Experimentally Determining Optimal Conditions for Mapping Forage Fish with RPAS

RPAS (Remotely piloted aircraft systems, i.e., drones) present an efficient method for mapping schooling coastal forage fish species that have limited distribution and abundance data. However, imagery acquisition in marine environments is highly dependent on suitable environmental conditions. Additionally, the size, color depth of schools will impact their detectability imagery. In this study, we identified optimal suboptimal conditions through a controlled experiment using model school containing four fish-like fishing lures. The was placed at 0.5 m, 1.0 1.5 2.0 m depths wide range then captured video results from cluster analysis, principal components, correlation analysis data found consisted moderate sun altitudes (20–40°), glassy seas, low winds (<5 km/h), clear skies (<10% cloud cover), turbidity. study provide researchers with best criteria detecting schools.