Classification Technique of Algae Using Hyperspectral Images of Algae Culture Media

Abstract

Increases in algal growth have been reported in rivers, reservoirs, and other water resources worldwide, including Korea. Algal overgrowth can result in algal bloom, which has several negative impacts, such as ecosystem degradation and economic losses. Mitigation measures employed in Korea include an algal warning system and survey-based water quality forecast systems. However, these methods are time-consuming and require sample collection from the site. On the other hand, remote sensing techniques that use chlorophyll a are unable to distinguish between different types of algal species. In this paper, we aimed to identify a classification technique based on remote sensing methods that can be used to distinguish between blue-green algae and green algae. We acquired and prepared an algal culture solution and used a hyperspectral sensor to obtain an algae spectrum. Thereafter, we measured the absorption and emission spectra of blue-green and green algae and distinguished them using the instantaneous slope change of the spectrum. The absorption spectra for green algae showed two peaks at 417–437 nm and 661–673 nm, whereas those of blue-green algae showed three peaks at 449–529 nm, 433–437 nm, and 669–677 nm. The results of this study could form a basis for developing mitigation measures for algal overgrowth.