The availability of high-resolution commercial satellite images, like this Ikonos image of the World Trade Center a day after the 9/11 terrorist attack, has helped transform the field of imagery analysis. (credit: GeoEye)

Letter: a new kind of strategic intelligence?

by Dwayne A. Day
Monday, September 11, 2006

In his recent article “A new kind of strategic intelligence?” (The Space Review, September 5, 2006), Taylor Dinerman makes frequent reference to “the imagery interpreters at the NRO.” He prescribes what he thinks is a solution to a problem with their training.

There are some problems with this article. To begin with, there is no such thing as an “imagery interpreter” in the intelligence field. The correct term is “imagery analyst,” and there is a history as to how this job description evolved, and continues to evolve. The second problem is that the NRO, which stands for the National Reconnaissance Office, is not responsible for training or utilizing imagery analysts, and never has been. A final problem is that it is unclear if there really is a problem with their training—and how would we know.

The National Geospatial-Intelligence Agency (NGA), not the NRO, is most responsible for imagery analysis for intelligence purposes. The NRO designs, develops, and operates America’s fleet of intelligence satellites, including signals intelligence and imagery intelligence satellites. Other agencies utilize the data produced by these satellites. NRO is a producer of intelligence, whereas other government agencies are the users—the analyzers. The National Security Agency, for instance, takes the signals gathered by NRO satellites and processes and analyzes them. NGA experts utilize the imagery (both photographic and radar) produced by NRO satellites. There are imagery analysts in various other government agencies, including the CIA and the Pentagon, but the NGA has the majority of them and is responsible for training them.

NGA is the relatively new name for what used to be called the National Imagery and Mapping Agency, or NIMA. NIMA was created in the mid-1990s via the merger of a CIA-run organization known as the National Photographic Interpretation Center (NPIC, pronounced “enpic”) and the Defense Mapping Agency. The merger and then the name change were intended to help break down the barriers between the imagery analysis and mapping communities. Today, geospatial information experts no longer think solely in terms of images or maps, but a combined product—digital software packages that merge imagery, and information about features of the imagery, into a hopefully seamless and user-friendly tool. The information embedded in the images includes things such as building addresses, terrain measurements, or the identification of structures like bridges and paved versus unpaved roads. The goal is to deliver a product to other users, such as troops in the field or pilots in a B-2 bomber, which contains the kind of information that they require to accomplish their mission. As a result, “imagery analysis” is now really part of a much broader effort to deliver more information to end users and the term itself is becoming outdated. One would probably have to dig through CIA and Department of Defense human resources manuals to see how the term is even used these days.

The term imagery analyst itself has some history behind it. Although I have not been able to determine exactly when it was applied, it probably dates to the mid-1960s. Before that, NPIC, which earned its reputation spotting Soviet missiles during the 1962 Cuban Missile Crisis, had “photo-interpreters,” or PIs. Many of the civilian PIs had military backgrounds as pilots, sailors, or soldiers, but not necessarily military training in photo-interpretation. In fact, many of them had training in history, geography, and even forestry. The ability to think in broad terms—of terrain, forests, or cultures—was considered an asset for the job. Naturally, there were bureaucratic squabbles (well, turf wars) over what kinds of intelligence a photo-interpreter was allowed to interpret. Other kinds of intelligence analysts argued that the PIs should simply report that they saw a building and not make any guesses as to what was inside of it. Eventually, the term photo-interpreter was changed to the more professional-sounding “imagery analyst,” but there were always squabbles as to how much analysis the imagery analysts were allowed to perform.

There were other squabbles as well. For instance, the CIA tended to treat imagery analysis as a profession, whereas the military tended to treat it as a specialization. What this meant was that the CIA trained their imagery analysts for years and allowed them more authority in analyzing intelligence and drawing conclusions. In contrast, the military provided less training and tended to treat their own imagery analysts as bean counters—count the number of tanks in the Siberian tundra, but don’t try to determine what they are doing or what unit they belong to. Naturally, when the CIA-run NPIC merged with the Pentagon-run Defense Mapping Agency under military control, many of the civilian imagery analysts feared that they would lose their professional status (not to mention their more generous CIA job benefits) and left government service. American imagery intelligence capabilities suffered in the 1990s as a result of this merger. The fact that the creation of NIMA—which was supposed to improve intelligence collection—may actually have harmed it is a subject that has never received the kind of public discussion it deserved. Several years ago NIMA started hiring hundreds of new imagery analysts, indicating that the senior leadership recognized that they had to reverse their losses. The degree to which they have been successful is not known outside of intelligence circles, but clearly a lot of experienced people left in the 1990s and it takes time to rebuild expertise.

Dinerman prescribes a solution that may be in search of a problem, outlining with much specificity how the government should retrain its analysts to deal with what he claims are two primary needs. These are the requirement to locate deeply buried facilities such as underground bunkers, and a requirement for experts who “specialize in combining cultural intelligence and knowledge with the ability to expertly examine imagery in order to extract not just tactical intelligence, but information on long-term trends inside the societies that are being studied.”

But is this really the problem? Is it a problem at the imagery analysis level, or at another level in the intelligence analysis chain? There are other intelligence analysts who specialize in cultures and economies who make use of imagery intelligence. Some of them are former imagery analysts themselves. If a shortage of these skills exists, it is undoubtedly at a different level than the people who spend the majority of their time dealing with imagery.

The renaming of NIMA into NGA was intended to reflect the fact that computers now make it possible to add information to an image as well as extract it, and to develop entirely new products. These organizational changes indicate that the intelligence community clearly placed a greater emphasis on developing computer skills for its analysts and breaking down barriers between imagery and mapping. The imagery analysts are still trained to derive information from what they see in their pictures, but clearly the community now values the ability to communicate that information in new ways. Has this emphasis on computing and communications come at the expense of training in analysis? We on the outside of the community do not know.

There is almost no public literature on the development of imagery analysis as an intelligence field, largely because so much of the field was classified until recently. The declassification of tens of thousands of documents on the first decade of NPIC’s operations now makes it possible to study the early years of this field. However, the computer revolution and the development of commercial remote sensing have rapidly transformed the field in ways that its early practitioners never envisioned. There are now numerous university level courses in “geospatial sciences” that train people to become “geospatial information specialists”—terms that are harder to say but sound more sophisticated than “imagery analyst.” At the same time, the development of powerful geospatial information system tools has meant that people with little or no training can now manipulate overhead imagery data in ways that only a highly-trained imagery analyst could do only a decade ago (a well-known example is Google Earth). How this is affecting the classified imagery analysis world is the kind of question that can only be answered via detailed research into the profession. One could argue that the intelligence community is not providing the right kind of training to its analysts, but that is a conclusion that one could only reach by having access to sources that are highly specialized, and undoubtedly classified.

Dwayne Day was the primary editor of Eye in the Sky, a history of early satellite reconnaissance, and writes frequently on the development of American reconnaissance satellites. He currently teaches a space policy class at The George Washington University.

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