Geomorphological evolution of coastal landslides in Malta: integration of terrestrial and marine datasets

The paper shows the main results of multidisciplinary research carried out in the Island of Malta aiming at the integration of terrestrial and marine datasets. Identification, mapping, monitoring and dating of landslides, including submerged ones, have enabled to define a time frame for the development of landslides and to reconstruct the geomorphological evolution of the investigated areas. This has provided useful means for landslide susceptibility and hazard mapping, which is crucial for north-west coast of Malta

Integrated Geomorphological Mapping of Emerged and Submerged Coastal Areas based on the Coupling of Terrestrial and Marine Datasets

A deeper understanding of the processes acting on the coastal areas is crucial for coastal hazard assessment and mapping. To this aim, integrated geomorphological investigations of emerged and submerged areas resulting in geomorphological mapping represent an innovative way to provide the necessary knowledge for preventing hazards and reducing risks. An example is provided from the north-western coast of Malta (central Mediterranean Sea)

Acoustic textures and multibeam mapping of shallow marine habitats - Examples from Eastern Malta

Multibeam sonars are now used in increasingly shallower waters, bringing very high resolution imagery and bathymetry from often very varied seabeds. These developments have been associated with technological challenges, such as the adaptation of systems designs for deeper waters to more restricted ranges, often with multiple reflections. They have also brought a step change in acoustic mapping, with at least an order of magnitude in resolutions now attainable, coupled with a higher susceptibility to small-scale variations. This paper will investigate how these changes affect seafloor classification, focusing on the role of acoustic textures of shallow habitats. Maps of marine habitats have several purposes, from ecological (ecosystem health monitoring, marine-protected areas) to socio-economic (resource accessibility and sustainability, changes brought by pollution or offshore activities). Classifications must therefore successfully address the relevant types of information. This will be presented using a high-resolution multibeam dataset acquired on the eastern coast of the island of Malta in May 2012, in water depths of 1.5-400 m. The 70-100 kHz Kongsberg EM710 multibeam echosounder was deployed over diverse terrains including horst and graben alternations, seagrass cover in some areas, gravel and different sediment types. After full processing, the dataset provides multibeam backscatter at 1-m resolution and bathymetry at 2-m resolution, supplemented with photographic ground truth and samples at appropriate locations. The results of acoustic texture analyses will be presented in the context of data acquisition choices (e.g. pulse lengths, survey speeds), terrain morphology (role of slopes and large-scale types) and multi-scale terrain variability (bathymetry and backscatter)

Advanced SAR interferometric analysis to support geomorphological interpretation of slow-moving coastal landslides (Malta, Mediterranean Sea)

An advanced SAR interferometric analysis has been combined with a methodology for the automatic classification of radar reflectors phase histories to interpret slope-failure kinematics and trend of displacements of slow-moving landslides. To accomplish this goal, the large dataset of radar images, acquired in more than 20 years by the two European Space Agency (ESA) missions ERS-1/2 and ENVISAT, was exploited. The analysis was performed over the northern sector of Island of Malta (central Mediterranean Sea), where extensive landslides occur. The study was assisted by field surveys and with the analysis of existing thematic maps and landslide inventories. The outcomes allowed definition of a model capable of describing the geomorphological evolution of slow-moving landslides, providing a key for interpreting such phenomena that, due to their slowness, are usually scarcely investigated

Landslide susceptibility analysis exploiting Persistent Scatterers data in the northern coast of Malta

During the last decade a pressing need for more adequate tools to manage the considerable increasing number of hydrogeological emergencies arose among land planning and civil protection authorities. As a consequence, both development and testing of different qualitative and quantitative methods for landslide displacements detection become fundamental in order to provide the best analysis performance in terms of cost-benefit and scientific reliability. Lately quantitative methods to measure deformations of unstable slopes had great advances. In this context, remotely sensed radar techniques, such as PSI (Persistent Scatterers Interferometry), can assist traditional landslide investigations in assessing ground and infrastructure deformations caused by large landslides. The main purpose of this study is exploiting the results of PSI analysis conducted over the Island of Malta to train a Bayesan model for evaluating active landslide susceptibility. This approach has been applied in the NW coast of Malta, where outstanding coastal landslides, such as rock spreads and block slides, have been recognized and mapped. The outcomes of the statistical analysis have been validated through specific field check and GNSS measurements. The results show that the developed susceptibility model predicts an acceptable percentage of landslides and can be considered reliable even if in areas without PSI data

Landslide susceptibility modeling assisted by Persistent Scatterers Interferometry (PSI): an example from the northwestern coast of Malta

Persistent Scatterers Interferometry (PSI) techniques are widely employed in geosciences to detect and monitor landslides with high accuracy over large areas, but they also suffer from physical and technological constraints that restrict their field of application. These limitations prevent us from collecting information from several critical areas within the investigated region. In this paper, we present a novel approach that exploits the results of PSI analysis for the implementation of a statistical model for landslide susceptibility. The attempt is to identify active mass movements by means of PSI and to avoid, as input data, time-/cost-consuming and seldom updated landslide inventories. The study has been performed along the northwestern coast of Malta (central Mediterranean Sea), where the peculiar geological and geomorphological settings favor the occurrence of a series of extensive slow-moving landslides. Most of these consist in rock spreads, evolving into block slides, with large limestone blocks characterized by scarce vegetation and proper inclination, which represent suitable natural radar reflectors for applying PSI. Based on geomorphometric analyses and geomorphological investigations, a series of landslide predisposing factors were selected and a susceptibility map created. The result was validated by means of cross-validation technique, field surveys and global navigation satellite system in situ monitoring activities. The final outcome shows a good reliability and could represent an adequate response to the increasing demand for effective and lowcost tools for landslide susceptibility assessment

Habitat mapping of the Maltese continental shelf using acoustic textures and bathymetric analyses

The uneven mapping of the Maltese continental shelf precludes a full assessment of its marine habitats, important for their monitoring and conservation in line with the EU Marine Strategy Framework Directive and local initiatives. From 2009 to 2012, high-resolution multibeam echosounder (MBES) surveys offshore the NW and E coasts of the Maltese archipelago were carried out, covering a total area of 1,408.3 km2 with a maximum resolution of 1 m, at depths from 1.5 to 263 m. The types of benthic habitats occurring on the continental shelf often showed subtle acoustic variations. This article aims at 1) integrating analyses of the bathymetry and acoustic textures with ground-truthing (grab samples) in key areas; 2) validating this combined approach by rewriting an existing benthic habitat map of the eastern continental shelf of Malta; 3) exploiting this ground-truthed classification to calibrate an unsupervised classification of a dataset acquired with a different sonar. The main results obtained from these analyses are i) a sediment map of the continental shelf of NW Malta and east of the Maltese archipelago – classifying in detail bedrock, rocky blocks, coarse sand and gravel, fine to medium sand and maërl, sand and gravel – that supports the geomorphological interpretation of the seabed features; ii) an automatic classification of the seafloor morphology, highlighting a very gentle sloping seabed crossed by the shelf break and by palaeo-river valleys; iii) the first full benthic habitat map of the continental shelf offshore E and NW coast of Malta obtained with a semi-automatic classification. In this work, we highlight and explain the main differences in seafloor sediment coverage, its morphology and the relative occurrences of benthic habitats between the NW and E sides of the Maltese archipelago

Benthic habitat map of the southern Adriatic Sea (Mediterranean Sea) from object-based image analysis of multi-source acoustic backscatter data

© The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Prampolini, M., Angeletti, L., Castellan, G., Grande, V., Le Bas, T., Taviani, M., & Foglini, F. Benthic habitat map of the southern Adriatic Sea (Mediterranean Sea) from object-based image analysis of multi-source acoustic backscatter data. Remote Sensing, 13(15), (2021): 2913, https://doi.org/10.3390/rs13152913.A huge amount of seabed acoustic reflectivity data has been acquired from the east to the west side of the southern Adriatic Sea (Mediterranean Sea) in the last 18 years by CNR-ISMAR. These data have been used for geological, biological and habitat mapping purposes, but a single and consistent interpretation of them has never been carried out. Here, we aimed at coherently interpreting acoustic data images of the seafloor to produce a benthic habitat map of the southern Adriatic Sea showing the spatial distribution of substrates and biological communities within the basin. The methodology here applied consists of a semi-automated classification of acoustic reflectivity, bathymetry and bathymetric derivatives images through object-based image analysis (OBIA) performed by using the ArcGIS tool RSOBIA (Remote Sensing OBIA). This unsupervised image segmentation was carried out on each cruise dataset separately, then classified and validated through comparison with bottom samples, images, and prior knowledge of the study areas.This research was funded by EUROSTRATAFORM (EC contract no. EVK3-CT-2002-00079), EU-FP-VI HERMES (GOCE-CT-2005-511234-1), EU-FP-VII HERMIONE (contract no. 226354) and COCONET (Grant agreement no: 287844); Convenzione MATTM-CNR per i Programmi di Monitoraggio per la Direttiva sulla Strategia Marina (MSFD, Art. 11, Dir. 2008/56/CE); Italian Flag Project Ritmare (Ricerca Italiana per il Mare); MAGIC (Accordo di Programma Quadro Consiglio Nazionale delle Ricerche—CNR, Dipartimento della protezione civile della Presidenza del Consiglio dei Ministri); MIUR-PRIN 2009 “Carbonate conduits linked to hydrocarbons enriched seepages” and MIUR-PRIN 2017 GLIDE 2017FREXZY. This paper contributes to H2020 Projects EVER-EST (Grant agreement no: 674907) and RELIANCE (Grant agreement no: 101017501). This is ISMAR-CNR contribution number 1975