Automatic Detection of Trawl-Marks in Sidescan Sonar Images through Spatial Domain Filtering, Employing Haar-Like Features and Morphological Operations

Charikleia Gournia,David P Williams,George Papatheodorou,Elias Fakiris,Maria Geraga

doi:10.3390/geosciences9050214

Charikleia Gournia, David P Williams + Show 3 more

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https://doi.org/10.3390/geosciences9050214

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Abstract

Bottom trawl footprints are a prominent environmental impact of deep-sea fishery that was revealed through the evolution of underwater remote sensing technologies. Image processing techniques have been widely applied in acoustic remote sensing, but accurate trawl-mark (TM) detection is underdeveloped. The paper presents a new algorithm for the automatic detection and spatial quantification of TMs that is implemented on sidescan sonar (SSS) images of a fishing ground from the Gulf of Patras in the Eastern Mediterranean Sea. This method inspects any structure of the local seafloor in an environmentally adaptive procedure, in order to overcome the predicament of analyzing noisy and complex SSS images of the seafloor. The initial preprocessing stage deals with radiometric inconsistencies. Then, multiplex filters in the spatial domain are performed with multiscale rotated Haar-like features through integral images that locate the TM-like forms and additionally discriminate the textural characteristics of the seafloor. The final TMs are selected according to their geometric and background environment features, and the algorithm successfully produces a set of trawling-ground quantification values that could be established as a baseline measure for the status assessment of a fishing ground.

Highlights

Protecting marine environments is a matter of great scientific and socio-economic concern [1,2,3,4].Over the last decades, the progression of remote sensing has brought to light widespread anthropogenic effects on the seafloor [5,6], caused mainly by fishing, mineral extraction and marine pollution [7].An emergent theme that has aroused a growing degree of interest is bottom trawling, a method of fishing involving the pull of trawl nets and trawl doors through the seafloor in order to catch bottom-living fish
These biogenic mounds are quite similar to the coralline algae reefs that have been reported in the Eastern Mediterranean Sea (Aegean Sea) by the authors of [13]
The results reveal that the design of the algorithm overcomes the aforementioned limitations, achieving high accuracy in TMs detection and decreasing the false alarm rates

Summary

Introduction

Protecting marine environments is a matter of great scientific and socio-economic concern [1,2,3,4].Over the last decades, the progression of remote sensing has brought to light widespread anthropogenic effects on the seafloor [5,6], caused mainly by fishing, mineral extraction and marine pollution [7].An emergent theme that has aroused a growing degree of interest is bottom trawling, a method of fishing involving the pull of trawl nets and trawl doors through the seafloor in order to catch bottom-living fish. The progression of remote sensing has brought to light widespread anthropogenic effects on the seafloor [5,6], caused mainly by fishing, mineral extraction and marine pollution [7]. Trawl-fishing could lead to benthic habitat degradation with consequent ecosystem alteration [8,9]. Direct contact of trawling nets and trawl doors with the seafloor scraps the seafloor and leaves scars in pairs, causing sediment suspension [10,11]. Bottom trawling has destructive effects on priority habitats (e.g., coral community, coralligenous formations, seagrass beds) which are targets for conservation actions [12,13,14]. Marine geoarchaeological sites have been heavily impacted by trawl-fishing [15,16]. The amount of the damage done depends on the spatial extent and Geosciences 2019, 9, 214; doi:10.3390/geosciences9050214 www.mdpi.com/journal/geosciences

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