Preliminary exploration of monitoring Gynaephora alpherakii using unmanned aerial vehicles (UAV)

Gynaephora alpherakii is one of the most serious pests of alpine grasslands. Broad-scale monitoring is the foundation for identifying the distribution and controlling the spread of G. alpherakii. However, traditional quadrat-scale monitoring is difficult to implement accurately and effectively at broad scales using long-term fixed-points. In this study, we propose a UAV-based monitoring method (UAV_Belt) to improve efficiency and accuracy over larger areas. Results showed that UAV_Belt improved field monitoring efficiency, sampling representation, and destruction of the caterpillar. The method overcame sampling obstacles and improved timeliness and predictability compared with traditional methods. Mavic 2 Zoom, which has terrain-following and digital zoom functions (UAV_M2) demonstrated more effective sampling uniformity, data extraction, and accuracy. Combined with long-term and cooperative monitoring and analysis of small-scale habitat fragmentation using UAVs (FragMAP), UAV_M2 is a promising technique for delivering early warning and effective prevention of G. alpherakii outbreaks, providing theoretical and practical guidance for sustainable development of the livestock industry and grassland ecosystems of the Qinghai-Tibetan Plateau.