Have you ever seen one of our canine teams in action at an airport? Or lucky enough to see a team working at special events, e.g., Superbowl, World Series, NCAA tournaments, etc. across the U.S.? With more than 1,000 teams deployed nationwide there is no doubt they are incredible assets to ensuring the safety and security of the nation’s transportation systems.
TSA’s Canine Training Center
The Canine Training Center (CTC) is located at Joint Base San Antonio-Lackland in San Antonio, Texas. This site trains and deploys both TSA-led and state and local law enforcement-led canine teams. These teams, made up of a canine and a handler, support the day-to-day activities that secure and protect transportation environments.
The CTC is considered the center for excellence in explosives detection canine training, and is the only program of its kind in the Department of Homeland Security and the second largest in the federal government, after the Department of Defense.
The site contains 17 indoor venues that mimic a variety of transportation sites and modes. This includes a cargo facility, an airport gate area, a checkpoint, a baggage claim area, the interior of an aircraft, a vehicle parking lot, a light rail station, a light rail car, an air cargo facility, a mock terminal, and open area searches venues for air scenting.
Canine Training
Canine teams are highly trained to detect a variety of explosives based on current intelligence data and emerging threats. But before getting to work, explosives detection canine teams undergo a 12-week training course. For our passenger screening canine teams, the training is 16-weeks! Of course, the training doesn’t end at graduation. Each team is continually assessed to ensure the canines demonstrate operational proficiency in their working environment.
So, next time you are at the airport and see a canine team hard at work, remember do not pet! They are working hard ensuring the safety and security of you and your fellow travelers. Want to learn more about canine training, check out our video below:
