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The benthic seabeds and seagrass ecosystems, in particular the vulnerable Posidonia oceanica (PO), are increasingly threatened by climate change and other anthropogenic pressures. Along the 8000km coastline of Italy, they are often poorly mapped and monitored to properly evaluate their health status. Thus to support these monitoring needs, the improved capabilities of the Landsat 8 Operational Land Imager (OLI) Earth Observation (EO) satellite system were tested for PO mapping by coupling its atmospherically corrected multispectral data with near-synchronous sea truth information. Two different approaches for the necessary atmospheric correction were exploited focusing on the Aerosol Optical Depth (AOD) and adjacency noise effects, which typically occur at land–sea interfaces. The general achievements demonstrated the effectiveness of High Resolution (HR) spectral responses captured by OLI sensor, for monitoring seagrass and sea beds in the optically complex Tyrrhenian shallow waters, with performance level dependent on the type of applied atmospheric pre-processing. The distribution of the PO leaf area index (LAI) on different substrates has been most effectively modelled using on purpose developed spectral indices. They were based on the coastal and blue-green OLI bands, atmospherically corrected using a recently introduced method for AOD retrieval, based on the Short Wave Infrared (SWIR) reflectance. The alternative correction method including a less effective AOD assessment but the removal of adjacency effects has proven its efficacy for improving the thematic discriminability of the seabed types characterized by different PO cover–substrate combinations.

Various species of cultivated thistle, such as Cynara cardunculus L. (cardoon), exhibit interesting features for industrial biomass production as bioenergy crops, given also their advantageous adaptation capacities to typical Mediterranean climate trends, with noticeable resilience to drought and salinization stresses. The in situ hyperspectral reflectance responses of three genotypes of cardoon plants, irrigated with water at different salinity levels, have been tested for assessing the effects on their biophysical parameters, aiming at improving the biomass yield for bioenergy production, minimizing at same time the environmental impacts and the exploitation of soils and waters resources. The leaf and canopy reflectance hyperspectral signatures, acquired at three different growth stages with biometric measurements, were statistically analyzed (ANOVA, Tukey&rsquo, s test, graphs), as noise-resilient spectral indices, sensible to different plant features of interest. Their broadband versions, based on the Landsat 8 OLI and Sentinel 2 MSI satellite sensors, were also evaluated in perspective of operative and extensive remote crop monitoring from space. The results highlighted significant differences in some spectral index responses, related to different cardoon genotypes and water salt concentration. The biometric data supported by red-edge indices modelling evidenced the impact of the highest salt water concentration (200 mM/L) on the plant growth and yield.

The meadow froghopper, Philaenus spumarius L., is endemic in Italy and was not considered a harmful species until 2014, when the olive quick decline syndrome (OQDS) showed up in Apulia (southern Italy). It was immediately suspected and then verified as the main vector of Xylella fastidiosa, the bacterium responsible for the disease. Currently, EU Directives consider the fight against P. spumarius compulsory in member states and recommend Integrated Pest Management (IPM), both in uncultivated and cultivated infested areas, to minimise the environmental impact of chemical pesticides. This should be based on an improved knowledge of the vector with its seasonal trends and feeding habits linked to specific herbaceous species. In this context, our field study was aimed to improve the understanding of the vector nutritional behaviour, especially at its critical nymph stage, by monitoring its presence on different herbaceous target species, using its typical feeding foams as key indicator. The study area was in Lazio region (central Italy), dedicated to olive growing and still unaffected by the X. fastidiosa plague. Over twoyears, during the nymph development period, field data have been acquired over the test area and then analysed by coupling statistical (ANOVA), geographical information system (GIS) and geo-referenced field sampling approaches. Results highlighted that P. spumarius exhibits significant preferences for specific herbaceous plants, especially at its early development stages, detectable by tenuous spittle. This indicates female oviposition activity, which seems also not influenced by olive tree proximity. Furthermore, the non-host plant species identified here could be suitable for creating green barriers for limiting the vector diffusion to contiguous areas where sensible plantations are growing. In the final section, applied implications arising from the present findings for P. spumarius population management are discussed.

In the framework of Posidonia oceanica (PO) preservation activities, a small-scale restoration pilot project was implemented in 2005 at a Santa Marinella site to replace the loss of this important species of seagrass in this zone of the central Tyrrhenian coast via an innovative transplantation approach. In this context, taking into account the recent advances in the fields of high-resolution (HR) satellite/airborne remote-sensing and genetics laboratory analysis techniques, we propose this integrated methodology for monitoring changes in transplanted meadows in regard to perspective to provide support in the assessment of the entire local PO and seagrass population dynamic. According to specific information requirements in terms of radiometric and spectral/spatial resolution, the multispectral data currently available from the QuickBird polar satellite's four-band (red, green, and blue visible and near-infrared) HR sensor were exploited for methodology implementation using a practical 'image-based' approach to account for atmospheric and water column turbidity typical of this mid-coastal Mediterranean region. First, the extents and types of seagrass cover were suitably mapped, and then also the distributions of specific vegetation parameters related to PO dynamics and health were assessed by exploiting the remotely sensed satellite-derived radiance signals and point sea-truth calibration measurements of the bio-genetic parameters. In particular, we implemented maps of leaf area index, genetic similarity, and density Giraud indices corresponding to distributions of PO patches using multivariate and data-mining models (artificial neural network) based on appropriately preprocessed radiometric and auxiliary (bathymetry) input variables. © 2013 Copyright Taylor and Francis Group, LLC.