Marine ecosystem monitoring requires observations of its attributes at different spatial and temporal scales that traditional sampling methods (e.g., RGB imaging, sediment cores) struggle to efficiently provide. Proximal optical sensing methods can fill this observational gap by providing observations of, and tracking changes in, the functional features of marine ecosystems non-invasively. Underwater hyperspectral imaging (UHI) employed in proximity to the seafloor has shown a further potential to monitor pigmentation in benthic and sympagic phototrophic organisms at small spatial scales (mm–cm) and for the identification of minerals and taxa through their finely resolved spectral signatures. Despite the increasing number of studies applying UHI, a review of its applications, capabilities, and challenges for seafloor ecosystem research is overdue. In this review, we first detail how the limited band availability inherent to standard underwater cameras has led to a data analysis “bottleneck” in seafloor ecosystem research, in part due to the widespread implementation of underwater imaging platforms (e.g., remotely operated vehicles, time-lapse stations, towed cameras) that can acquire large image datasets. We discuss how hyperspectral technology brings unique opportunities to address the known limitations of RGB cameras for surveying marine environments. The review concludes by comparing how different studies harness the capacities of hyperspectral imaging, the types of methods required to validate observations, and the current challenges for accurate and replicable UHI research.

Quantifying the structural complexity provided by biogenic habitat structures is important in ecology, conservation and management, and yet remains a challenging task, particularly in deep sea and polar environments, that current photogrammetry tools can alleviate. In this study, we demonstrate how small remotely operated vehicles and compact underwater GoPro® action cameras can be easily integrated into coastal Antarctic surveys to quantify structural complexity of under‐ice benthos via underwater photogrammetry. Forty‐four pairs of 1 m2 quadrats at 1 cm resolution, each comprising an orthomosaic and three‐dimensional reconstructions, were analyzed to describe relationships between benthic cover and structural complexity metrics. The study case provided insights into a unique biogenic habitat, highlighting the role of integrating structural complexity metrics in Antarctic benthic surveys. Although no clear relationships between structural complexity and biodiversity were found, high cover of live reef‐building polychaetes was associated with higher levels of structural complexity, particularly fractal dimension (D). Further, broken biogenic structures, product of disturbance events retain habitat structural complexity known to be associated with larvae settlement and biogenic reef growth. This suggests that D can be used as a metric for detecting subtle changes in biogenic structural complexity. We build from available open‐source code, a reproducible scientific workflow that is expected to facilitate the acquisition and analysis of structural complexity metrics. The workflow presented aims to encourage and accelerate the use of photogrammetry tools for benthic studies aiming to quantify biogenic structural complexity across depths and latitudes.