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The Patras Gulf Pockmark field is located in shallow waters offshore Patras City (Greece) and is considered one of the most spectacular and best-documented fluid seepage activities in the Ionian Sea. The field has been under investigation since 1996, though surveying was partially sparse and fragmentary. This paper provides a complete mapping of the field and generates new knowledge regarding the fluid escape structures, the fluid pathways, their origin and the link with seismic activity. For this, data sets were acquired utilising high-resolution marine remote sensing techniques, including multibeam echosounders, side-scan sonars, sub-bottom profilers and remotely operated vehicles, and laboratory techniques focusing on the chemical composition of the escaping fluids. The examined morphometric parameters and spatial distribution patterns of the pockmarks are directly linked to tectonic structures. Acoustic anomalies related to the presence of gas in sediments and in the water column document the activity of the field at present and in the past. Methane is the main component of the fluids and is of microbial origin. Regional and local tectonism, together with the Holocene sedimentary deposits, appear to be the main contributors to the growth of the field. The field preserves evidence that earthquake activity prompts the activation of the field. [ABSTRACT FROM AUTHOR]

The primary objective of this research is to demonstrate advanced surveying methods and techniques for coastal erosion identification and monitoring in a densely human-populated coastline, the southern coastline of the Gulf of Patras (Greece), which diachronically suffers erosion problems expected to become worse in the forthcoming years due to climate change and human intervention. Its importance lies in the fact that it presents a robust methodology on how all modern scientific knowledge and techniques should be used in coastal erosion problems. The presented methods include the use of satellite and aerial photo imaging, shallow seabed bathymetry and morphology, sediment sampling, geotechnical investigations, as well as hydrodynamic modelling. The results are extensively analyzed in terms of their importance in coastal erosion studies and are cross-validated to define those areas most vulnerable to erosion. Towards this scope, the seabed erosion rate produced by hydrodynamic modelling is compared with the coastal vulnerability index (CVI) calculations performed in the examined area to identify which coastal zones are under a regime of intensive erosion. The results between the CVI and the seabed erosion rate appear to coincide in terms of the erosion potential, especially in zones where the vulnerability regime has been calculated as being high or very high, with the P. oceanica meadows playing an important role in reducing erosion. [ABSTRACT FROM AUTHOR]

Helike, the Achaean Dodecapolis capital, in the Corinth Gulf, Greece, was, according to historical sources, devastated and disappeared from sight during an earthquake followed by sea invasion on to land in 373/372 B.C. A marine remote sensing survey, which was carried out to examine a landslide following a 6.2 R earthquake in 1995, that affected the coastal and near-shore delta plain zone on which Helike stood, accompanied by onshore borehole data, enabled us to postulate the geological processes leading to the Helike catastrophe. Helike was initially leveled during a 6 to 6.7 R earthquake; it is postulated to have then submerged following a translational landslide caused by liquefaction. This Helike catastrophe model is consistent with historical sources and current views regarding the expected geological hazards magnitude in the Gulf. [ABSTRACT FROM AUTHOR]

In many remote-sensing applications, measured data are a strong function of the environment in which they are collected. This paper introduces a new context-dependent classification algorithm to address and exploit this phenomenon. Within the proposed framework, an ensemble of classifiers is constructed, each associated with a particular environment. The key to the method is that the relative importance of each object (i.e., data point) during the learning phase for a given classifier is controlled via a modulating factor based on the similarity of auxiliary environment features. Importantly, the number of classifiers to learn and all other associated model parameters are inferred automatically from the training data. The promise of the proposed method is demonstrated on classification tasks seeking to distinguish underwater targets from clutter in synthetic aperture sonar imagery. The measured data were collected with an autonomous underwater vehicle during several large experiments, conducted at sea between 2008 and 2012, in different geographical locations with diverse environmental conditions. For these data, the environment was quantified by features (extracted from the imagery directly) measuring the anisotropy and the complexity of the seabed. Experimental results suggest that the classification performance of the proposed approach compares favorably to conventional classification algorithms as well as state-of-the-art context-dependent methods. Results also reveal the object features that are salient for performing target classification in different underwater environments. [ABSTRACT FROM PUBLISHER]

A series of marine remote sensing and ground-truth surveys were carried out at NW Gulf of Patras (W. Greece). The same area was surveyed in 1971 by Throckmorton, Edgerton and Yalouris, who are among the pioneers in the application of remote sensing techniques to underwater archaeology. The researchers conducted a surface reconnaissance survey to locate the site where the Battle of Lepanto took place on 7 October 1571. Their remote sensing surveying resulted in a map of two "target" areas that showed promise as possible remnants of wrecks from that battle and proposed a ground truth survey for their identification and in the detection of two modern shipwrecks. The ground truth survey was never fulfilled. The objectives of our repeat surveys, which were completed 50 years later, were to relocate the findings of this pioneer survey with higher spatial and vertical resolution, to ground-truth the targets, fulfilling their investigation, and to interpret the newly collected data in the light of modern developments in marine geosciences. Our repeat surveys detected mound clusters and individual mounds referred to "target" areas. These mounds could be interpreted as the surface expression of mud and fluid expulsion from the underlying deformed soft sediments. The ground truth survey demonstrated that the tops of mounds represent biogenic mounds. The ROV survey did not show any indication of wreck remnants of the Battle of Lepanto within the two survey areas. The site formation processes of the two modern shipwrecks were also studied in detail. Two noticeable seafloor morphological features were detected around the wreck sites; field of small-sized pockmarks and seafloor depressions. We would like to dedicate this work to the memory of Peter Throckmorton and Harold E. Edgerton, who are among the pioneers in the formative years of underwater archaeology in Greece. [ABSTRACT FROM AUTHOR]

Marine geophysical data collected during an underwater natural and cultural heritage assessment survey along the coastal zone of Kefallinia Island in the Ionian Sea, Greece, showed among other seafloor features, the presence of a Roman shipwreck and its amphorae cargo on the seafloor. The study and analysis of the collected data demonstrated that: (i) sidescan sonar and chirp sub-bottom profiling systems, can successfully detect ancient shipwrecks and their amphorae cargo on the seafloor, (ii) the use of objective computer vision techniques in processing sidescan sonar seafloor images, is a valuable tool for the separation of potential ancient shipwreck targets from other seafloor features with similar acoustic signatures. Furthermore, a guideline for the data acquisition parameters that should be used to obtain optimal seafloor sonar images to maximize the separation of potential shipwreck targets from other seafloor features, is provided. The underwater sonar remote sensing techniques may also provide adequate indication regarding the amphorae hull stowage and its vulnerability to human activity in the area. The shipwreck is dated between 1st century BC and 1st century AD and is one of the largest found so far in the Mediterranean Sea, for that period. It is estimated that it was carrying about 6,000 amphorae. The amphorae cargo, visible on the seafloor, is in very good state of preservation and the shipwreck has the potential to yield a wealth of information about the shipping routes, trading, amphorae hull stowage and ship construction during the relevant period and is therefore considered to be of significant archaeological importance. • Ancient shipwreck underwater sonar remote sensing detection. • Automated target detection. • Acquisition parameters to obtain seafloor images to maximize the separation of wreck targets among other seafloor features. • Roman wrecks 1st century BC to 1st century AD, Mediterranean Sea. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]