Episode Transcript
[00:00:02] Speaker A: When we get into Lisco, we have an opportunity to focus our assets based on what we know the terrain will allow them to do.
The Russians make very good maps, very detailed maps, but the question is, will they be willing to give this level of information at the lowest level?
[00:00:19] Speaker B: This is the Convergence the Army's Mad Scientist Podcast I'm Matt Sanisper, Deputy Director of Mad Scientists, and I'll be joined in just a moment by our MadSci intern, Aldrin Yaszko. Mad Scientist is a U.S. army initiative that continually explores the evolution of warfare, challenges assumptions, and collaborates with academia, industry and government. You can connect with us on social media, ME madsci and don't forget to subscribe to the blog the Mad Scientist Laboratory at madsci Blog Tradoc Army MIL on today's episode, we're talking with Jason Fesser, army veteran and branch Chief for the Data and Generation Production Branch in the Warfighter Support Division of the Army Geospatial Center. Will be talking with Jason about the Army Geospatial center, the role emerging and advanced technology plays, and the capabilities of our most important adversaries.
As always, the views expressed in this podcast do not necessarily reflect those of the Department of Defense, Department of the Army, Army Futures Command, or the Training and Doctrine Command.
Let's get started.
[00:01:16] Speaker C: Jason, thanks so much for being on the show.
[00:01:18] Speaker A: Hey, I'm happy to be here. Longtime fan of the podcast and I'm excited to be a part of the community.
[00:01:25] Speaker C: Awesome. Well, we're excited to have you here. So before we get started talking about the big topic today, why don't you you tell us a little bit about yourself, your background, and then how you got to where you are today.
[00:01:33] Speaker A: My name is Jason Fesser. I'm a branch chief at the Army Geospatial center as opposed to my background and how I got here. Two completely different things, but I'll address them both.
I enlisted in the army back in 1992, right out of high school at age 17, and have been a geospatial engineer since 1994. I've been assigned to multiple heavy divisions, 2nd Infantry Division, 3rd Infantry Division, 1st Infantry Division as a terrain analyst, MOS 81, Quebec before we transition much later to the geospatial titles. I've been assigned to the Army Geospatial center and then had the good fortune of being assigned to the Stryker Brigade Combat teams for about seven years, both 125Stryker as they transformed out of a Light Infantry Brigade and then 2nd Cavalry Regiment. We moved from Fort Lewis, back to Vilsack. Number of deployments in Iraq during those seven years and then went on to US Army south with the 512 Geospatial Planning Cell. Also the jack in Molesworth, England. And then ended my career at the Army Geospatial center as the Military Advisor to the Director of agc.
How I got here I would say I got here by the benefit of a lot of great leaders. In my career as a young geospatial analyst, a terrain analyst, engaging with senior leaders, having them empower me to find new and exciting ways to engage with staff, answer questions, deliver solutions, really open the door for me and help me understand that the army is where I belong.
So that's how I got here. I've had a number of great leaders who have guided me along the way. And if you'll just indulge me real quick, I'd like to point out that Lt. Gen. Jones is retiring on the 31st of July. Great leader, one of the leaders that really influenced me through my career. And it'll be a big loss to the army once he retires.
[00:03:41] Speaker D: Many of our listeners might not be familiar with the Army Geospatial Center. Could you tell us a little bit about that organization, its purpose, and how it supports warfighters and the Joint Force?
[00:03:52] Speaker A: Sure. To understand the Army Geospatial Center, I think I'd start with the geospatial engineers.
The MOS, 12 Yankees and the 125 Deltas are the warrant officers across the Force.
Geospatial Engineers are embedded in formations across our force structures from brigade combat teams all the way up to the Army Service component commands, typically located with the S2s and the G2s and Ace, but they can also be found under the Engineer or the S3G3. Geospatial engineers do the analysis that contribute to GEOINT in support of the command and staff. And their principal job is to help surf elements of the operational environment that'll impact operations.
Typically, we think of terrain when we think of impact operations, but it can include any number of aspects that include cultural, institutional or physical aspects of the environment that will work against our forces across multiple domains.
Geospatial engineers pull those critical aspects out of the environment for the staff, kind of like a needle and thread through multiple staff processes like mdmp, IPB targeting. The Army Geospatial center supports those geospatial engineers and the army staff by providing critical data sets, critical services necessary to support everything from the command and control systems, broad area analysis and specialized Products to help decision makers and geospatial engineers across the force. We support and service anyone in the DOD that has questions or issues related to the terrain, to the operational environment. But our customer base is principally the army and army units. AGC is principally divided into two divisions. The first division is the Systems Acquisition Support Division and the second is the Warfighter Support Division where I work.
SASD Systems and Acquisition Support Division is principally oriented around challenges that deal with modeling and simulation, geoint system acquisition policy and standards. They do a lot of work for PEO IAWs within the geoint space and they also work generating common terrain backgrounds for modeling and the War Fighter Support Division, which is the division that I work in, has five branches. Those branches include the Collections branch, which generates high resolution EO and 3D data. We have the Engagement Branch, which focuses on RFIs and keeping 12 Yankees and 125 Deltas across all three compos up to speed on the latest and greatest technology through training events. We have the Operational Resilience branch, which is they hold the DOD's mission for groundwater and liquid logistics support, so finding where we can drill wells anywhere around the world and making sure we have water for our troops.
I'm the branch chief for the Data Generation and Production branch, which is to say that we build large scale data sets to support mapping anywhere from the 1 to 5,000, all the way up to 1 to 50,000 scale map products.
We have three lines of productions, which is part of the Intel Mission Product Guide. We have the Engineer Route Study. We have the Regional Terrain Planner, and then we have the Urban Tactical Planner. All three products are produced in my branch as well as the supporting data. So collectively, AGC supports over 140,000 mission command systems with map data and products.
In an average year, we deliver the rough equivalent of the Library of Congress map data products, war fighters around the globe. And then we support all the command and control systems in terms of testing, evaluating and making sure these maps work properly and could support the warfighter however they need.
[00:07:37] Speaker C: So it sounds like you're doing a lot there, and it sounds like there's a lot of capability at the Army Geospatial Center. Tell us a little bit about the technology that allows these capabilities to unfold. So you talked about, you know, pulling the thread, building these data sets. What tech are you using to get this data?
[00:07:53] Speaker A: So we use a number of geospatial information systems, the most common of which is made by a company called esri. But we use geospatial information systems to extract Data from imagery, from tabular data, from unstructured data. But we build databases of information that are tied to the earth's surface. These are spatially relevant sources of information. It could be in the terms of vector data, which is points, lines and polygons that are tied to attributes. So vector data has geometries which are tied to. If you think of a spreadsheet, a row in a spreadsheet would be tied to a geometry, and then the columns of information in that spreadsheet hold descriptors of that geometry. So you would have a road line, but the columns of information would describe how wide it is, what it's made of is that road on a bridge. It could be a hydro line, it could be a forest. Right? So that's vector data. We have raster data that's either representing satellite imagery or elevation data.
We have. LIDAR is a form of elevation data where we fly aircraft and scan the earth with a lase being to determine the altitude of different features or the elevation of different features.
So there's a lot of different data types that goes into a geospatial information system. And all of this data can be associated with activities or the impacts of the environment on those activities. We could also use it to quantify things. So if you've ever gone to Google Maps and you're like, I want to go to this establishment to buy something, and you'll see that little bar chart at the bottom that shows when it's most active at that store.
Geospatial information in the background tied to your phone.
What Google does is it says how many phones are in the store at any given time of day. And then they transform that information into a little chart that you see there when you, when you go into Jason's Furniture Warehouse. It'll show you when the busiest times are based on the collection of phones in that location.
Another good example of geospatial information systems is delivering packages for FedEx UPS. Your grocery store card, your address that's tied to your account for your discount, is tied to the store's catchment area.
So what stores do is they track what you buy, they match that up with demographics, and then they streamline their logistics from the warehouse to the store based on what everybody in that demographic is likely to buy.
So GIS can be used in any number of ways to describe the environment, to describe how the environment will impact our lives or operations.
And it's a really fascinating field to be a part of.
[00:10:39] Speaker C: That's really interesting. And it's. It's Kind of amazing to see how many normal day to day things that we do as civilians are impacted by the geospatial area.
So we, and when I say we, I mean, you know, the TRADOC, G2, the Army in general have focused recently on large scale combat operations. There's been kind of a shift towards that in recent years. This is based on insights that we've gleaned from contemporary conflicts. And we even based our annual assessment, the Operational Environment 2024-2034 on that idea.
How does that affect geospatial analysis, if at all?
[00:11:14] Speaker A: I think for the geospatial community this is a return to what we, what we were engaged in prior to the coin fight. Prior to September 11, a lot of what we did as geospatial engineers was codified in a number of FMS that date back to like the 1970s. FM 3010 is an example. Military intelligence of terr terrain or 533 terrain analysis. All of that was geared towards a high intensity conflict.
If you think back to that timeframe, there weren't drones, we didn't have shadows or Preds or reapers or any of those other types of full motion video. But as a staff, we had to come together and figure out what is the enemy going to do within this battle space, this operational space, and how are they going to do it.
One of the key limiting factors that drives how any force will operate within the battle space is the terrain. There's three neutral factors on the battlefield. It's terrain, time and weather. Right. And all these three things kind of come together that it can be evaluated in an objective way to understand how the enemy is going to fight with any operational space. What I like to tell people is that within any operational space there is battlefield geometry and then there's operational trigonometry. Battlefield geometry describes the width and depth of any engagement area. And then the operational trigonometry that sits on top of that is how any force can be arrayed according to their doctrine within the constraints of how the terrain will limit them.
So where will this tank be? Doctrinally, 50 meters from another tank along the front line. Given this specific type of mission, whether it's a defense, movement of contact or attack or whatever it is, how those tanks are oriented and how far apart they are is constrained by the terrain. Slope, hydrology, soil type, weather, how long did it rain? Is the soil still wet? How will that affect operations?
How will that tank be able to maneuver across the terrain? These are all aspects that can be tied up in that relationship between terrain and how any force will maneuver doctrinally within that space.
And so when we talk about large scale combat operations, it's kind of a return to that environment where we really dig into the terrain and start talking about all the things that they can't do in order to elevate to the surface, all the things that are possibilities for them to do.
This is radically different than what we've done in the COIN fight, where we had to have sensors everywhere, we had to see everything all the time, everywhere, all at once.
Lots of video feeds, lots of real time feeds. But when we get into Lisco, we have an opportunity to focus our assets based on what we know the terrain will allow them to do, and doctrinally, how that enemy formation is organized, how they operate within any given mission profile.
So if you're a fighting force that doesn't have a lot of logistics, you will tend to fight your fight within the scope of where you can support your logistics. If you're missing a certain layer, Russian army has a lot of organic and strategic logistics, but are missing that operational layer. So when you talk about how they fight, you would expect to see them fight along those lines of communication that will fill in that gap for that operational layer. That provides some insight that can be elevated within the staff as we go through course of action, development, mission analysis, and ultimately through X hour.
[00:14:54] Speaker D: It's notable that you mentioned drones and sensors because one of the key insights from many of the contemporary conflicts that we're witnessing today is that there's been a massive proliferation of drones and unmanned vehicles.
Could you talk a little bit about how these technologies are affecting geospatial data? Or conversely, how geospatial data is affecting these new technologies.
[00:15:21] Speaker A: So let's talk about how terrain will affect these unmanned and remote piloted systems. Terrain, as we talk about what a drone can and cannot do, is going to be a very vital part of any autonomous system that we decide to employ within the operational space.
A few episodes ago, we heard from somebody who fought in the Ukraine fight. The logical answer to that kind of situation is to provide these drones and unmanned systems with a highly detailed, high resolution understanding of the terrain so that they can conduct specific tasks even when they do not have access to that remote pilot or remote operator to tell them to go this way or that way. And this gets compounded as the operational space becomes more and more dirty, if you will, road craters, minefields, different operational situations, down bridges.
If we don't take the time now to consider how these drones and unmanned systems will Operate without that remote connection to our pilots and operators.
What we will find is that we will have soldiers moving to the front line, driving past a number of unmanned assets that have been rolled over, tipped, caught in a ditch, because they didn't have that high fidelity understanding of what the battle space looks like. And that high fidelity understanding of that battle space was an updated on a frequent basis.
How these drones will affect terrain and geospatial information is that we have an opportunity to collect a lot of information as we saturate the operational environment with all these sensors. The intersection of any two sensors, three sensors by modality, whether that's eo, lidar, maybe it's radar, or any other type of source of sensor that they may be operating off of.
If it can be backhauled into the operational center, into some sort of cloud repository or node within that operational theater, then we can take that data and synthesize a better understanding of the operational space at a truly high fidelity. The intersection of these different types of modalities will expose a lot of details that may not be evident from just a map or just from satellite imagery or any other resource.
So terrain analysis, geospatial analysis will shift as these drones saturate the operational environment, and the results will be quite interesting.
Recently I had an engagement with a commercial partner who is working on embedding multiple modalities into a single satellite imager. And what that'll give you is the opportunity to understand 15 modalities for every 10 meters of imagery that you see. So for every pixel, they have embedded 15 different modalities, LiDAR elevation, they've embedded EO radar, and they've also embedded a gravity map, which is something you can actually map. Gravity. Gravity is not the same around the world. So they've embedded all these different sources of information into a single pixel and it creates a 64 bit description of that 10 meter space that becomes very, very specific and can be used to answer some very, very specific questions about the impact of the environment on operations.
So when we talk about sensors, we talk about AI and some of the new technologies that are coming out. The future is pretty exciting from the sense that we will be able to pull in a vast quantity infrastructure of information. The question is, can we turn that information around quickly and use it and leverage it against anyone that we face within the operational space?
[00:19:18] Speaker C: So I would like to talk about artificial intelligence as you brought up, but you kind of piqued my interest when you said that one of those layers in that pixel is mapping gravity. Why would we want to know that. How does that help us?
[00:19:30] Speaker A: First, we have to understand that gravity is not equal around the Earth's surface. Right.
A lot of effort and a lot of math is spent to calculate gravity as a equilibrium across the Earth. So we can make some general calculations a lot easier. Everything from flight of ammunition, from artillery shells to the sniper bullet, we use some very generalized values to represent gravity. But that calculation comes from understanding it's a mean value between all the differences in gravity. A number of things that can affect gravity. Water is a big one.
When China dammed the Three Rivers Gorge and created a huge water reservoir, it drastically shifted the GRAV in that area. Whenever you have wet areas, wet soils, you will find that gravity increases as opposed to when it's dry. If it's in a large geography.
