Kelp forest mapping by use of airborne hyperspectral imager

Abstract

We present an easy and efficient approach for remote sensing of ocean color, relevant for monitoring and management of kelp forest and bottom substrate with a cheap custom made hyperspectral imager. Remote sensing of ocean color was performed in the Kongsfjord, Spitsbergen (79 deg N and 12 deg E) from an airplane (2950 m altitude) equipped with a hyperspectral imager, giving monochromatic images (425-825 nm) using the push broom technique, captured with custom designed software in 5 nm steps. Synchronously in situ measurements of upwelling spectral irradiance, (Eu())( = 350-950 nm) measured at 30 cm depth were performed as a reference for the remotely sensed images. Surface water samples were taken for enumeration and identification of organic (plankton), inorganic particles, and colored dissolved organic matter. For identification and classification of kelp and bottom substrate, Bayesian supervised classification and a differential histogram equalization technique were used and compared. Both techniques gave successful discrimination between kelp and bottom substrate in shallow water above the Secchi depth (<19 m). The imager could easily be implemented for other applications such as detection and monitoring of phytoplankton blooms, suspended matter, and colored dissolved organic matter in surface waters, especially in connection with environmental and aquaculture management.