Morphological Dune Mapping in Shallow Alluvial Stream Using UAV-based Hyperspectral Images

Abstract

Characterizing morphological features in shallow streams such as dunes and ripples is vital to studies on fluvial geomorphology and in-stream habitat assessments of stream ecology. The paper aimed to examine the feasibility of a conventional hyperspectral method called linear optimal band ratio analysis for capturing the detailed morphologies in shallow small streams, allowing the identification of ripples and dunes. The present study involved a dedicated field experiment at the Gam stream, which is a tributary of the Nakdong River, South Korea. An unmanned aerial vehicle based hyperspectral image was obtained with a spatial resolution of <10 cm and developed an optimal depth-band ratio rating by densely scattered in situ bathymetry measurements with a portable Real Time Kinematic Global Positioning System. The derived hyperspectral bathymetric map with a 7 cm spatial resolution successfully captured the detailed bed morphology, where dunes with sizes of 1.5 m were clearly identifiable. The correlation with depth measured by RTK-GPS was found to be 0.956, with Root Mean Square Error of 0.033 meter. The research confirmed that the conventional linear OBRA used for low-altitude UAV-based hyperspectral images can capture morphological features in shallow streams with a high spatial resolution.