1 (23:52):
Mm-Hmm.
So I guess it would depend, likeyou said this happened, most
likely happens thousands oftimes a day, how it gets fed
back into those.
Now I could see if one of theproduct projects that I worked
on specifically was changedetection of seeing aerial
imagery and being able to seewhat has changed over time.

(24:12):
So you look at historical imagesand, I've even worked with a,
imagery company to where theywould do daily flyover
satellites of North America andthey had that data served up.
So doing that change detectionand bringing that back in., in
my current position working withEsri, I work with customers

(24:33):
across the country and I couldtell you ones that would say,
oh, you found an error, let'sfix it, and would be happy to do
so.
But I can also see ones of like,oh, that's not our problem, not
our issue.
So that, that goes back to, Iwould almost say the varying
complexities and complacency ofgovernment agencies.

(24:54):
Because really if you thinkabout it, like your, the road,
if it's a public road thatshould go to and work through
the streets department or thedots or whoever that might be,
and some would be happy to bringin those kind of changes.
And I could tell you some wouldbe saying, well, not really.
Uh, we'll send someone out toget to it.

(25:14):
And at the speed of government,you know, it takes six to eight
months to get someone to go outand verify that that road is in
the wrong place.

pj_1_02-01-2024_100239 (25:21):
So this is an interesting point because
it, it hammers home that thegovernments are the
authoritative source of thisdata.
So even like in Rob's case wherethere is this clear discrepancy
between the government data andthe maps, and you can point it
out, you guys aren't able tocorrect that yourselves.

(25:41):
You have to feed it back intothe authorities in order to
close the loop.
Is that a fair way of puttingthat?

Track 1 (25:49):
I would say yes, partially, I can't speak to the
exact way that say Apple orGoogle maintain their street
network and everything, but atEsri.
We rely specifically on aprogram of partnering with the
local cities to get their streetnetwork data.
So we're not gonna go in andchange Rob's road, even though

(26:12):
it's blatantly wrong, until thecounty or whoever is the
authoritative source for thedata send sends us an update
with those

rob_1_02-01-2024_100240 (26:22):
think on the flip side of that, I
think Google and Apple doactually change it in the data
that they get.
I believe a lot of it's donethrough machine learning and AI
type processes these days.
But you'd see areas like yousay, like you could look at upon
the map and the satellite roadis over here on the left, and
the actual rendered road fromGIS data is not overlaid on the

(26:44):
visible road.
That very rarely happens todaywith Apple or with Google Maps,
so I can only assume that theyare fixing it from the data they
get, so they may not beauthoritative with the local
governments.

Track 1 (27:02):
Mm-Hmm.

rob_1_02-01-2024_100240 (27:03):
Which I think is what you're saying you
are, but they are correct fromthe roads actually here.
'cause the satellite said itwas, and it's hard to say that
the image is wrong and I thinkthey do all that through just
computational photography typeoperations and machine learning.
And maybe there's a bit of humanintervention in there when it
can't be done automatically.

(27:24):
But I do believe that that isdone quite a bit.
'cause I, I know of a few roadsaround here, if they were roads
that were wrong and now theyhaven't been wrong for years.

Track 1 (27:33):
It is very true.
And.
That's, again, I think the closerelationship that Esri has with
these local governments becausethey provide the actual
mechanisms for maintaining thoseroads in the GIS system.
So they rely on theauthoritative source for those
before pushing it out.

(27:54):
Because if, you know, Esri doeshave base maps as well that
utilize points of interest andall these others that, um, is
used in multiple aspects.
So yeah, there, there's, there'sdifferent parts to those.
Again, more of on the side ofthe professional users of I'm

(28:14):
maintaining that road, I amputting that into the correct
location versus someone who'sneeding to drive to Rob's house
to get, uh, to drop off apackage or something along those
lines.

pj_1_02-01-2024_100239 (28:26):
What.

rob_1_02-01-2024_100240 (28:26):
I, I do think the current map systems
that we've brought mapping intothe consumer space maps are now
a consumer product wherepreviously, other than printed
maps, they were very much aprofessional product, especially
in electronic form.
So with all of the resources andassets of Apple and Googles of
the world that are making these.

(28:48):
Electronic maps.
I think the customer consumerpointing side of maps is these
big mapping applications, whichhave progressed a long way from
giving me directions from yourhouse to my house.
And now maps are an entireecosystem of

Track 1 (29:05):
Mm-Hmm

rob_1_02-01-2024_10024 (29:06):
backend, data.
There's all the backendprocesses that Google, apple
have to do because like I said,there's Apple and Google.
Both know where traffic lightsare and where speed cameras are,
and they probably weren'tentered by hand.
They're probably all done viaimage detection.
And image recognition imagechanges across time.
So there's a lot of technologyat the back end, at the front

(29:27):
end.
We have these now incrediblycomplicated applications that
render the world in 3D and youcan see buildings and you can
see, even individual, like mayonly be a square for a house
where a skyscraper might havethe actual mesh of the
skyscraper.
So it's the correct shape, butjust the sheer amount of data
that these maps now contain forthe consumer space and for

(29:50):
consumer presentation is insaneand feed all that back in.
Now it's not even a staticsystem, like maps are always
static.
They print them, they'd last ahundred years and then you print
them in a book and they'd last ayear.
Now they're truly dynamic.
It's like traffic maps are live,updated from anonymized data,

(30:10):
from how many iPhones areslowing down at this part of the
road, or how many Android phonesare slowing down from this part
of the, road and speed sensorsand cameras watching the road
that are then machine processedto come up with,, flow maps and
current live state maps, andthen directions, route around
the slow parts So.
We've come a long way fromhaving a paper map in the back

(30:32):
of a pickup truck.

Track 1 (30:33):
To keep that, you know, annoying little kid in the back,
entertained on a four hourdrive.
Oh wait, that was me.

rob_1_02-01-2024_100240 (30:38):
So I remember when Google Maps first
came out, well before GoogleMaps, obviously we had, we had
MapQuest and anyone who'sremembers MapQuest in the early
two thousands.
It was great.
It was basically an onlineversion of the older products,
which were like order route,auto map.
they were text-based DOS apps, Ithink made in the UK originally.

(30:59):
you could type an address to anaddress and it was fairly
mundane.
It was technically just like asimple graph.
Solve the graph from A to B, uh,add up the distances as you go,
or add up time or whatever youwanted to solve for.

Track 1 (31:12):
And then print that off and take you

rob_1_02-01-2024_100240 (31:13):
And then.

Track 1 (31:14):
And

rob_1_02-01-2024_100240 (31:14):
Print it off, take up within the car.
And then, but this was like theeighties and this was magical.
When you first got this app, Ithink someone gave me a, uh,
floppy disc with it on or acouple of floppy disks and it
was like, wow, that's amazing.
I can get directions toanywhere.
And all those questions in mymind came to be of like, how did
you update this?
How did they get this?
And it was fairly crude backthen'cause it didn't actually
show you a map.

(31:35):
They just abstracted the conceptof a map into a, like a abstract
graph in computer terms.
And then they solved the A to Bproblem on that graph and they
assigned that back to rows,things like that.
And that's how they got thedirections.
Fairly crude directions.
It would be, wouldn't it bewrong?
It, you would get there, but it,you had little faith like it was

(31:56):
the best route or the fastestroute or the road even existed
anymore.
'cause sometimes it was like, godown this little dirt road.
things like that.
But it was just, that was justthe connection of the digital
data to the real world.
Data in the eighties wasn't verygood.
But then in the two, early twothousands we got.
MapQuest?
Well, probably the latenineties.
Actually.
A MapQuest was great because itwould, show you the map.

(32:19):
It would still give youdirections, and I remember it
would give you a little map, astatic map for each turn that
you had to make.
So when you printed out thedirections, it was like 15 pages
and that was what everyone usedfor.
Everyone would print thedirections for, they left the
house, they wanted thosesmartphones, and it was great.
You've got the actual maps soyou could see what the road
looked like.

(32:40):
And then I remember when I firstsaw Google Maps, my mind was
completely blown because of afew things.
One, you could scroll it withthe mouse, you could just grab
the map and move it.
And I think back then Googlejust used pre-rendered like 64
by 64 tiles, and there wasliterally just a stream of PNGs
coming down to your machine asyou scroll the map around and

(33:03):
they had them all on the serverand they'd update them and
things like that.
Today it's not that way.
They're doing a lot of actualrendering from.
vector type data in the webbrowser, but back then it was
just there.
But the other amazing thing thatGoogle had from day one was
satellite maps.
And I guarantee you the absolutefirst thing everybody did was to
go look at the house from asatellite and view it from high

(33:25):
altitude, view it from lowaltitude.
How close can you get?
Can I see my car in the,driveway?
And then everyone played thegame of trying to guess when
that photo was taken because oflike, oh, I don't have that car
anymore, so this must be a yearold.
And things like

Track 1 (33:39):
cans are out there.
'cause it must have been aWednesday that they took it on
that day.
Yep.
Mm-Hmm.

rob_1_02-01-2024_100240 (33:44):
yeah, ev, ev, everyone played that.
Everyone played that same gamein like 2004 whenever it was,
when Google Maps first appeared.
And of course it could dodirections too, and it would
draw on the map and you couldsee it and you could scroll the
map.
While it had directions on it,it was an absolute game changer.
And then, I guess this was thefirst I.

(34:06):
Consumer facing like mapproduct, as we, as, as we'd
recognize it today, it's, we'drecognize MapQuest is the old
internet where nothing wasinteractive.
Um, I think Google Maps is thefirst one we'd recognize a, a
current map product.
You can see its history.
And I also think then Googlethen took a huge step forward

(34:27):
with street View, where we'relike, let's just go and drive on
every single street and get GPSdata.
And that's the start of the goaltoday of where we'd like to have
a, some sort of 3D app thatshows you exactly what it would
be like to drive that way out.
I'm surprised that there's no VRapps yet that do that.
And.
I think AR has a huge place inmaps too, because if we could

(34:51):
get wearable AR we could use ina car, then we could do things
like markup turns.
I always thought the only grailfor an AR app would be to
literally have something likeGoogle Apple Maps that literally
draws on the road, like followthe yellow brick road, like the
blue line that's drawn on themap, is drawn on the road where
you have to go.

(35:11):
That's incredibly hard to do.
We talked about this in a ARepisode.
lots of understanding of whatyou're looking at.
It becomes an AI renderingproblem, ar problem more than a
maps,

Track 1 (35:22):
so going off of that, the ar part, seeing that yellow
brick road like you werementioning, one place that I see
in, like they said, the GISworld is okay, you have your
directions.
This is again, more on theprofessional side, but if you
were to use your augmentedreality without the issues like
you were mentioning in theepisode of being outdoors and

(35:43):
all of that, but think of forthe road crews being able to
stand on the road and seeexactly where the underground
utilities

rob_1_02-01-2024_100240 (35:53):
Yeah, I think that's all in incredibly,
useful, but I'm surprised evenfor VR that doesn't, exist.
I think we're heading there withthe 3D views in Apple View,
apple Maps, and we have the samein Google and Google do have
some AR component where you canhave the camera and it will
basically point, like, go lefthere.
But it's, it's just icons thatare put on top of the map.

(36:15):
It isn't really like integratedinto this understanding of the
scene that it's looking at.
So we're definitely headingthere and it's just amazing how
far we've come from what weoriginally did for maps.
We print them out.
And today we have this devicethat will just tell you, it's
like, turn here, turn here.
As as you're going along, whatwe don't do anymore is ask for

(36:36):
directions.
Very rarely does somebody askyou for directions anymore.

Track 1 (36:40):
I actually had to do that recently.
I was outta the country and Ididn't have data service, so I
had to do the old ask fordirections, and it felt so
nineties to me.
You know, I could almost hearthe grunge music playing as I
did it.
But yeah, that's just somethingwe just don't do anymore because
we either have it in our cars oron our phone or some way to be

(37:00):
able to find the directions forthat.

rob_1_02-01-2024_100240 (37:02):
So I guess another question we have
today is these maps are now fullecosystems.
They're full platforms and theygather a lot of data about our
movement and our location and.
That's used to fund ads andwhich fund the platform, and is
that ultimately worth what we'regiving up to get what we're

(37:25):
getting back?
I mean, that's a question oftechnology and society as a
whole, but maps are incrediblysensitive due to location.
And you can even like visuallymine map data so easily.
If I know you were at this housethree nights a week and then
here for three nights a week,you can imply a lot about that

(37:45):
just based on static locationdata that you just looking at
with your own eyeballs.
If you start mining this datawith machine learning algorithms
and supercomputers.
The amount of information youcould derive about somebody
solely based on their locationand the time of that location is
ridiculous.
And we know Google already dosome of this because they have

(38:06):
the, your his, your locationhistory, which is kind of like,
well, I went to all these placesand it knows you've been here
before.
And they say some of it isanonymized, but that's more like
the traffic flow data, though.

Track 1 (38:18):
that's what they sell to companies like Esri, because
we get that type of data to liketraffic flow.
one that I use specifically isflow around, subway and rail
stations, is using that data towhich platform for this
particular train is moreutilized from a choice

(38:43):
perspective rather than justgoing to the first one.
So that's one of some of thatanonymized data, but you're,
you're right, that.
It tracks that information Ilooked at my phone the other
day.
We were, it was a last Friday,and my wife and I usually go out
for drinks on a Friday night andI was finishing up work, opened
up my phone.

(39:03):
It's like, oh, are you headed tothis location at, uh, for, I
mean, it knew where we go at acertain time and probably knows
exactly what we're doing therebecause it has the, the business
information.
So it knows that I go to thesame place every Friday for
drinks.
So, and you're spot on.
I'm sure the, the tech companiesare gathering that information

(39:27):
and helping sell ads for me

rob_1_02-01-2024_100240 (39:29):
Yeah, absolutely.
It's probably not gonna give youthe ad'cause it knows you go
there, but it's gonna givesomeone like you the ad because
it wants, yeah.

Track 1 (39:37):
cause you know, we, I go to the same place as a lot of

rob_1_02-01-2024_100240 (39:40):
But I don't think they sell that
information.
I think that information thatthey have privately on you, I
don't believe, I don't believethey sell it as is.
They may anonymize it and sellit in other ways, but I don't
think they sell.
This is PJ's information.
This is where we went.
But then there's a question oflaw enforcement and subpoenas
and all of that at the back end,which is also an a very
interesting thing.

(40:01):
And just the amount ofinformation that they have based
on literally you were here atthis time

pj_1_02-01-2024_100239 (40:06):
so Rob, I think you brought up a really
good.
sphere here in terms of theconsumer space and it's really
interesting to see, Google andApple able to make these changes
because they have consumerclients.
Corey, the idea that theenterprise slash professional
space with these municipalitieswhere it's, this is, you're
going back to this as anauthority to whatever you can

(40:29):
speak of.
What are some of the major usecases that you're seeing for new
avenues for the municipal space,that enterprise and professional
space?
So, like Esri obviously is, isoccupying something different
than a B2C?
Obviously there may be some B2Ccomponents in there, but like

(40:49):
can you talk us through a littlebit about where the latest,
greatest sort of advances inavenues are happening for
municipalities or for, you know,the clients you guys typically
say.

Track 1 (40:59):
So we've already kind of talked about a little bit
this topology.
If everything's connected, youknow, there's a way that traffic
is connected to how I do myday-to-Day job or so on.
One of those that we're seeing amajor growth in not only
municipalities, but stategovernments.
the customers that I workspecifically in public transit

(41:19):
of real time tracking ofvehicles or.
Anything that you need to trackand analytics done in real time?
Lemme give an example again, myspecialty is public transit, so
taking where that bus is, andone of the things that every
transit agency has to report tothe federal government is what

(41:41):
is the on time percentage ofthat bus?
So across the system, we're at85% on time and so many minutes
late or so on, but how do youtrack that?
Before it was the bus wouldgather its information, on its
on the bus itself, and get backto the bus yard, download that

(42:02):
data, it would be processed andhelp with your on time
performance.
Tracking these new technologiesof being able to stream the bus
locations of being able to seethat, map of the bus's movie.
Now with this real time, notjust tracking, but analytics, I
have the ability to take wherethat bus is, compare it to the

(42:23):
schedule that this bus should beat, this location at this time,
do the analytics and give me anumber in near real time.
We're talking 15 seconds andbeing able to track that over
time.
So that's one that we're seeinga lot of use for that.
Another good example isespecially in cold weather

(42:44):
climates tracking where thesnowplows are, being able to see
where every snowplow is in thestate of Colorado and see where
they've plowed, not only wherethey plowed, but what materials
they've put down and showingthat to the public in a way
that, okay.

(43:04):
yeah, we just had a big snowfallof, you know, 18 inches,
whatever it might be, and you'reneeding to get out of your
neighborhood.
Well, the snowplow is scheduledto be there today, and it's six
blocks away and it's putting,whether it's gravel or salt down
or whatever to help with that.
But that's being able to trackthose kind of locations in real

(43:25):
time.
So that's one thing that we areseeing a lot of use for, and
it's growing.
I talked about vehicle tracking,so snow plows, buses, I've
worked with a customer who usethat for the collars they put on
wildlife.
So the example I want to givefor that is salt Lake City
Airport.
You know, there's the Great SaltLake right next to the airport,

(43:48):
but they also have a good amountof pelicans in that lake.
I wouldn't think so, but theyare.
In fact, I here in the summerhere in Colorado, I see pelicans
in the lakes around here.
But those pelicans can cause adisruption to the traffic coming
out of the Salt Lake airport.

(44:09):
So they actually, the Departmentof Wildlife put trackers on
these pelicans so they can seewhich way that the pelicans are
flying and direct traffic ofthe, airlines to avoid the
pelicans to avoid bird strikes.
'cause you know, we saw whathappened in there in the Hudson,
in, uh, in New York, I can'tremember how many years ago,

(44:29):
where they had a bird strike andhad the plane flew into the
Hudson.
So these are examples of usingthat real time analytics.
I mean, tracking a bird.
We got 50 birds outside theairport, seeing where they are.
Okay, we need to make sure theplanes go the other direction.
That's tracking and analyticshappening as.

(44:50):
The situation happens.
So that's a big one that we'reseeing with that.

rob_1_02-01-2024_100240 (44:53):
So going back to the real time data
you get from people like Google,is that truly real time?

Track 1 (44:59):
From Google?
Well, it depends on the source.
Like the ones that I work in,uh, especially in transit, we're
getting them within five to 10seconds after the device is, is
ped,

rob_1_02-01-2024_100240 (45:11):
so, are you getting that from like
Google doing, its anonymizedAndroid tracking, or are you
getting it from the variouslittle RFID type antennas that
has placed along the freeways orradar sensors?

Track 1 (45:28):
so are we talking Traffic

rob_1_02-01-2024_100240 (45:31):
Traffic flow?
I'm thinking about like where'sthe where's the bottlenecks and
why is this bit here slowingdown?

Track 1 (45:37):
that's the anonymized data that we would get for those
that I, I actually utilize in mytransit models to show that at a
certain time of day, the trafficslows down at this location.
And we can see the impact itdoes on the schedule.
The other ones that I see, likeI mentioned, the utilization of
tracking the phones, that's alsoan anonymized, you know, which

(45:59):
part of the rail station arethey going to or anything like
that.
That's the anonymized, we don'tget anything specific, but there
is a push in.
Uh, that was going to be thenext part that I talk about of
where we seeing this going isnot just outdoor mapping, indoor
mapping, so utilizing, thevarious indoor positioning

(46:21):
systems or IPS A good examplethat we use for this is, a
convention center.
So you've got a huge conventioncenter, say like San Diego, one
of the biggest ones that, thatwas utilized.
Being able to put these indoorpositioning trackers is think,
okay, I'm going, I want to go toa session in room B 15.
Where is that at and how do Iget there?

(46:41):
So the same thing of indoorrouting, not just along the
streets, but actually routingyou within a building is
something we're seeing a lot ofuse at in convention centers.
Airports is another one ofhelping people get from one part
of the airport to another.
I was just in Houston and thatairport, you know, I was going

(47:03):
from one terminal to another andtrying to get through there.
And the amount of time that Ihad from make my transfer was
crazy.
But that's this thing of, wethink of maps as the whole wide
world right outside our window,but really it can be indoors
too.
I mentioned airports, conventioncenters, hospitals is another

(47:24):
one.
a.
Good utilization that some localmunicipalities are doing is fire
departments utilizing thisindoor mapping to help with the
evacuation of a building or ifthey're searching for it.
Police departments can use thistoo, to, alright, we're having
to clear a building because of apolice situation.

(47:45):
Where are the little cubbies andHeidi playing that we would need
to be able to look out for anykind of thing?
So mapping isn't just, like Isaid, not just the world.
It's also indoors that we'rereally seeing a lot of, growth

rob_1_02-01-2024_100240 (47:59):
What is the technology behind those
indoors?
I assume it's just like static.
Known position, some sort ofnode, which is wifi, Bluetooth,
ultra wideband, whatevertechnology it may have, but it
has to be something that yourphone has'cause there's no

Track 1 (48:15):
correct,

rob_1_02-01-2024_100240 (48:16):
for this.

Track 1 (48:17):
yes.
The tools that we're puttingtogether utilize those indoor
positioning systems.
And with those nodes throughoutthe building themselves, it
doubles as the GPS that youwould use outdoors.
And so you can actually get veryaccurate information.
At my company's headquarters inCalifornia, if I wanted to say
I've got an issue at a certainroom, we've mapped all those out

(48:40):
to where I can have the, ITpeople come in and know exactly
what projector is having anissue.
Because you have the indoorlocation, you have your assets
in there, you can actually gothrough and make a digital twin
of your entire building.

pj_1_02-01-2024_100239 (48:56):
This is pretty awesome actually.
and you got under the edgereally of where I wanted to go
next, which is, okay.
So indoor mapping looks likethis.
Giant frontier.
That is, we're on the verge offor maps.
What are some of the otherexciting areas that, you know,
your work maps, where's thisstuff going?

Track 1 (49:13):
I think, one of the big one is AI or machine learning.
We're seeing that in a lot ofspaces.
given example of that is acolleague of mine built a model.
He works specifically withcommercial railroads, so you
know, union Pacific, BNSF and soon.
But they came to him with aproblem of, okay, we need to

(49:36):
track, how many types of railcars are leaving a port or a
depot or whatever like that.
So he built a machine learningmodel that watched a video feed.
And actually it's like, okay, asthis train goes by, that's a
rail, that's a, container car.
That's a.

(49:56):
one for liquids or, and thatsort of for cars.
So it actually gave the trainlocation and the time and
actually counted the types ofcars through there.
So, the machine learning canutilize so many different things
like that.
We'd already talked about imagedetection.
You know, that was one thingthat you brought up, Rob, was
being able to find where thoseroads are not, in the right

(50:17):
location.
An example that I've helped acustomer with was actually oil
wells in, the Permian Basin, youknow, New Mexico and all those
to where the, regulatory agencywas using that, these change
detection.
I had used that phrase earlier,okay.
These satellites are going overdaily, maybe every other day, to

(50:40):
where they were using thatdetection to locate drilling
without permits.
So it was actually a revenuemaker for the, state itself
because it was able to say, allright, you say we've got a
permit for a well at thislocation, but from the aerial
imagery, we're able to see thatyou're also drilling here at

(51:02):
this other location.
One of the biggest ones thenthis came, first, came out, is
also, um, around swimming pools.
And I know that sounds, why dowe need to look at swimming
pools?
Well, in Southern California,they had a lot of problems with,
green swimming pools or poolsthat weren't maintained.
But if you think of how manypools are within Southern

(51:24):
California could take, allright, let's zoom into each
house and check those.
Now with this machine learningand this ai.
It scans the entirety of theaerial images you train to say,
this is what a green pool lookslike.
All right there, you know, givesyou the list, the addresses, and
all the owners of these poolsthat are not being maintained

(51:47):
for, you know, that could havemosquitoes or West Nile virus or
anything like that.
So that's really where anotherone of those uses of machine
learning and AI come in.
Helpful.

rob_1_02-01-2024_100240 (51:58):
This sounds to me like a somewhat of
a dystopian future.
It's like, I mean, how, and thisis way off the subject of tech,
but how far can municipalitiesgo with this?
I mean, if you put a shed up andthey go, oh, you built a shed
without, telling us we found itby aerial imagery.
It's like, where's, where's theline as to what they can.

(52:19):
And force based on thistechnology.
I, I think that's somethingthat's gonna be up for debate in
the future when machines arelooking for things that they can
look for instantly that wouldtake people years to do.

Track 1 (52:31):
Your point is valid of when, what is the ramifications?
Okay.
What are they gonna look fornext?
Because of this ability to havethese images of my backyard, of
your backyard, of where everyoneelse's.
And how does that play intoregulatory surfaces?

rob_1_02-01-2024_10 (52:48):
Absolutely, because I mean, you can say to
Google like, this is privateproperty.
I don't want you to look at it.
And they'll, they'll honor yourrequest and they'll fool you
outta street view and thingslike that.
Why do, why is the municipalityallowed to do it wholesale,
regardless of whether you wantit to be private or if you
don't?

pj_1_02-01-2024_100239 (53:07):
Rob, I think this is why we moved to
places with lots of trees.
Unless Corey's gonna tell us,basically we, they've got some
other, you know, penetratingradar that could be used to, get
through that.

Track 1 (53:19):
There is, with lidar, you can actually remove the.
Foliage.
So if you wanted to see likeunderneath the trees, there's
certain types of lidar and radarremote sensing is what we call
it to where you can actuallytake that ground cover and be
able to see that.

(53:39):
I, I don't want to make, youknow, you're gonna move now.
PGII realize that, but,

pj_1_02-01-2024_100239 (53:43):
No, no, no.
I just, it just justifies nowcovering everything in aluminum
foil, uh, to bounce back thelidar.
It's, you know, it's fine.

rob_1_02-01-2024_100240 (53:50):
Yeah, it's, it's very interesting have
all of this, all of thesedisjoint technologies all feed
back into one big database of,like you said, where, and you
factor in.
This with like topology andeverything else that these
databases have, and we end upwith a pretty interesting map of

(54:11):
the world that we've built ontop of the world that was
already there.

Track 1 (54:14):
That where?
Component that wear variable youcould go on for days.
Tracking all the little nuancesof our lives to that wear.

pj_1_02-01-2024_100239 (54:25):
Even with all of this data and
technologies, it goes back to areally interesting point you
made really early on in this, isthat there's still some human I.
That can draw arbitrary linesthrough neighborhoods to tell a
different story.
but It seems fascinating thatthere's still this arbitrariness
that Im like, impacts all ofthis objective

Track 1 (54:49):
Mm-Hmm.
I wouldn't be surprised if itutilizes AI for those kind of
things now, but I would hopethat there's always a check and
balance put into that.
Being able to have a impartialview.
I, I know I'm reaching here forthe stars, but hopefully to this
ability to always have animpartial view of it, but the

(55:12):
world is how it's

pj_1_02-01-2024_100239 (55:13):
Any, other thoughts in terms of where
things are going from atechnological standpoint?
Are there any bits oftechnology?
I mean, we, we just talkedabout, I mean, obviously
satellite data as imagery,layering in lidar.
What else is on the forefronthere in terms of how we improve
maps

Track 1 (55:33):
So one that I am,

pj_1_02-01-2024_100239 (55:35):
that you can talk about?

Track 1 (55:36):
I could talk about, well, there's one that I'm
hopeful I would love to see ittake off.
I, I am a little cautious on it,is utilizing game engines where,
where I'm going with this istake a forest fire perhaps, but
you want to be able to see whatit's like on the ground there.

(55:58):
But you have all this great dataand authoritative and accurate
data, but you like the episodesthat you had on AR and VR
managing to be able to put onsome goggles and actually see
what's happening on the groundwith a forest fire in virtual
reality, but utilizing realdata.

(56:21):
I think that's one that's has alot of potential.
I've seen something similar tothis with, we call it bim or
Building Information Model.
So this is like the 3D buildingswe had talked about, a little
bit earlier, but being able toutilize and stand in a building
that hasn't been built yet invirtual reality, that's one that

(56:42):
I see.
But also in places that, maybewe don't have access to or for
safety reasons, like a forestfire.
Being able to see the extent ofit, what it's looking like at a,
in a location that you can'tvisit.
Being able to take the personwho would be seeing the 2D map,
take them to that location, showthem real data, but within a

(57:04):
game engine, you know, unreal orwhatever it might be, to really
take that immersiveness oftaking the data, you know, your
maps.
I I don't want to call it fourD, but whatever.
But you have your 3D maps.
Let's take it to another level.
And I think that's where thispossibility of utilizing game
engines can go as well.

pj_1_02-01-2024_100239 (57:24):
Do we have the data to do that today?

Track 1 (57:26):
That example of a forest fire, I have seen a
demonstration of it.
We have the topography.
We have the elevationinformation.
Let's say that there's buildingsthere.
We have the footprints.
One of the things that I did alot of work on, especially for
my, graduate degree, was forestfire data.
We have satellites could tellyou the exact temperature, how

(57:46):
intense that the fire is burningfrom satellite data.
So you can actually combine allthose two, all those together
and put it in a, in a virtualreality view and see what it's
like to be in a forest fire.
Or wherever you're needing togo.
So really, we have the data todo it.

(58:07):
It's just combining it into amedium and a platform that we
can see it all together.

pj_1_02-01-2024_100239 (58:12):
Rob, maybe we should make that one of
our next projects.

rob_1_02-01-2024_1002 (58:15):
Something there for sure.
But that would be great for thepeople.
Like say it's like the, thefirefighters and all that.
I think the AR wanted be evenbetter'cause they could look at
the real world and see it markedup.
But I think we're a long wayfrom the.

pj_1_02-01-2024_100239 (58:28):
well, Corey, this has been amazing.
thank you so much for coming on.
I know we've only just scratchedthe surface on so much of this
stuff, so I think we'd love tohave you back on and do like
some deeper dives into a lot ofthe, I mean, we covered a lot of
ground here from the past to thecurrent state of things, indoor

(58:49):
mapping potentials for thefuture.
So we would love to deep dive alittle bit more on any of those
things and also any of the newand exciting things that are yet
to come in maps.

Track 1 (58:59):
Well, thank you both so much for having me on here and
as a map nerd.
And I say that with pride isthat I, from the kids sitting in
the back reading the Ran McNallyto today, being able to think of
maps in a game engine andindoors and all of this I'm
happy to talk about this anytime

rob_1_02-01-2024_10024 (59:19):
Awesome.
Thank you for coming on, Corey.
That was a great conversation.