AUTOMATION OF RIVERBED SURFACE GRAIN SIZE DISTRIBUTION MEASUREMENT TECHNIQUE USING UAV AERIAL IMAGERY AND ITS APPLICATION TO UNDERWATER

Abstract

 In this study, we propose a method using UAV-SfM that does not require a scale in images. We also addressed various image analysis issues through image processing and created an RPA (Robotic Process Automation) program for automatic continuous processing, reducing labor in measuring riverbed surface grain size distribution. We applied this technology underwater and found that for UAV images where underwater stones and gravel are distinguishable, image processing improved grain size identification accuracy. In high water depth areas where stones are not distinguishable, image processing slightly improved identification accuracy in shaded areas.