Turkish-made unmanned aerial vehicles (UAVs) played an active role in efforts to extinguish over 2,000 wildfires last year.
Unmanned aerial vehicles (UAVs) take up important tasks for observation and detection of forest fires while employing effective intervention of fires, according to data from the General Directorate of Forestry (OGM).
The UAVs were essential for observing and detecting forest fires, as well as for effective intervention, according to data from Türkiye's General Directorate of Forestry.
The Bayraktar TB2 and Aksungur drones by defense industry companies Baykar and Turkish Aerospace Industries, respectively, have been used in the early warning and extinguishing efforts since 2020.
Some 2,500 forest fires and 3,000 rural fires have occurred in Türkiye as of Nov. 15 last year.
In June 1-Nov. 15, 2023, UAVs detected 546 out of 1,300 forest fires, and 1,500 out of 1,900 rural fires, adding up to over 2,000 fires in total.
Thermal cameras mounted on UAVs allow them to detect even a square meter of heat from a source making a small glare from 100 kilometers (62 miles) away.
The footage is then sent to a fire management center in the capital Ankara, which instructs personnel in the afflicted zone, thanks to infrastructure developed by Baykar.
In addition to detecting fires that have already started burning, UAVs continually monitor forests with surveillance cameras and thermal imaging systems to detect potential fires.
The response time of UAVs to fires has since been reduced from 45 minutes to 11 minutes, wiht the goal being to reduce this further to a flat 10-minute mark.
Some 14 UAVs are monitoring forest fires in Türkiye in 2024. Additionally, the early-warning system for forest fires called Oyesus will help develop institutional capacity and early detection of forest fires.
The Oyesus software will analyze forest images within 15-kilometer radii and detect distant smoke within 15 to 25 seconds.
The Fire Management Project, an artificial intelligence-powered dynamic fire risk map, will also be used to predict forest fires and take cautions.
