A multi-method approach for benthic habitat mapping of shallow coastal areas with high-resolution multibeam data

Abstract

The coastal waters of the Maltese Islands, central Mediterranean Sea, sustain a diversity of marine habitats and support a wide range of human activities. The islands' shallow waters are characterised by a paucity of hydrographic and marine geo-environmental data, which is problematic in view of the requirements of the Maltese Islands to assess the state of their coastal waters by 2011 as part of the EU Marine Strategy Directive. Multibeam echosounder (MBES) systems are today recognised as one of the most effective tools to map the seafloor, although the quantitative characterisation of MBES data for seafloor and habitat mapping is still an underdeveloped field. The purpose of this *Manuscript Click here to download Manuscript: Manuscript.doc Click here to view linked References 2 study is to outline a semi-automated, Geographic Information System-based methodology to map the distribution of seafloor composition and morphology in shallow coastal waters using high-resolution MBES data. We test this methodology in a 28 km 2 area of Maltese coastal waters. Three data sets were collected from this study area: (i) MBES bathymetry and backscatter data; (ii) Remotely Operated Vehicle imagery and (iii) photographs and sediment samples from dive surveys. Our approach combines a suite of topographic and textural analytical techniques to map different types of seafloor morphologies and compositions at various scales. Topographic analyses, based on bathymetric data, classify the seabed into five morphological zones and features-flat and sloping areas, crests, depressions and breaks of slope-by using morphometric attributes, the Bathymetric Position Index and geomorphometric mapping. Textural analyses of backscatter and bathymetry data segment the seafloor into four classes-medium sand, maerl associated with sand and gravel, seagrass settled on sand and gravel, and seagrass settled on bedrock-using roughness estimation, TexAn analyses and supervised classification based on information from training stations. The resulting topographic and seabed composition maps were combined to plot the distribution of the predominant habitats in the coastal waters offshore the NE Malta, some of which are of high conservation value. Groundtruthing of the habitat map using ROV imagery and dive observations confirms that our approach produces a simplified and accurate representation of seafloor habitats in a quick and objective manner while using all the information available within MBES data sets.

A review of marine geomorphometry, the quantitative study of the seafloor

“…The more general term "multi-scale" is used in this paper to refer to both types of analysis as well as geomorphometric analysis using data of different resolutions. (Lundblad et al, 2006;Lanier et al, 2007;Micallef et al, 2012a;Dolan and Lucieer, 2014) Aspect (Galparsoro et al, 2009), northness/northerness and eastness/easterness (Monk et al, 2011) Mean curvature (Dolan et al, 2008); profile curvature (Guinan et al, 2009); plan/planimetric curvature (Ross et al, 2015); Bathymetric Position Index (BPI) (Monk et al, 2010;Pirtle et al, 2015) Rugosity (Dunn and Halpin, 2009); vector ruggedness measure (VRM) (Tempera et al, 2012); relative relief (Elvenes, 2013); fractal dimension (Wilson et al, 2007) Commonly used terrain attribute and software (algorithm reference)…”

Acoustic mapping and classification of benthic habitat using unsupervised learning in artificial reef water

“…Acoustic habitat mapping has become a major tool for evaluating the status of coastal ecosystems. This technique is also commonly used in marine spatial planning, resource assessment and offshore engineering (Micallef et al, 2012). Traditional sampling methods can only provide a snapshot that covers a fraction of the seafloor area (Harper et al, 2010), while acoustic mapping technologies are capable of efficiently capturing images across large areas of the seabed (Huang et al, 2014).…”

“…Conventionally, MBES data sets of seabed geological features have been manually interpreted by experts or using simplified substrate classification methods developed for single beam echosounder. Recently developed quantitative computational techniques can transform spatially complex bathymetric and backscatter data of large areas into simple, easily visualized maps that provide the end users with abundant information (Micallef et al, 2012). Driven by the advances in objective classification algorithms, a variety of automated methods have been developed and tested (Brown et al, 2011).…”

PILOT APPLICATION OF 3D UNDERWATER IMAGING TECHNIQUES FOR MAPPING POSIDONIA OCEANICA (L.) DELILE MEADOWS

“…Moreover, underwater imaging is an important tool to understand geological and biological processes taking place on the seafloor, providing scientists with high levels of detail and the ease of interpretation. Underwater 3D mapping has normally been carried out by acoustic multibeam sensors or side scan sonar (Paul et al, 2011;Micallef et al, 2012;Montefalcone et al, 2013;Campos et al, 2014). However, the information provided by acoustic devices is normally gathered in the form of elevation maps, which are useful for providing a rough approximation of the global shape of the area, but are inadequate for detecting more complex structures, (Campos et al, 2014).…”