Using hyperspectral imagery to investigate large-scale seagrass cover and genus distribution in a temperate coast

Kenneth Clarke,Andrew Mcgrath,Sam Gaylard,Alison Turner,Milena B Fernandes,Robert Daly,James Cameron,Megan Lewis,Andrew Hennessy

doi:10.1038/s41598-021-83728-6

Abstract

Seagrasses are regarded as indicators and first line of impact for anthropogenic activities affecting the coasts. The underlying mechanisms driving seagrass cover however have been mostly studied on small scales, making it difficult to establish the connection to seagrass dynamics in an impacted seascape. In this study, hyperspectral airborne imagery, trained from field surveys, was used to investigate broadscale seagrass cover and genus distribution along the coast of Adelaide, South Australia. Overall mapping accuracy was high for both seagrass cover (98%, Kappa = 0.93), and genus level classification (85%, Kappa = 0.76). Spectral separability allowed confident genus mapping in waters up to 10 m depth, revealing a 3.5 ratio between the cover of the dominant Posidonia and Amphibolis. The work identified the absence of Amphibolis in areas historically affected by anthropogenic discharges, which occasionally contained Posidonia and might be recovering. The results suggest hyperspectral imagery as a useful tool to investigate the interplay between seagrass cover and genus distribution at large spatial scales.

Highlights

Seagrasses are regarded as indicators and first line of impact for anthropogenic activities affecting the coasts
The analysis of genus spectral separability was performed on the highest quality portions of the imagery through the visual selection of reference sites, establishing separability under near ideal conditions
The benthic cover mapping had very high accuracy (98% overall accuracy, Kappa = 0.93), and the genus classification had high accuracy (85% overall accuracy, Kappa = 0.76)

Summary

Introduction

Seagrasses are regarded as indicators and first line of impact for anthropogenic activities affecting the coasts. These include among others opportunities for recreation, protection from erosion and sea level rise, carbon sequestration, offsetting of ocean acidification, and breeding and nursery habitat for economically important species[2,3,4] These functions and services are threatened by the high sensitivity of seagrasses to water q uality[5], exacerbated by their generally high level of connectivity with neighboring h abitats[6]. Remote sensing approaches provide an opportunity to inform management through integration of data at meaningful spatial scales, but mapping of subtidal seagrasses is hindered by many factors including water reflection, scattering and absorption of light[8]. Progress in remote sensing technology has provided a pathway to investigate these knowledge gaps, through increased spatial and spectral resolution associated with the development of multispectral and hyperspectral s ensors[17]

Methods

Results

Conclusion