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May 20th, 2010
ERDAS Focuses on Cutting through the Data Deluge


V1: How is business?

Campbell: We are noticing globally that a recovery is starting to happen. There is an increasing amount of interest, with a growing number of infrastructure projects getting kicked off. A lot of the government funding at the state and local level was being squeezed over the past few years, and that is beginning to loosen a little. We’re seeing signs of the recovery throughout our business.

Right now, our business is seeing the largest amount of growth in Asia. We’re seeing year-on-year growth in a significant double-digit range. We’re also starting to see Europe move in a positive direction, and the same is true in the United States, as well as Central and South America.

The area that we’re seeing the strongest interest in is around our ERDAS APOLLO suite of products, which enables the management and delivery of geospatial information to a wide variety of people. From an industry perspective, organizing and doing something meaningful with a tsunami of data is the challenge of the decade. – Letting organizations know what data they have, where it is, what it looks like, and how to set up appropriate security-based access to it. Through ERDAS APOLLO, organizations can handle massive amounts of geospatial data so those that need this information, can easily use it.

During the past few years, a significant effort has been centered on our server technologies, and the implementation of large spatial data infrastructures (SDIs) or multi-departmental sharing systems. We are continuing to develop these solutions to be all-encompassing inside of an organization.

We recently provided ERDAS APOLLO to the Port of Rotterdam, who received funds as part of the recovery. They are using the server platform to organize and communicate all of the data that they have for the operation of the port.

Another significant customer that we’re working with is the British Transport Police (BTP), who is building a complete geospatial data infrastructure around ERDAS APOLLO for law enforcement and transportation to support the upcoming 2012 Olympics in London. As you can imagine, this is an important project with a big profile.

The defense industry calls this the COP (the common operating picture), the unifying framework that provides all responders a similar view into real time events as they are occurring. I think it’s natural for the BTP to be engaged in this program, and we’re happy that they’re doing it with us.

V1: Can you describe the pieces of APOLLO, and how they form this framework for geospatial data infrastructure?

Campbell: There are several key components to the platform. There is the catalog function that enables organizations to harvest metadata and understand the kinds of information that they have available to them. ERDAS APOLLO scours their network for all the geospatial data that they have and organizes it into a catalog. There is also the management function that enables you to eliminate duplication and store data in the best format for efficiency and effectiveness. Finally, there is the delivery function, providing a diverse set of methods for securely streaming geospatial information over the Internet, enabling end-users to find the data they need, and stream it to a browser application or download it for use locally.

All of these components are important in managing the breadth of geospatial data, and that is what our ERDAS APOLLO is all about. ERDAS APOLLO is an interoperable platform and enables organizations to share data internally or with any third party, and into any application or web client. ERDAS APOLLO gives everyone the opportunity to access this treasure trove of data through our open platform and interoperability.

We’re seeing a lot of interest, because ERDAS APOLLO is robust along multiple areas of performance and was built to meet standards of interoperability. No one is excluded from the game. We can jump into these heterogeneous environments and play nicely with whatever tools and data types are there, without making an organization change how they operate, or the tools they use or the custom applications that they’ve created. We just fit right in, making all the existing technology better.

V1: I’ve noticed that you’re able to handle CAD formats and other formats outside of GIS. Is there a growing interest in being able to handle all kinds of data, and is there a coming together of these workflows?

Campbell: What we’re seeing is a merging of the workflows in the lifecycle from design to as-built in the CAD world, where the data is immediately available in a GIS for analysis or cartographic representation, all the way through to image analysis and feature extraction to update the original data.

In the early days of our industry, engineers designed things in CAD. Then, we would take those CAD files and try to shoehorn them into a GIS. We might then get images after the fact, and figure out how to do analysis, in semi-automatic ways, to see what might have changed from the original CAD drawing. All of these were independent processes that depended upon a sneaker net or FTP to move the data from place to place. They were also ingesting algorithms for CAD import, and things like that.

Now we’re seeing these processes blended together because of the interoperability picture. We can now view CAD files, and maybe even update them. People are storing more data in geodatabases or spatial databases that are relational in nature, and updating this data becomes easy and fluid. The workflows remain independent, but there’s a merging of how we work between the different workflows, which obviously benefits everyone involved.

In the ERDAS APOLLO and ERDAS IMAGINE 2010 releases, we’ve done significant work with Safe Software’s Feature Manipulation Engine (FME) to support additional GIS and CAD formats. We created this partnership with Safe Software to make it easier for our users to directly read and write an ever expanding number of vector and feature formats, including MicroStation’s DGN v7 and v8 format files.

V1: The data management space seems to be a good place, given the explosion in imagery satellites. There are more than 100 planned for launch within the next ten years. The refresh of imagery with that many satellites will be something to see. Are you focused on the rapid delivery of information?

Campbell: We’re working now with full motion video imagery at 30 frames per second. We’re seeing a lot of interest in real-time or near-real-time full motion video, and the ability to analyze this and integrate it with other geospatial information. We are investing our R&D resources in that domain to fully understand how to merge these capabilities together and make them work.

In addition to all the satellite launches, there are a significant number of new airborne sensors every year, in large, medium and small format. There is also an explosion of airborne LIDAR, and the emergence of terrestrial and mobile LIDAR. Laser scanners can now be mounted on vehicles that drive through cityscapes, providing highly accurate measurements of building facades, street furniture and everything else in the surrounding area.

There is data coming to us from everywhere—we are working with our customers to understand their needs, and how we can provide the best tools to leverage all of this data to solve a common problem.

V1: What is the status of a metaverse or visualization platform that allows you to fuse and visualize all of this in a sort of visual common operating picture? Is that a focus of yours as well?

Campbell: It definitely is, and you’ve just touched on an area that we’re spending a lot of time, energy and money on in our research. The common visualization platform, where you can deal with 2D, 3D, 4D, and perhaps even 5D all on the same canvas, and all integrated, is what we’re working on. That’s an area that we think there’s a lot of opportunity to grow our product offerings, and provide real value to customers that have historically used multiple different product sets to do various types of things with their different data.

V1: How does the Internet play in that? Are you focused on the cloud for the computing and visualization power to make that happen?

Campbell: Are you reading our internal notes or something? This is another big area of research focus. I’ve defined visualization, the fusion of multiple data types (including full-motion video), the exploitation (not only the management) of point cloud data, and then the next area is in the whole notion of cloud computing. Within cloud computing, there are two areas where there is a great deal of interest.

One is the ability to leverage the cloud for the scalable processing power that you need. If I received all new imagery, and wanted to create a whole new orthomosaic of my entire area, that’s a compute-intensive process. Maybe I would have to have a large server system to crunch through that in a meaningful timeframe, but I would only need to do that maybe once per year. The ability to access that power outside my organization when needed is something that is really interesting to our customers, and we’re working toward doing that.

The second part of the cloud that is equally interesting to us is the software-as-a-service (SaaS) that a cloud environment could offer. If you were an engineering company doing a feasibility study for a new highway, maybe it’s only a 90-day project, and you have 10 engineers working on it for 90 days. You may not want to buy a lot of software for a 90-day project, but you could use software as a service through the cloud, with the full robustness of the product, but only pay for it on a monthly basis. There’s an interesting business model there that the technology allows us to engage in.

V1: People seem much more flexible on how they utilize resources. Your tools are well ahead of that curve.

Campbell: If you think about our space, at one point, all we had was Landsat imagery, with file sizes in the megabytes that could be loaded onto your hard drive. Now, if you go to GeoEye or DigitalGlobe and you buy a half a meter image of a square mile, it is gigabytes in size. Before long, you have an enormous amount of data, not only in quantity, but also in physical size. This means you need to have a tremendous amount of disk space and processing power. For many organizations, it is getting harder and harder to keep up with the volume. As the data becomes better, it also gets larger, and as it gets larger, it takes more power to process and disk space to store. I think these are the issues that are forcing people to think of some alternative ideas.