Creating Actionable Intelligence on the Cloud

BK: Insights from Hexagon Geospatial product line director of M.App X, about how Hexagon Geospatial cloud-based solutions are bringing geospatial intelligence to the cloud, enhancing real-time decision-making.

Defence & intelligence agencies are faced with many challenges, such as producing and managing geospatial intelligence in the face of escalating global tensions, the changing nature of threats, and limited capacity. Providing near-real-time, actionable information is paramount, but the traditional desktop workstation model for analysts typically means that maps are outdated by the time that they’re disseminated to mobile units and decision-makers.

Welcome to HxGN RADIO. My name is Brian. Thanks for joining us today. We are speaking with Brad Skelton, Hexagon Geospatial product line director, M.App X, about how the M.App X solution solves these challenges by fostering geospatial tradecraft creation, common usage, and secure sharing of the latest intel, ultimately making the latest information accessible and reusable. Brad, thanks for joining us!

BS: Thank you.

BK: So before we talk about the M.App X solution, tell us about some of the data access and sharing challenges that are common in the D&I area.

BS: Well, in defence organisations, especially in the analysts’ organisations, they make their living – their job is to extract information, and typically from imagery, and they receive a lot of imagery. They get imagery from their own sensors, their own satellites, they get imagery from commercial vendors, commercial sensors, and they have to manage all this imagery. And there are a lot of tools for managing this imagery. They have  – in many cases, they have their own libraries, they have their own entire image management infrastructures for doing that. In some cases, they’ll use our product second to manage imagery, and in some cases they have to be able  – be prepared to deal with things somewhat ad hoc fashion, as something comes in, get it and use it. So we have to be prepared to deal with these with these various different ways of getting imagery.

BK: Now we’ve heard the expression real-time data for creating actionable intelligence in the D&I space for many years. Most believe this to be aspirational, especially given the ongoing dramatic rise of new data sources. How does M.App X make real-time data sharing a reality?

BS: In several ways. First off, M.App X is very flexible in the kinds of data and data formats it can read. Second, it is sensor model aware. So what this has to do with things is that it typically in an image exploitation system, you may need the imagery to be ortho-corrected before you deal with it. M.App X doesn’t need that. M.App X can use the sensor model. It’s a part of the imagery, can begin making direct and precise measurements from imagery immediately without doing that. M.App X also can deal with the data in its native formats. A great deal of the imagery within the defence and intelligence agency comes in a format called NITF, and NITF is actually a broad and complex format, and M.App X can deal with almost any form or flavor of NITF that you throw at it.

BK: Excellent. So tell us about how M.App X can provide tremendous cost savings for D&I agencies.

BS: Well, typically in D&I agencies that have been doing imagery exploitation, they use what are called electronic light tables. It’s software for looking at imagery. But this has traditionally and typically been deployed on pretty high-end workstations. So each analyst, of which there may be hundreds or thousands in a large organisation, will have a workstation, and that workstation will have their preferred software on that workstation. And so you can imagine that there’s a lot of expense, in a) purchasing the workstations, b) keeping them up-to-date. And so M.App X pushes the software back to a server. The main workhorse of M.App X is a server component that can live on a cloud, a private cloud, or it can be posted on a public cloud. Usually not in a defence organisation; it’s in their own internal cloud. Because of this, you don’t have to have all the expensive hardware at each analyst’s seat. You do have to have nice big servers. But the thing is, I can concentrate my expensive hardware in one place, and then it can be used by the people that need it when they need it. It’s not sitting there unused, perhaps, at some times. You can have less expensive workstations that people work at, and when I have to deploy the software I only have to put it on the server. I don’t have to go out to each single workstation and update it.

BK: Excellent. Does that create better security as well, with all that?

BS: We usually  – the security comes within the organisation, it’s all operating on an internal network, and they have to have a secure network itself.

BK: Yep, piece-by-piece kind of thing. Okay, excellent. Tell us about M.App X’s unique spatial data modeling environment that provides near-immediate feedback and previews.

BS: Well, one of the things we include in M.App X is our spatial modeling engine, and the spatial modeling engine is a very flexible core component that we develop in our IMAGINE product. We use it in many of our products now. What it lets you do is actually create new algorithms graphically. So a specialist who knows what needs to be done, but might not  – might not be a programmer, can actually use our graphical spatial modeling engine to put together a particular processing workflow. And once they’ve put this together and got it working, they can push it to the server, publish it, and then that new geoprocessing capability becomes available to the analysts. So it’s a very rapid way to build and deploy new functionality.

BK: And we touched on the cost savings, which is fantastic. How does this technology help, you know, these agencies to move away from expensive legacy applications and hosting?

BS: Once again, it’s a server product, like I said. In the traditional domain, you’ll have a lot of different desktop applications, possibly on each one of these workstations. Now, by pushing it back to the server, and a server which is very extensible and programmable, instead of having a series of different desktop applications, what you can do is have different processing algorithms, and because the M.App X platform is extensible, and our toolkits are available to other people, then they don’t have to get all their capability just from us. Other people can add on to M.App X, can integrate with M.App X, and it can integrate with other systems too.

BK: Excellent. And you touched earlier on the idea of getting the information out there quickly, so sharing and dissemination of data in the field of  – to the warfighter is paramount as well for mission success. How does this solution offer instant access to relevant data?

BS: Now M.App X itself really is  – is primarily for the analysts, the analyst job is to  – in the end, make a report, and a report is not a written report but a graphical report, like a PowerPoint. And their job is usually to go to a decision-maker or even a warfighter, some kind of graphic that has to be delivered, so in M.App X, you can make a graphic, the graphic can be in the form of a PDF or maybe a PowerPoint, and those can be quickly disseminated to people in the field who have tools that can read those.

BK: Excellent. I love it. Very, very efficient, that’s what we like. Tell us about some of the noteworthy features of M.App X, for example, up-to-date feature repository, smart data management, things like that.

BS: I think some of the very nicest features of M.App X are, like I said, it is sensor model aware, so you can take precise measurements off of M.App X. We can do feature editing on M.App X. So in a defence organisation, an intelligence organisation, they usually are building up a database of information. We’ve set up M.App X so that, using industry standards like WFS, they can collect information on top of this imagery in precise locations and put it directly back into their database. They don’t have to store it in any kind of internal M.App X format.

BK: Okay. How can solutions like M.App X help systems integrators offer more comprehensive, cloud-based solutions to their customers as well?

BS: Well M.App X is not an out-of-the-box solution. Each one of these organisations has a different setup, they have a different imagery management system, they perhaps have different sorts of maps and templates, they have different processes and procedures. We work with integrators, we intended it for integrators to take the product and, you know, take it that last mile to fit it to the workflow of the individual defence organisation.

BK: Okay, excellent. And like you said, things are always being added to it and so it can always really adapt nicely  –

BS: Right .

BK:  – as organisations need it.

BS: It is a product intended to be integrated into the environment, not just a standalone isolated piece.

BK: Good, seems to be a lot more efficient that way.

BS: Yes.

BK: All right. In looking towards the future, what types of new features are you aiming to offer in the updated versions of M.App X?

BS: OK, well you’ll be hearing a lot about the Luciad technology that we’ve acquired, and Luciad has a web-based component called RIA, and we are actually building RIA in, we’re replacing the lowest level component the M.App X client with RIA for its visualisation capabilities. What that’s going to let us do is have not only a 2D application but a 3D application, so you know, one of the big features over the next year is that we will have a fully 3D-capable M.App X client that will help people exploit things like point clouds better, they’ll be able to pull in buildings and meshes and  – and look at realistic scenes, as well as doing their traditional 2D, heads-up image analysis work.

BK: Excellent, very exciting future!

BS: So it’s exciting to us too.

BK: Yeah, I love it. Brad, thank you so much for your time. Really appreciate it.


BK: For more information on this, please go to And of course, to listen to additional episodes, or learn more, Thank you so much for listening.


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