Enhancing benthic habitat mapping: A review of integrating satellite and side scan sonar data for improved classification accuracy - Yeong, Wei Yi; Chong, Wei Sheng; Ching Hue; Imelus Nius (e-VIBS, Faculty of Science and Natural Resources, 2024)
Prevalent challenges persist within remote sensing techniques for benthic habitat mapping. While efforts are being made to improve mapping accuracy through combined remote sensing approaches, the synergistic use of satellite and side-scan sonar datasets to address the inherent limitations of spectral discrimination and geometric distortions in each method remains limited. This review focuses on exploring the latent potential inherent in the complementary properties of both datasets. An analysis of articles from the Scopus databases published between 2010 and 2023 has shown that different data inputs with classification techniques influence the accuracy of coral reef community mapping. The integration of acoustically derived data and/or bathymetric data with satellite imagery can influence mapping results to varying degrees. The addition of acoustic hardness to satellite imagery has unfortunately led to inaccuracies. The contribution of slope derived from bathymetry varies with extraction algorithms; the use of more sophisticated algorithms leads to higher accuracy. Research on classification methods shows that object-based approaches produce different results depending on field conditions, which are consistently better than pixel-based methods, for both satellite spectral and side-scan sonar data. This review not only highlights conceptual discoveries, but also provides recommendations for future research: (1) the need for comparative evaluation of classification algorithms to determine the optimal classifier; and (2) side-scan sonar-derived slope as a forcing factor to improve accuracy. It is also expected that the review will provide valuable insights into data and classification decisions regarding the use of satellite imagery and acoustic data in future coral reef community mapping.