The future of GEOINT

MARK KNAPP
You sure people will tell you or machines will tell you something much quicker than a person can, but there’s the ability of a human brain to really contextualize something, attribute pieces that maybe just aren’t in the data stack, and that’s going to be a high risk to take that element out.

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JEFF PHILLIPS
Welcome to NeedleStack, the podcast for professional online research. I’m Jeff Phillips, your host. Joining me as co host today is Tom Kay. Now, Tom’s a program manager at Authenticate with more than 25 years of geospatial experience. Thanks for being here and being a co host, Tom.

THOM KAYE
Hello, Jeff.

JEFF PHILLIPS
And also joining both Tom and I is Mark Knapp. Mark is the CEO of Terra Cover, and Mark joins us today to discuss all things geo in. Mark, welcome to the show for you also.

MARK KNAPP
Thanks, Jeff. Great to be here.

JEFF PHILLIPS
All right, I’m excited for today’s session with both of you. Let’s start at the top, if you will, or with the basics. Mark and then Tom, if you want to chime in. Also, can you tell us what is GEOINT for some of our listeners that may not know? And how does it differ from other intelligence disciplines?

MARK KNAPP
Yeah. Great question, Jeff. Geospatial intelligence, or GEOINT for short. There are many different ways to define it. There’s been books written about it. I like to just break it down and make it as simple as possible. Geospatial intelligence is any information that can either be spatially referenced somewhere on the planet or time referenced somewhere on the planet. And when you have the combination of the two, then you’re talking about something really powerful. And if you think of geoints relative to other sources of information or INTs, again, this is electromagnetic spectrum visual. A lot of radio frequency pieces and also bands of light that we can’t see, but a lot of sensors can that can be distinct relative to other things like human intelligence and signals intelligence, which certainly operate in different domains.

THOM KAYE
And Mark, would you say that your specialty is more focused on imminent, which is essentially a sub discipline of GEOINT?

MARK KNAPP
Yeah, I would like to think that I’ve learned how to interpret these sensors, kind of push them as far as you can. But taking a step back, I really like to consider myself a space junkie, someone who looks at the whole threshold of what’s going on from spacecraft manufacture, launch communications, and then finally you have a sensor with data that’s coming down to Earth and making sense of that data. The imagery piece is something I certainly pride myself in.

THOM KAYE
So, Jeff, I don’t know if you knew this, but Mark and I, we go back many years, and we used to work on several programs together. One of the coolest programs that we worked on together was for a national security customer to monitor world events. And I remember I don’t remember the exact date escapes me, but it was when the Turkey presidential election was going on, I believe it was erdogan was reelected and there was a lot of protests. I was tasked with monitoring that event and I captured a lot of social media for that event and we noticed a lot of protests going on and with most things that happen within that realm, you have to corroborate events. And we were unable to corroborate this event from the social media that we captured. But Mark came up with this real ingenious way of making sure that we could prove that this protest was actually happening. And Mark, could you please expand upon that particular event?

MARK KNAPP
Well, we’re certainly taking a stroll down memory lane there, Tom, but it was an interesting time that national security partner was keen to understanding what was going on and using open sources of information to figure out those answers. You had clued into some really, I think, impactful messages that we saw in the social media world and we wanted to kind of verify or at least corroborate with another source. And one of those sources that we thought would be at our disposal was Earth observation or satellite imagery. And so we looked at what had been available over that area of interest recently. And unfortunately, at the time stamps that we had on the social media feeds, we didn’t have directly correlating imagery, the coverage wasn’t there, but we did have imagery before and after the event or the alleged event took place. So that’s something that when you compare those two images, two different points of time, you can do change detection in the regular spectrum of light, what we see visually there wasn’t anything all that unusual. I think it was like a park area that we were looking at. But so we started to look elsewhere in the electromagnetic spectrum and specifically the near infrared band and then doing an index based off of that, which is normalized difference vegetation index or NDVI for short.

MARK KNAPP
And you basically are looking at the chlorophyll or at least the health of vegetation with that near infrared band. And so we saw before image, we saw an afterimage and when we did the comparison NDVI, there was a real degradation in the grass in this park. And so we thought, well, that kind of adds up. I mean, if you have thousands of people present here walking back and forth, that’s probably going to hurt the grass. But we can’t just say with this standalone comparison of one site that that’s what happened. And it’s empirical we know that the vegetation is less healthy after than it was before. So we actually picked some other control points a handful of kilometers away. Also open parklands where there was grass and vegetation present. We looked at the before and after and there wasn’t a major change, I guess, in the health of those areas, their vegetation anyways. And that then created the anomaly at that park. And again, being able to corroborate that back to the social media that you had identified. We suddenly had more context. We had a story that we could tell.

THOM KAYE
Yeah, that was a really great memory. I think it was if I can recall, it was Periscope. I don’t even know if Periscope is around anymore. I think they were like part of Twitter. People used to make live videos on periscope. But yeah, that’s a great memory. It was good stuff.

JEFF PHILLIPS
Well, for someone like me. When I think of Mark, you were talking about a lot of different technologies that make up geospatial intelligence and that whole space. Again, I think of satellites, I think of pictures to think of something like you just discussed, which is able to tell differences in chloroform. I didn’t know that technology existed.

THOM KAYE
Chlorophyll.

JEFF PHILLIPS
Chlorophyll. Not chloroform. Good lord. Shouldn’t give anyone chloroform.

THOM KAYE
Don’t want to get canceled.

JEFF PHILLIPS
No chlorophyll. But that was even a technology that’s available.

MARK KNAPP
Yeah, rightly. So that’s one of the challenges, I guess, when you start thinking about imagery intelligence and geospatial intelligence and how it gets processed, at least how it’s been done up to this point. There’s some pretty high end tools and software that gets employed and not everyone is comfortable doing that. And so you’re kind of limiting the scope of people who can actually take this and make sense of it. And that’s something that we’re hoping changes as time goes by.

JEFF PHILLIPS
And what do you think about? I would think that that might open it up. Sorry. This shows about professional online research. We have a lot of people doing intelligence and evidence gathering, but it would seem that maybe other industries can benefit from GEOINT as we go into the future. Would that make sense?

MARK KNAPP
Yes, and that’s something I am quite passionate about. National security partners and customers have basically kept the geospatial intelligence industry moving along here for a number of decades. To this day, the US government is the largest consumer of geospatial intelligence that’s produced in commercial venues in the world. And that probably won’t change anytime soon, but it’s important for the industry as a whole to kind of basically diversify its dependence on one or two customers and so tapping into some of the other industries out there that can benefit from it. And what we were just describing here, using the near infrared band and the NDVI index to look at plant health, I mean, that has dramatic implications. What can be done for agriculture and commodities and predicting what’s happening and going to happen going forward.

THOM KAYE
What about in terms of natural disasters, things of that nature? How does GEOINT help in, I guess, resolving or bringing light to natural disasters and helping people after these events?

MARK KNAPP
It GEOINT has played a critical role in supporting first responders, I guess getting people informed as these hazards and events are happening literally anywhere in the world within minutes. You can have a satellite overhead task. It image what’s down there. What comes to mind? Fortunately, Lebanon, a handful of years ago, right at the port, there was a major explosion and end of the day it turned out it was fertilizer stored, not in a safe condition, and whatever happened, it blew up and the shockwave was immense and buildings were destroyed for many hundreds of meters around. Getting a sense of what the extent of all that was, understanding who was impacted, the populations and where to start placing people who are going to come in and do some good work. Hopefully a lot of that was driven by geospatial intelligence. It was obvious that the cone of explosion was here and so people that needed to help should be here, here, and here. And then you can start to draw on other capabilities and resources to refine that impact. There’s so many examples where you can talk about natural disasters, from earthquakes to fires. Australia, it seems every year you get to see satellite images of just huge areas being consumed by fire and it’s just tragic.

MARK KNAPP
And again, scoping that and seeing it in real time. Geospatial intelligence has very few peers. I can’t think of another way to do it as efficiently as geospatial intelligence does.

THOM KAYE
Yeah, I remember that event very well. And another GEOINT aspect a lot of people probably don’t think about is terrestrial imagery. I mean, if you think about that event, there was a lot of it that was captured through social media, which people had filmed and uploaded. And if you geolocate that, it’s essentially spatially referenced and temporarily referenced. So you could use that to help zero in on exactly where the people needed their support as well. So, speaking of which, in terms of open source intelligence and GEOINT infusing them together, give me a sense of what is publicly available. Like we could talk a little bit about Lansat, right, obviously a government funded, remote sensed earth observation satellite and then talk a little bit about what’s available for commercially available information. The Black Skies and other organizations like that.

MARK KNAPP
Yeah, these different sources of satellite imagery or GEOINT, you do have systems that have been on orbit in some way, shape or form for decades, such as Landsat, and it’s proved critical again to do some change detection. I mean, think of like high latitude polar regions and seeing the ice melt and assessing what did it look like in 1984, what does it look like in 2014, what does it look like today? You can see those events over time and again. I like to say the imagery doesn’t lie. There are certainly occasions when you get curveballs thrown at you, but when you see something at that scale happening over decades from space, it can be very impactful. So, yeah, the major constellations that are out there available publicly include Landsat, which is owned and operated by the US government. European Space Agency has a constellation of satellites called Sentinel, and they include both optical synthetic aperture radar and then some other multispectral sensors, and they run the gamut. You again talk about the electromagnetic spectrum. We’re seeing more and more and more of that spectrum covered by publicly available imaging systems. And then another important contributor to that publicly available information include the likes of JAXA or the Japanese space agency, with assets that have been basically put up in tandem to complement what both the US.

MARK KNAPP
And Europe are doing. And there are other nation states such as Brazil and India and China that have constellations that are out and available data qualities are not always consistent from platform to platform, but if you stay within a single platform over the years, it should be relatively good to do your compare and contrast and your change detection there. All that has really, I think, fostered an ecosystem of analysis and people who are energized by having access to this data from space, where there was enough energy, I guess, to justify a commercial service. And then you saw in the 1990s that really start to crescendo up here in the US. As well as Europe, commercial sensors taking orbit. Primarily in the early days it was optical, but you had some synthetic aperture radar systems, most notably from Canada, and then as the years ensued, so now we’re early 2000s, mid 2000s. You had a couple of organizations in the US. That were really kind of charging ahead, and that would have been digital globe and GoI. Again, not far behind them was Airbus in Europe. And the US government was certainly making its presence known.

MARK KNAPP
Large multi year contracts in the hundreds of millions of dollars. And that was enough to really kind of plant the seeds and then water it and see this industry grow. Things got tremendously exciting here probably within about the last decade, when the size of the satellites was really brought down. So you suddenly had micro satellites, nano satellites, satellites that are roughly the size of a dorm refrigerator, even down to the size of a loaf of bread now. And they’re, they’re still quite capable. You know, the, the components and hardware that you had to have on, on your satellite back in 1990 are very different than what you need to have in 2023. And it’s been an explosion. I mean, it’s an exponential increase in the volume of data. The number of Earth observation satellites, it continues to go up literally every month. And we’re a really, I think, important point of inflection for the GEOINT industry and those commercially available sources that I was telling you, again, back to the company is kind of moving along, competing. It’s mushroomed. You now have many others, the planets, the black skies, the Capellas, the umbras I don’t want to leave anyone out, but I have to, because the list would go on and on.

MARK KNAPP
And you also see different nation states getting involved at this point. So the US is still I’d say very much. I don’t want to say in the lead, but moving forward with others, trying to keep up and yeah, that volume of data creates a new challenge for everyone, in fact, that there just aren’t enough eyeballs to look at all the imagery every day. And so you need to start automating and leveraging things like machine learning and artificial intelligence so you can scale analysis to the point where you’re driving insights rapidly and quickly and leaving no pixel left behind.

JEFF PHILLIPS
One thing you both have mentioned a couple of times, I think you’ve referred to optical versus synthetic aperture types of what’s the difference between those two, or what are they? Let’s start with what are they? And then how do they differ?

MARK KNAPP
Yeah, no, Jeff, that’s great to kind of focus on that a bit. So we’ve referenced electromagnetic spectrum, and within that there’s a tiny sliver which is visible light. That’s what we can all see. And so when we have our phones on our cameras and whatnot we take pictures, that’s what we’re looking at, that spectrum of light. And so a lot of imaging systems certainly cover those bands of light. And when the images come down from space and we look at them, it’s all very normal and natural looking in many cases. But there’s other bands of light that aren’t visible to our naked eye. And so if you have a sensor that can kind of interpret it, see it, that is very helpful. And now you’re suddenly branching out. And there are signatures that you can see in different bands of light relative to one another. Synthetic aperture radar is also part of the electromagnetic spectrum. It’s SAR for short. And that’s a sensor that is active in that there’s energy that it’s beaming down from the sensor to a surface on the Earth and then it’s being reflected back up. All this happens at the speed of light because it’s in the electromagnetic spectrum, but it’s a radio frequency.

MARK KNAPP
And when that data comes back, a lot of math happens behind the scenes. But basically you get a 3D rendering of what’s on the Earth, the surface of the Earth at any given point. So you can see objects and hills and terrain. If you look at the image, you may be like, that’s not very interesting. But it really is quite interesting when you’re a geoant enthusiast, because the amount of data that’s behind the scenes is telling you a lot.

THOM KAYE
One of the things that I appreciated about SAR is that since it is an active sensor, it can be used at night. A lot of our adversaries will typically recognize that our electro optical imagery is flown between ten and two. So they tend to keep their activities in the late afternoons or in the evenings. But using radar, we can easily see those activities as well as being an all weather sensor. So specifically in the equatorial bands of the world, where the cloud cover is almost persistent. You could use radar imagery, and it can penetrate that, and you can see objects on the ground.

JEFF PHILLIPS
We were talking about some different industries and all this technology that’s up in space now. Mark, can you tell us a little bit about your work now at Terra Cover and what you’re doing there and what the company is all about?

MARK KNAPP
Yeah, Terra Cover is really a cool company. We spun it out from the University of Minnesota a handful of years ago. And I’m not a product of the university. I’m just a friend of the university, but my co founder is a product of the university. So we effectively now have an umbilical cord back to the university, and resources are available to us for a number of different initiatives. But our focus is generating what we term water intelligence. So freshwater resources think lakes, rivers, reservoirs, and the use cases are literally endless. Water is so important to so many different facets of life and industry and whatnot. So we’re in the early stages but certainly getting some good traction and headway, and we’re very optimistic about what the future holds.

THOM KAYE
I want to talk a little bit more about some of the changing technology that’s coming our way. We talked a little bit about SAR. Big fan of it. MSI from Multispectral I’m starting to see a lot more hyperspectral discussions in the past few months. Specifically, I saw the National Reconnaissance Office just kicked off a new campaign or a program with some of the commercial satellite providers to procure hyperspectral imagery. Why should we care what is hyperspectral imagery and what are some of the applications?

MARK KNAPP
Yeah, so hyperspectral, if we just break the term down, you’re looking at the electromagnetic spectrum, but at a hyper scale, like you’re looking at hundreds or thousands of bands simultaneously. So you have to have a great sensor to do that. And the data behind it that you’re actually pulling onto your spacecraft is significant. And that I don’t want to say has well, I will say it. It slowed the ability of that industry to just say the hyperspectral commercial world, space imaging world, to move as quickly as some people would like because of those data volumes. But where we’re at today, the new infrastructures that are emerging for communicating with your satellite, once you have the data on the ground, how it gets processed and analyzed, a lot of the automation that’s out there now is allowing us to really get our hands around a hyperspectral data cube is what it comes down to. It’s more than an image. It’s literally like hundreds or thousands of images each time. The sensor is capturing all of that light, and you start imagining what pull the thread here. What does that mean? What is the use case? If you can have a signature for a particular type of material or chemical on the surface of the Earth in a certain band of light or light bands of light.

MARK KNAPP
It has that signature and it can be nothing else like it’s. So empirical and irrefutable. And now you put that on a spaceborne sensor and you’re able to detect these objects with that high level of confidence. It’s truly a game changer. We could run for hours thinking of the possibilities here and how that’s going to be used and leveraged, but it’s really, I’d say, wise of the US government to be supporting those commercial operators who are getting these hyperspectral sensors on orbit.

THOM KAYE
I’m a little nervous because as a classically trained cartographer who my photo interpretation skills could essentially be replaced by a hyperspectral image who could identify virtually everything on the ground. And that means that all of the foundational geography could be captured through AI. Is that unheard of, do you think?

MARK KNAPP
No. There are certainly large features and objects on the Earth that are often manually derived by analysts sitting at a computer looking at an image, making their best assessment that this is what I’m looking at in that, again, optical image, the bands of light that are visible to us. And now when you suddenly throw this added information in there, that again, it becomes irrefutable that that is what that object is. I don’t know that it’s going to blow all those analysts to the side and be its own entity going forward. I think it’ll be quite complementary. Those individuals who have been practicing this trade craft for a number of years, they’ll just have another tool in their tool belt.

THOM KAYE
There you go. What do you think about this human and machine teaming concept? And do you think that plays a role in the future?

MARK KNAPP
Yeah, Tom, I’m glad you asked that question, because human machine teaming, it’s at the core of everything we’re doing at Terra Cover, and it needs to be at the core of anyone who’s embracing artificial intelligence or machine learning. When applying that to, say, Geospatial intelligence or GEOINT. Once you take a person out, sure, people will tell you or machines will tell you something much quicker than a person can. But there’s the ability of a human brain to really contextualize something, attribute pieces that maybe just aren’t in the data stack. And that’s going to be a high risk to take that element out. So human machine teaming HMT is critical going forward. And if you go back through history I love my history studies, Medieval ages, and I kind of use this as a metaphor of where Earth observation is today and where it could go. Middle Ages, not many people could read or write. People were illiterate as a whole. Those that did have the ability to read and write, typically, at least in the western Occidental world, were part of the church. And so, you know, all the written scriptures interpreting that and telling, you know, the populace, this is what you should and shouldn’t be doing.

MARK KNAPP
That that gave an added edge, you know, more power, so to speak, to to those who could read and write. That’s kind of where we’re at today with earth observation. You have all of this data out there, and it’s going up exponentially as more satellites take orbit, there’s just not enough people to really interpret it and understand it. So the GEOINT literacy rate is very low when you look at humanity across the board. And that’s a problem, potentially. And so being able to automate workflows and scale out things that people are doing day in and day out, I think it increases awareness and gives other people who are maybe not GEOINT savvy, GEOINT literate, the ability to tap in and use this data. And that at the core again, fundamentally, it’s human machine teaming, facilitating that going forward that’s really important for this industry and for national security partners included to recognize that.

THOM KAYE
Well said. Well said. Thanks for a trip down memory lane, man. I really missed these conversations. For sure.

MARK KNAPP
Yeah, pleasure right here as well, Tom. Thanks.

JEFF PHILLIPS
Thanks to our guest, Mark Knapp for joining us today, as well as my co host, Tom Kay. If you like what you heard, you can view transcripts and other episode info on our website, authentic8.com/needlestack. That’s authentic with number eight .com/needlestack. And be sure to let us know what you thought of the show on twitter @needlestackpod and to like and subscribe wherever you’re listening today. We’ll be back next week with more GEOINT.