Improved predictive modelling of coralligenous formations in the Greek Seas incorporating large-scale, presence–absence, hydroacoustic data and oceanographic variables

Our understanding of the distribution of coralligenous formations, throughout but mostly on the Eastern Mediterranean seafloor, is still poor and mostly relies on presence-only opportunistic trawling and fishermen reports. Previous efforts to gather this information created relevant geodatabases that led to a first draft predictive spatial distribution of coralligenous formations in the Mediterranean Sea using habitat suitability modelling techniques. In the last few decades, the use of hydroacoustics to map the seafloor for various geotechnical and habitat mapping projects accumulated high amounts of detailed spatial information about these formations, which remains majorly unexploited. Repurposing these datasets towards mapping key habitats is a valuable stepping stone to implementing the EU Habitat Directive. In Greece, a unique volume of seafloor mapping data has been gathered by the Laboratory of Marine Geology and Physical Oceanography, Geology Department, University of Patras. It accounts for more than 33 marine geophysical expeditions during the last three decades, having collected hydroacoustic data for a total seafloor area of 3,197.68 km2. In the present work, this information has been curated, re-evaluated, and archived to create the most complete, until now, atlas of coralligenous formations in the Greek Seas and the only integrating presence–absence data. This atlas has been used to train and validate a predictive distribution model, incorporating environmental variables derived from open data repositories, whose importance has been assessed and discussed. The final output is an improved probability map of coralligenous formation occurrence in the Greek Seas, which shall be the basis for effective spatial planning, gap detection, and design of future mapping and monitoring activities on this priority habitat

Multi-frequency, multi-sonar mapping of shallow habitats – Efficacy and management implications in the National Marine Park of Zakynthos, Greece

In this work, multibeam echosounder (MBES) and dual frequency sidescan sonar (SSS) data are combined to map the shallow (5⁻100 m) benthic habitats of the National Marine Park of Zakynthos (NMPZ), Greece, a Marine Protected Area (MPA). NMPZ hosts extensive prairies of the protected Mediterranean phanerogams Posidonia oceanica and Cymodocea nodosa, as well as reefs and sandbanks. Seafloor characterization is achieved using the multi-frequency acoustic backscatter of: (a) the two simultaneous frequencies of the SSS (100 and 400 kHz) and (b) the MBES (180 kHz), as well as the MBES bathymetry. Overall, these high-resolution datasets cover an area of 84 km2 with ground coverage varying from 50% to 100%. Image texture, terrain and backscatter angular response analyses are applied to the above, to extract a range of statistical features. Those have different spatial densities and so they are combined through an object-based approach based on the full-coverage 100-kHz SSS mosaic. Supervised classification is applied to data models composed of operationally meaningful combinations between the above features, reflecting single-sonar or multi-sonar mapping scenarios. Classification results are validated against a detailed expert interpretation habitat map making use of extensive ground-truth data. The relative gain of one system or one feature extraction method or another are thoroughly examined. The frequency-dependent separation of benthic habitats showcases the potentials of multi-frequency backscatter and bathymetry from different sonars, improving evidence-based interpretations of shallow benthic habitats

An Automatic Target Detection Algorithm for Swath Sonar Backscatter Imagery, Using Image Texture and Independent Component Analysis

In the present paper, a methodological scheme, bringing together common Acoustic Seabed Classification (ASC) systems and a powerful data decomposition approach, called Independent Component Analysis (ICA), is demonstrated regarding its suitability for detecting small targets in Side Scan Sonar imagery. Traditional ASC systems extract numerous texture descriptors, leading to a large feature vector, the dimensionality of which is reduced by means of data decomposition techniques, usually Principal Component Analysis (PCA), prior to classification. However, in the target detection issue, data decomposition should point towards finding components that represent sub-ordinary image information (i.e., small targets) rather than a dominant one. ICA has long been proved to be suitable for separating targets from a background, and this study represents a novel exhibition of its applicability to Side Scan Sonar (SSS) images. The present study attempts to build a fully automated target detection approach that combines image based feature extraction, ICA, and unsupervised classification. The suitability of the proposed approach has been demonstrated using an SSS data-set containing more than 70 manmade targets, most of them metallic, validated through a marine magnetic survey or ground truthing inspection. The method exhibited very good performance as it was able to detect more than 77% of the targets and it produced less than seven false alarms per km2. Moreover, it was compared to cases where, in the exact same methodological scheme, no decomposition technique is used, or PCA is employed instead of ICA, achieving the highest detection rate, but, more importantly, producing more than six times less false alarms, thus proving that ICA successfully manages to maximize target to background separation

Developing software tools for the processing and analysis of marine geophysical data: Applications to the gulf of Corinth and to the Aegean and Ionean seas

The present PhD thesis is a combinational research product concerning the development of software tools for the processing and analysis of marine geophysical data and their application to original data, collected by the Laboratory of Marine Geology and Physical Oceanography (L.M.G.P.O), university of Patras, Greece, during the period 2005-2011. The fields that this thesis focuses on are: 1) the Acoustic Seabed Classification Systems and 2) the mapping and quantification of very important marine habitats that specifically are the Posidonia Oceanica Prairies and the Coralline formations in the Aegean and Ionian seas. The software tools SonarClass and TargAn, that respectively refer to the Acoustic Seabed Classification and the quantification of Regions Of Interest in swath sonar imagery are presented and applied to the cases of Posidonia Oceanica in Zakinthos Isl. (Ionian Sea) and Coralline formations in Cyclades Isl. (Aegean Sea). Additionally and extending the range of the research products of this thesis, other software tools that are presented are: 1) the SBP-Im-An for the recreation (georeferencing and digitization) of old analog Sub Bottom Profiler recordings, 2) the MagLevel for the tie line leveling of marine geomagnetic data and 3) the PGStat for the quantification of trawl marks in swath sonar imagery, all of them with significant applications to original data. This thesis demonstrates originality due to both the development of new methods for the analysis and processing of marine geophysical data and the applications to study areas with particular environmental interest and research fields for which the attention of the marine scientists is at its peak.Η παρούσα διδακτορική διατριβή αποτελεί ένα συνδυαστικό ερευνητικό προϊόν που στοιχειοθετείται από την ανάπτυξη υπολογιστικών εργαλείων επεξεργασίας και ανάλυσης θαλάσσιων γεωφυσικών δεδομένων και την εφαρμογή τους σε πρωτογενή δεδομένα, συλλεγμένα από το Εργαστήριο Θαλάσσιας Γεωλογίας και Φυσικής Ωκεανογραφίας (Ε.ΘΑ.ΓΕ.Φ.Ω) του πανεπιστημίου Πατρών, κατά το διάστημα 2005 – 2011. Τα πεδία στα οποία συγκεντρώνεται το κέντρο βάρους της διατριβής είναι: 1) τα συστήματα ακουστικής ταξινόμησης πυθμένα και 2) η χαρτογράφηση και παραμετροποίηση εμφανίσεων των πολύ σημαντικών θαλάσσιων ενδιαιτημάτων της Ποσειδώνιας και των κοραλλιογενών σχηματισμών στο Ιόνιο και στο Αιγαίο πέλαγος. Έτσι αναπτύχθηκαν και παρουσιάστηκαν εκτενώς τα λογισμικά εργαλεία SonarClass και TargAn, που αναφέρονται αντίστοιχα στην αυτόματη ακουστική ταξινόμηση πυθμένα και την παραμετροποίηση περιοχών ενδιαφέροντος σε εικόνες ηχοβολιστών ευρείας σάρωσης και εφαρμόστηκαν για την χαρτογράφηση λειμώνων Ποσειδώνιας στη Ζάκυνθο και κοραλλιογενών σχηματισμών (τραγάνας) στις Κυκλάδες νήσους. Παράλληλα και επεκτείνοντας το εύρος των ερευνητικών προϊόντων αυτής της διατριβής, αναπτύχθηκαν επίσης: 1) το λογισμικό SBP-Im-An για τη γεωαναφορά και ψηφιοποίηση παλαιών αναλογικών καταγραφών τομογράφων υποδομής πυθμένα, 2) το λογισμικό χωροστάθμησης θαλάσσιων γεωμαγνητικών δεδομένων MagLevel και 3) το λογισμικό ποσοτικοποίησης αλιευτικών ιχνών σε δεδομένα ηχοβολιστών ευρείας σάρωσης PgStat, με αντίστοιχες σημαντικές εφαρμογές σε πρωτογενή δεδομένα. Η παρούσα διατριβή επιδεικνύει πρωτοτυπία τόσο σε επίπεδο ανάπτυξης νέων μεθόδων ανάλυσης και επεξεργασίας γεωφυσικών δεδομένων όσο και σε επίπεδο παρουσίασης εφαρμογών τους σε περιοχές μελέτης με ιδιαίτερο περιβαλλοντικό ενδιαφέρον αλλά και σε πεδία έρευνας για τα οποία το ενδιαφέρον της σύγχρονης θαλάσσιας επιστημονικής κοινότητας βρίσκεται στο απόγειό του

An Automatic Target Detection Algorithm for Swath Sonar Backscatter Imagery, Using Image Texture and Independent Component Analysis

In the present paper, a methodological scheme, bringing together common Acoustic Seabed Classification (ASC) systems and a powerful data decomposition approach, called Independent Component Analysis (ICA), is demonstrated regarding its suitability for detecting small targets in Side Scan Sonar imagery. Traditional ASC systems extract numerous texture descriptors, leading to a large feature vector, the dimensionality of which is reduced by means of data decomposition techniques, usually Principal Component Analysis (PCA), prior to classification. However, in the target detection issue, data decomposition should point towards finding components that represent sub-ordinary image information (i.e., small targets) rather than a dominant one. ICA has long been proved to be suitable for separating targets from a background, and this study represents a novel exhibition of its applicability to Side Scan Sonar (SSS) images. The present study attempts to build a fully automated target detection approach that combines image based feature extraction, ICA, and unsupervised classification. The suitability of the proposed approach has been demonstrated using an SSS data-set containing more than 70 manmade targets, most of them metallic, validated through a marine magnetic survey or ground truthing inspection. The method exhibited very good performance as it was able to detect more than 77% of the targets and it produced less than seven false alarms per km2. Moreover, it was compared to cases where, in the exact same methodological scheme, no decomposition technique is used, or PCA is employed instead of ICA, achieving the highest detection rate, but, more importantly, producing more than six times less false alarms, thus proving that ICA successfully manages to maximize target to background separation

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

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

Τhe soundscape of the Inner Ionian Archipelago as evinced through the West Patraikos Gulf Ambient and Seismic Noise Monitoring Project

Impacts of man-made acoustic noise on the marine environment are associated to the frequency and timing of any activity as well as the distribution and abundance of marine life. Offshore commercial operations, shipping activities, energy exploration and pile driving add noise to the already established ambient noise levels. Attention has been raised by the years to the topic of underwater noise and its effects on marine life, but the effects of underwater noise are not yet fully understood. As the adoption of the European Marine Directive (MSFD 2008/56/EC - Descriptor 11) has given great impulse to the research in thisfield, governments, companies and institutes are working to specify the background ambient noise levels. Those studies have formed the guidelines and have set the protocols for performing safer offshore operations, which are adopted by the major energy companies. Hellenic Petroleum S.A. has undertaken a Marine Seismic Survey in West Patraikos Gulf waters in Greece between January and February 2016, which was coupled with an intensive sound noise monitoring program. Acoustic data were collected around Marine Protected Areas of the Inner Ionian Archipelago during three monitoring phases: 1) the pre-start, 2) theconcurrent and 3) the post-completion ones. Sound pressure levels (SPLs) were collected using drifting hydrophones deployed on a frequent schedule, spanning 1.5 months, collecting more than 130 hours of data. The ambient noise data gave insight into the footprints of the anthropogenic and biogenic factors on the soundscape of the Inner Ionian Archipelago. Most importantly, the recorded SPLs of the impulsive seismic and the continuous shipping noises were studied against the bearing and distance to the corresponding sound sources

Shallow Seafloor Litter: Tracking their Sources and Spatiotemporal Trends in the Presence of Oceanographic Drivers through efficient monitoring

Seafloor litter is the least exploited component of marine litter. The spatially variable distribution of their densities over time is a cumulative effect of sources’ intensities and natural drivers like wind/wave and current conditions in interaction with seafloor morphology. Making safe interpretations about the exact spatiotemporal distribution of benthic litter requires good knowledge of the local above-mentioned seafloor components. In this work, visual monitoring over 3 years of a shallow urbanized bay in Syros Island, Cyclades, Greece, was proved a reliable way to assess the intensity of litter sources along their coasts. It showcased that spatial ranges that are influenced mainly by the annual ocean dynamics should be treated with caution or even excluded from the analysis. There, intense litter fluxes over the year, hinder any effort to separate local anthropogenic littering intensity changes from natural litter input-output fluctuations. Towed underwater camera surveying and auxiliary bathymetric and swath sonar backscatter datasets were used to find links between the seafloor litter transport dynamics and the seabed micro- and macro-topography, finally indicating litter traps and sinks