Analysis of reflectance spectra of tropical seagrass species and their value for mapping using multispectral satellite images

ABSTRACT

Mapping of the distribution of individual seagrass species is essential for any attempts to manage seagrass ecosystems. It is therefore important to understand how the spectra of different seagrass species vary, in order to establish their unique absorption features and how these can be utilised for mapping by making use of remote-sensing images. This paper presents measurements of the reflectance spectra between 400 and 900 nm for nine tropical species of seagrass. Continuum removal and multispectral resampling procedures were applied to the spectra. Dendrogram analysis was carried out to identify species clustering as the basis for a mapping scheme. Spectral Angle Mapper (SAM) and Spectral Information Divergence (SID) approaches were employed for the classification of seagrass species using WorldView-2 images and measured spectra as the input endmember. Classification Tree Analysis (CTA) and an image segmentation approach using CTA (Object-Based Image Analysis – OBIA) were performed as a means of comparison. The results indicate that the absorption features and overall shape of the spectra for all seagrass species are relatively similar, and implied that the major differences are attributable to the absolute reflectance values. Consequently, SAM and SID produced results of low accuracy (<30%), whereas, CTA and OBIA delivered results exhibiting higher accuracy (60–92%). The use of a spectral-based classification algorithm was ineffective for the classification and mapping of seagrass species using multispectral images. The utilisation of absolute reflectance values was beneficial for the classification of seagrass species having similar spectral shape.

Acknowledgements

This research is funded by “Direktorat Riset dan Pengabdian Masyarakat – Direktorat Jenderal Penguatan Riset dan Pengembangan – Kementerian Riset, Teknologi, dan Pendidikan Tinggi Republik Indonesia” via Penelitian Dasar Unggulan Perguruan Tinggi – PDUPT Scheme Grant Number 153/UN1/DITLIT/DIT-LIT/LT/2018.

Disclosure statement

No potential conflict of interest was reported by the authors.