Abstract
We developed a novel integrated technology for diver-operated surveying of shallow marine ecosystems. The HyperDiver system captures rich multifaceted data in each transect: hyperspectral and color imagery, topographic profiles, incident irradiance and water chemistry at a rate of 15–30 m2 per minute. From surveys in a coral reef following standard diver protocols, we show how the rich optical detail can be leveraged to generate photopigment abundance and benthic composition maps. We applied machine learning techniques, with a minor annotation effort (<2% of pixels), to automatically generate cm-scale benthic habitat maps of high taxonomic resolution and accuracy (93–97%). The ability to efficiently map benthic composition, photopigment densities and rugosity at reef scales is a compelling contribution to modernize reef monitoring. Seafloor-level hyperspectral images can be used for automated mapping, avoiding operator bias in the analysis and deliver the degree of detail necessary for standardized environmental monitoring. The technique can deliver fast, objective and economic reef survey results, making it a valuable tool for coastal managers and reef ecologists. Underwater hyperspectral surveying shares the vantage point of the high spatial and taxonomic resolution restricted to field surveys, with analytical techniques of remote sensing and provides targeted validation for aerial monitoring.
Highlights
The need to efficiently monitor marine and freshwater ecosystems is more urgent than ever for their effective conservation and resource management[1, 2]
Our study demonstrates that underwater hyperspectral imaging provides significant and direct benefits for coral reef surveys
The hyperspectral reflectance of various benthic targets contains several signatures that are useful to assess taxonomic identity or physiological status[35]. Capturing this information across large reef areas enables analyses that can provide rich descriptions of reef habitats in a scalable and non-invasive manner. These benefits suggest that, given the costs and efforts involved in underwater surveys, collection of underwater hyperspectral imagery will represent a significant improvement in the informational throughput of reef survey efforts without significant disruption of existing monitoring schemes
Summary
The need to efficiently monitor marine and freshwater ecosystems is more urgent than ever for their effective conservation and resource management[1, 2]. While direct visual surveys provide accurate observations, they can only cover a limited reef area under typical logistical constraints They require extensive field time, are affected by the biases of the ecologist’s expertise, and do not generate a lasting record of the habitat structure for re-analysis. The resulting large data sets[15] have shifted the bottleneck of generating results to the analysis of large collections of survey images to identify reef substrata/organisms[16, 17]. Such analysis typically entails sub-sampling the high-resolution images and visual identification by experts to estimate benthic coverage[18, 19]. Other efforts have explored the use of spectral filtering to estimate benthic coverage[24, 25]
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