Advanced Warfare: New Technologies and Their Application in Civil Reconnaissance

By Kyle Povio

Photo: AT&T, 2018, COW Drone mid-flight during an employment exercise with the Network Recovery Team.


When I was in my sophomore world history class, my teacher assigned us to watch the 1964 film Fail-Safe to give my peers and me a better understanding of the Cold War. After watching the movie, there is still one scene that stands out. Two nuclear bomber pilots are playing pool at the recreation center; the older of the two begins to become frustrated because of all of the new equipment and technology in the aircraft and how it creates a virtual boundary between the pilots and the rest of the crew. The younger pilot then exclaims to the older one, “Well, that’s the new policy, eliminates the personal factor, everything’s more complicated now, reaction times are faster, you can’t depend on people the same way anymore.” The veteran pilot then turns and asks, “Then who do you depend on?”

This question is relevant today because in seemingly every facet of society and within the military, technology seems to be augmenting human decision making and removing the need for human oversight. This paper and research aim to highlight and determine which potential technologies can coexist with the human role that occurs in civil reconnaissance and which technologies increase success. Before examining this set of technologies, let us first explore and describe what Civil Reconnaissance is and how nuanced technologies can be implemented within the Civil Affairs (CA) community.

Civil Reconnaissance

To understand how to enhance Civil Reconnaissance with technology, we must define what civil reconnaissance is. According to the U.S. Army doctrine for Civil Affairs, FM 3-57, Civil Reconnaissance (CR) is a "targeted, planned, and coordinated observation and evaluation of specific civil aspects of the environment for collecting civil information to enhance situational understanding and facilitate decision making. Potential sources of civil information include areas, structures, capabilities, organizations, people, and events (ASCOPE) assessments."[1]

One applied example can be CA's actions during Operation Unified Response in 2010. During which operators of the 95th Civil Affairs Brigade (Special Operations) (Airborne) conducted CR to collect initial damage assessments to address the local population's needs after the devastating 7.0 magnitude earthquake in Haiti.[2] Another notable example was the deployment of CA forces during the NATO-led Implementation Force (IFOR) in Bosnia and Herzegovina. In support of IFOR, a selected group of CA forces monitored landmine contamination's effects on impacted populations. These soldiers also used these missions as an opportunity to disseminate landmine awareness messages on comic books and soccer balls to vulnerable children in these landmine infested areas.[3]

Emerging Technologies as Force Multipliers

Going back to doctrine, CR allows commanders to meet specific critical information requirements and any request for information through the operations process. The ability of a CA team to accurately collect and disseminate information on the civil component is one of the most critical steps in the Civil Information Management (CIM) cycle.[4] However, commanders of CA forces must give their personnel as many resources as possible to be successful in their mission and help achieve the unified action force's overall goals. Here are some great up and coming tools that can help give CR more long-term success.

1. Snapshot Hyperspectral Imaging

With the unaided eye and regular digital cameras, we can only take in three visible light forms on the electromagnetic spectrum (EM). While this is useful for recording and observing the civil component while conducting CR, hyperspectral imaging (HSI) takes it to the next level. HSI uses a multitude of light detectors that take in all parts of the EM. These images create great civil data products because it allows us to detect problems we could not originally discover with average cameras. A notable example we can find is in the agriculture industry.