CoMMa: a GIS geomorphometry toolbox to map and measure confined landforms

Arosio, Riccardo; Gafeira, Joana; De Clippele, Laurence H.; Wheeler, Andrew J.; Huvenne, Veerle A.I.; Sacchetti, Fabio; Conti, Luis A.; Lim, Aaron. 2024 CoMMa: a GIS geomorphometry toolbox to map and measure confined landforms. Geomorphology, 458, 109227. 10.1016/j.geomorph.2024.109227

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Abstract/Summary

The Confined Morphologies Mapping (CoMMa) Toolbox, a novel ArcGIS Pro python toolbox expressly created for semi-automated seabed morphological mapping, is presented here. The toolbox includes a selection of tools for the pre-processing, delineation and description of confined features on a digital elevation model (DEM) that are either negative or positive. The CoMMa Toolbox addresses the need for a flexible and multi-faceted solution applicable to different mapping problems, also encapsulating and re-interpreting existing methodologies. This study also evaluates, qualitatively and quantitatively, the performance of CoMMa delineations performed on a synthetic bathymetry DEM with 150 coral mounds of known characteristics against manual digitisations completed by five expert geomorphologists. The results show that the best CoMMa delineation falls within the range of competence demonstrated by the expert manual mappers. Edge evaluation metrics and attribute error scores are comparable or often superior to four of the five human delineations, although the Toolbox never reaches the performance of the best expert. Nevertheless, the semi-automated techniques can be of assistance to any user, providing rapid, visually unbiased and consistent delineations, thus saving time: they can then be optimised manually where desirable. Moreover, while the toolbox was created for marine geomorphometry, it can be applied to any DEM, either marine, terrestrial or extra-terrestrial. The CoMMa Toolbox is available in a public GitHub repository with a thorough user guide.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	10.1016/j.geomorph.2024.109227
ISSN:	0169555X
Date made live:	05 Aug 2024 10:32 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/537797

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