Evaluating the Visibility of Power-Line Bird-Collision Warning Devices Using an Avian Spectral-Response Weighting...

Collisions with overhead power lines are an important source of avian mortality, particularly for migratory and large-bodied birds. Although warning devices are widely installed to increase line visibility, their image-based visibility across viewing distances and directions remains poorly quantified. We evaluated eight power-line bird-collision warning devices using UAV-based multispectral imaging and an avian spectral-response weighting model. Images were acquired at 5, 10, 20, 30, and 50 m under upward-looking, horizontal, and downward-looking viewing geometries. A composite visibility score quantified target-background separation within the multispectral images. Raw mean visibility increased from 0.351 at 5 m to 0.484 at 50 m; however, the distance effect was not significant after accounting for viewing angle and heterogeneous residual variance. Viewing angle was the dominant source of variation at 20-50 m, with substantially higher visibility under downward-looking views than under horizontal and upward-looking views. A significant distance × viewing-angle interaction further showed that distance-response patterns differed among viewing geometries: visibility increased with distance under downward-looking views but remained consistently low under horizontal and upward-looking views. The relative performance of the tested devices also changed under low-visibility conditions, with the self-luminous tag and circular tag B attaining the highest condition-standardized mean scores. These findings identify viewing geometry as a critical determinant of warning-device visibility and demonstrate that averages pooled across observation conditions can obscure important performance differences. Evaluation and deployment should therefore prioritize device visibility from below and during near-horizontal viewing, particularly for overhead ground or shield wires at medium and long distances. This condition-specific framework provides a quantitative basis for improving the design and placement of power-line bird-collision warning devices.