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An Eco-Friendly Fight Against Thaumetopoea Pityocampa Infestations in Pine Forests Using Deep Learning on UAV Imagery

Thaumetopoea Pityocampa (TP), or Pine Processionary Moth, is one of the most destructive species in the Mediterranean, causing defoliation of pine forests. TP infestations have a considerable economic impact in primary sectors, particularly forestry. They also have a negative impact on human health, the environment, and society. TPs make silken, tent-like nests on the tops of pine trees. The detection and mapping of Thaumetopoea Pityocampa Tents (TPTs) in aerial imagery taken from Unmanned Aerial Vehicles (UAVs) flying over TP-infested pine forest zones are presented in this research. Deep learning-based image segmentation has been used to detect TPTs in the aerial imagery. The geolocations of the centroids of the detected TPTs are calculated and converted to spatiotemporal maps using navigation logs and the camera parameters of the UAV. These maps are a valuable resource for biologists, ecologists, and forestry agencies' pre- and post-management plans. The system's effectiveness has been demonstrated in the pine forests surrounding the Çakilarasi Mathematics Village, Saricakaya region of Eskişehir, Türkiye.