Semi-Automatic Versus Manual Mapping of Cold-Water Coral Carbonate Mounds Located Offshore Norway

Alexandra Jarna,Valérie K Bellec,Sigrid Elvenes,Terje Thorsnes,Markus Diesing,Nicole J Baeten

doi:10.3390/ijgi8010040

Alexandra Jarna, Valérie K Bellec + Show 4 more

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https://doi.org/10.3390/ijgi8010040

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Abstract

Cold-water coral reefs are hotspots of biological diversity and play an important role as carbonate factories in the global carbon cycle. Reef-building corals can be found in cold oceanic waters around the world. Detailed knowledge on the spatial location and distribution of coral reefs is of importance for spatial management, conservation and science. Carbonate mounds (reefs) are readily identifiable in high-resolution multibeam echosounder data but systematic mapping programs have relied mostly on visual interpretation and manual digitizing so far. Developing more automated methods will help to reduce the time spent on this laborious task and will additionally lead to more objective and reproducible results. In this paper, we present an attempt at testing whether rule-based classification can replace manual mapping when mapping cold-water coral carbonate mounds. To that end, we have estimated and compared the accuracies of manual mapping, pixel-based terrain analysis and object-based image analysis. To verify the mapping results, we created a reference dataset of presence/absence points agreed upon by three mapping experts. There were no statistically significant differences in the overall accuracies of the maps produced by the three approaches. We conclude that semi-automated rule-based methods might be a viable option for mapping carbonate mounds with high spatial detail over large areas.

Highlights

Coral reefs, which are frequently associated with warm, shallow and photic tropical seas, are found widespread in deep waters of continental shelves, slopes, seamounts and ridge systems around the world [1]
Among a range of possible semi-automated methods of mapping carbonate mounds, we selected two for this study: Geographic Object-Based Image Analysis (GEOBIA) and classification based on terrain analysis of pixels (Figure 1)
Previous works [26,30,31] have suggested that suitable derivatives of bathymetry for classification of carbonate mounds are the slope, curvature and bathymetric positioning index (BPI)

Summary

Introduction

Coral reefs, which are frequently associated with warm, shallow and photic tropical seas, are found widespread in deep waters of continental shelves, slopes, seamounts and ridge systems around the world [1] Such cold-water coral (CWC) reefs are of high importance since they contribute to increased biodiversity [2], create suitable conditions for nurseries for fish larvae [3,4], provide food to many organisms [5,6] and act as carbonate factories [7,8]. CWC reefs are fragile and slow-growing three-dimensional structures that are vulnerable to various anthropogenic impacts, such as demersal fishing [9,10,11], mining [12], hydrocarbon drilling [13] and climate change (ocean warming [14] and acidification [6,15]). Glacial landforms, such as iceberg ploughmarks, drumlins and megascale glacial lineations may provide hard bottom substrates, which are frequently exposed to enhanced currents that carry food towards the reef structures [18,20]

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