This study proposes monitoring methods of wild boars in plains or mountain forest areas using unmanned aerial vehicles (UAVs) equipped with infrared cameras. It is recommended to monitor in winter when the canopy layer is thin and the temperature difference between the ambient temperature and the body temperature of the wild boar is distinct, so that the infrared camera can better detect the wild boars. In flat land, the plane movement of the UAV can be easily monitored using the line transect, the point count survey, the plot sampling method, and the belted transect. In the mountain forest, there are variations in elevation due to slopes. Therefore, we introduced the WAYPOINT function to reflect the difference in altitude. After the investigator designates the waypoint, various information can be modified according to the terrain, and the WAYPOINT can be transmitted to other UAVs, so the utilization is high. In this method, once a route is created using the WAYPOINT, there is no need for additional operation after the start of the flight, and it helps to re-monitor the site by using the WAYPOINT record repeatedly. Therefore, this technical note provides a more repeatedly sustainable and scalable monitoring method than the conventional UAV method.

The transparency and reflectivity of glass are primary factors contributing to bird collisions, as they prevent birds from recognizing glass surfaces as obstacles. However, the effectiveness of bird collision prevention products is primarily evaluated through transparency-based tunnel tests, which do not adequately account for the reflective conditions commonly found on building glass. We developed an indoor flight tunnel system that simulated sky reflections on glass surfaces and compared avoidance responses to three bird collision prevention patterned samples under both transparent and reflective conditions. A total of 507 wild small passerines were tested, each undergoing a single flight trial. All three patterned samples showed lower avoidance rates under reflective than transparent conditions, but the overall effect of test condition on avoidance was not statistically significant. The frequency of invalid flights increased significantly under reflective conditions. These findings suggest that avoidance responses to bird collision prevention products may vary between transparent and reflective test configurations, although the magnitude of this difference remains uncertain. Incorporating reflective conditions alongside conventional transparency-based tests may therefore provide complementary information for evaluating product performance under different optical conditions.