Morphometric parameters of the Squid Mounds (SQM), Namibian coral mound province

Quantitative morphometric analyses were carried out for each mound following the workflows presented by Purkis et al. (2007) The coral mound base was defined following the methodological approach of Correa et al. (2012) using the dip angle map, generated from the digital elevation model (DEM), to extract closed polygons that follow the 3°-contour line. This 3°-cutoff has been qualitatively validated with a comparison between the DEM and the dip angle (Fig. 2). Small-scaled polygons within mound perimeters and resulting from bathymetric artifacts were filtered out. Manual editing was applied to split simple merged mound structures (e.g. twin-peak mounds) based on higher cut-off slope values (4-5°). Furthermore, polygons describing the mound footprint have been corrected to remove unrealistic shapes especially common for the CBM. The DEM was subsequently re-gridded to generate hypothetical bathymetric maps without mounds, for which the vertical relief beneath each removed mound was interpolated from the mound perimeters. The newly interpolated surfaces were then subtracted from the original DEMs to evaluate the volume and heights of the coral mounds. Only features with a footprint area greater than 900 squared meters (corresponding to a two-dimensional array of 3 × 3 DEM grid cells) and with a height of >2 m above the surrounding seafloor (4 × 0.5 m of vertical precision) were considered as coral mounds and quantitatively analyzed.

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Cite this as

Tamborrino, Leonardo, Purkis, Sam, Hebbeln, Dierk (2022). Dataset: Morphometric parameters of the Squid Mounds (SQM), Namibian coral mound province. https://doi.org/10.1594/PANGAEA.944627

DOI retrieved: 2022

Additional Info

Field Value
Imported on November 30, 2024
Last update November 30, 2024
License CC-BY-4.0
Source https://doi.org/10.1594/PANGAEA.944627
Author Tamborrino, Leonardo
Given Name Leonardo
Family Name Tamborrino
More Authors
Purkis, Sam
Hebbeln, Dierk
Source Creation 2022
Publication Year 2022
Resource Type text/tab-separated-values - filename: SQM_quantitative_morphometric_analyses
Subject Areas
Name: BiologicalClassification

Name: Ecology

Related Identifiers
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