In this study, we present a framework for seagrass habitat mapping in shallow (5–50 m) and very shallow water (0–5 m) by combining acoustic, optical data and Object-based Image classification. The combination of satellite multispectral images-acquired from 2017 to 2019, together with Unmanned Aerial Vehicle (UAV) photomosaic maps, high-resolution multibeam bathymetry/backscatter and underwater photogrammetry data, provided insights on the short-term characterization and distribution of Posidonia oceanica (L.) Delile, 1813 meadows in the Calabrian Tyrrhenian Sea. We used a supervised Object-based Image Analysis (OBIA) processing and classification technique to create a high-resolution thematic distribution map of P. oceanica meadows from multibeam bathymetry, backscatter data, drone photogrammetry and multispectral images that can be used as a model for classification of marine and coastal areas. As a part of this work, within the SIC CARLIT project, a field application was carried out in a Site of Community Importance (SCI) on Cirella Island in Calabria (Italy); different multiscale mapping techniques have been performed and integrated: the optical and acoustic data were processed and classified by different OBIA algorithms, i.e., k-Nearest Neighbors’ algorithm (k-NN), Random Tree algorithm (RT) and Decision Tree algorithm (DT). These acoustic and optical data combinations were shown to be a reliable tool to obtain high-resolution thematic maps for the preliminary characterization of seagrass habitats. These thematic maps can be used for time-lapse comparisons aimed to quantify changes in seabed coverage, such as those caused by anthropogenic impacts (e.g., trawl fishing activities and boat anchoring) to assess the blue carbon sinks and might be useful for future seagrass habitats conservation strategies.

A survey of the biological and physical oceanography of the Ligurian Sea was conducted in the late summer of 2000. Forty-one stations were sampled for nutrients, oxygen, fluorescence and hydrographic information. Acoustic backscatter measurements were used to estimate abundance of small (<5 mm) zooplankton biovolume versus depth and the distribution of northern krill, Meganyctiphanes norvegica. Net-tow and underwater video data were collected to identify the zooplankton present. These data were used to analyze the Ligurian Sea ecosystem for physical and biological linkages that control zooplankton abundance and distribution. Results are compared with those from a similar study conducted in 1999. Hydrographic sampling showed a dome of dense water in the southwestern middle of the basin. The highest chlorophyll a (Chl a) concentrations were measured in this area, while small zooplankton biovolume was evenly distributed throughout the survey. Integrated values of Chl a and small zooplankton biovolume in 2000 were greater than in 1999. Meganyctiphanes norvegica, siphonophores and salps were the dominant components of the macrozooplankton population in the upper 200 m. In the sampled depth strata, siphonophore abundance did not change during the day, while M. norvegica were only caught at night. Acoustic backscatter data show that higher densities of M. norvegica occurred in deeper water and in the western and southwestern areas of the Ligurian Sea.

Mediterranean seagrasses are represented by five species, whose most representative are Posidonia oceanica (L.) Delile and Cymodocea nodosa (Ucria) Ascherson. Spatial data analysis through remote sensing techniques is certainly a useful tool in order to understand and quantify the extent or loss of seagrass areas. Seagrass mapping and monitoring by remote sensing have been established using various optical remote sensors and mapping methods1. In most studies for habitat mapping, the most common satellite images used are Landsat, Ikonos, Quickbird, Pleiades, World View 2 and the recent Sentinel-2 etc. 1-2. The aim of this work is to compare the spatial accuracy of medium – resolution satellite images (Sentinel-2 and Landsat-8 OLI) vs. high-resolution images (MIVIS and WorldView-2) for mapping P. oceanica meadows and evaluating their conservation status. The present study was conducted in 2016 within the MPA “Capo Rizzuto” (Mediterranean Sea - Southern Ionian Sea). Remote sensing images were processed following several stages such as preprocessing phase, segmentation, supervised classification and accuracy classification assessment. Preliminary results highlighted differences in spatial and thematic accuracy between medium and very high spatial resolution images for seagrass habitat mapping.

European legislative framework supports a multidisciplinary strategy of environmental monitoring because the environment is a complex system of abiotic and biotic interactions, and it should not be studied and protected by looking at one single aspect. The resulting heterogeneous data request to be carefully processed, and the application of Weight of Evidence (WOE) approaches is, thereby, an integrated validated tool. In this perspective, the present study aims to: (i). apply a specific model (Sediqualsoft) based on the WOE approach for processing multidisciplinary data related to four Lines Of Scientific Evidence (LOEs: chemical analyses, ecotoxicological bioassays, bioaccumulation tests and biomarkers) regarding sediments from an area of the Adriatic Sea; (ii). evaluate the usefulness of this specific integrated approach to estimate the potential environmental hazard due to the presence of gas production platforms respect to the traditional approach of sediment chemical characterization. This latter recognized a more contaminated area within 100 m of the platforms in which the Sediqualsoft model showed the presence of a chemical hazard, ranging from moderate to severe, and identified the contaminants (e.g., some metals, benzo(a)pyrene and acenaphthene) most responsible for it. A significant hazard also appeared in some of the sampled stations by analyzing the LOEs dedicated to the biological responses. The choice of different reference values (regulatory limits, threshold values or concentrations measured in the control area) influenced only the chemical hazard but not the overall integration with other LOEs, showing a moderate hazard for the majority of stations. Here, the concentrations measured in a control area are firstly proposed as possible reference values in Sediqualsoft model applications; this could be of particular relevance when Sediment Quality Guidelines are not available for all the measured substances. Moreover, the limitations of a conventional pass-to-fail approach or worst-case scenario were overcoming interpreting whole chemical and ecotoxicological results. All data analyzed and discussed confirm Sediqualsoft as a suitable tool for processing environmental data, including those first processed here on a monitoring scenario of gas platforms that discharge Produced Water into the sea.