The traditional approach for coastal monitoring consists in ground investigations that are burdensome both in terms of logistics and costs, on a national or even regional scale. Earth Observation (EO) techniques can represent a cost-effective alternative for a wide scale coastal monitoring. Thanks to the all-weather day/night radar imaging capability and to the nationwide acquisition plan named MapItaly, devised by the Italian Space Agency and active since 2010, COSMO-SkyMed (CSK) constellation is able to provide X-band images covering the Italian territory. However, any remote sensing approach must be accurately calibrated and corrected taking into account the marine conditions. Therefore, in situ data are essential for proper EO data selection, geocoding, tidal corrections and validation of EO products. A combined semi-automatic technique for coastal risk assessment and monitoring, named COSMO-Beach, is presented here, integrating ground truths with EO data, as well as its application on two different test sites in Apulia Region (South Italy). The research has shown that CSK data for coastal monitoring ensure a shoreline detection accuracy lower than image pixel resolution, and also providing several advantages: low-cost data, a short revisit period, operational continuity and a low computational time.

In the present paper, a numerical chain aimed at predicting wave-induced runup on an embayed sandy beach is validated by means of measurements derived from a video-monitoring station, recently installed in Southern Italy, during two storm events in 2016. The numerical approach employs the MeteOcean forecasted waves within SWAN and SWASH models (both in 2-d and 1-d mode). The combination of multibeam and d-RTK surveys with Unmanned Aerial Vehicle (UAV) imagery provides high resolution depth grid (0.015 m), particularly required in shallow waters, where wave hydrodynamics is highly influenced by the bottom. The results show a good agreement between video measurements and 2-d predictions of runup. A sensitivity analysis of the Manning's roughness factor is needed in 1-d simulations. The accuracy of the empirical formulas in predicting wave runup in an embayed beach is also investigated, showing mainly overestimation of the observations.

Frequently exposed to natural agents such as waves, wind, tides, storm activity, seasonal changes and anthropogenic agents, coastal areas are tangibly high energy environments and therefore subject to considerable dynamics. In order to mitigate and reduce the impacts on these areas, different types of coastal protection systems can be implemented. Rockwalls and breakwaters are the most ordinary structures and even if used precisely for coastal protection, these flexible structures can in turn be damaged or ineffective over time. Therefore, like the monitoring of coastal areas in terms of execution frequency and accuracy, the measurement of changes over time of these structures, in particular after significant events, can allow to carry out an economic maintenance service before a serious occurrence and costly damage. However, given the rapid evolution of the preservation state of coastal areas and protection structures, it is therefore essential to plan an equally frequent, practical and accurate structural-coastal monitoring. On the other hand, their accessibility can sometimes be dangerous or uncomfortable such as to compromise operations in the field. In this work, the application of two close-range detection techniques competitor, i.e. from the Terrestrial Laser Scanner and from Remote Piloted Aircraft Systems, aimed at the generation of three-dimensional reconstructions of a protection structure, was analyzed. By performing a cloud-to-cloud comparison, interesting considerations have been obtained on the precision that can be achieved and on the technical limits deriving from the two methodologies. Considering the economy and practicality of use, if used correctly, a Remote Piloted Aircraft Systems supported by a suitable geo-referencing and an optimized data processing, can produce accurate and coherent 3D reconstructions as those derivable from the Terrestrial Laser Scanner. Finally, the results obtained by merging the point clouds generated from the two different techniques were evaluated in order to identify any advantages in the structural maintenance of the systems.

A new system for estimating the synthetic parameters of sea states during physical investigations has been implemented. The technique proposed herein is based on stereographic analysis of digital images acquired with optical sensors. A series of ad hoc floating markers has been made and properly moored to the bottom of a large wave tank to estimate the synthetic parameters of generated waves. The implemented acquisition system and the proposed algorithm provide automatic recognition of all markers by a pair of optical sensors that synchronously captures their instantaneous location and tracks their movements over time. After transformation from the image to the real-world coordinates, water surface elevation time series have been obtained. Several experimental tests have been carried out to assess the feasibility and reliability of the proposed approach. The estimated wave synthetic parameters have been then compared with those obtained by employing standard resistive probes. The deviation were found to be equal to ~6% for the significant wave height and 1% for peak, mean, and significant wave periods.

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Sea wave reflection from coastal protection structures is one of the main issues in the coastal design process. Several empirical formulas have been proposed so far to predict reflection coefficient from rubble mound breakwaters and smooth slopes. The aim of this study is to investigate wave reflection from a rubble mound structure placed in front of a vertical concrete seawall. Several experimental tests were performed on a two-dimensional wave flume by reproducing on a rubble mound structure with a steep single primary layer armored with a novel artificial unit. A new approach for the prediction of the reflection coefficient based on dimensional analysis is also proposed, and a new empirical equation is derived. The performance of the proposed equation was compared with widespread existing formulas, and a good accuracy was found.

The present work focuses on the preparatory phase of the design of the biodiversity monitoring network. The preliminary results of this first phase are then presented, starting from the formation of a cognitive framework based on previous knowledge of environmental parameters, the definition of sampling stations, areas, and detection points. At the same time, the results of the analysis of the evolutionary dynamics of the coasts are shown in the light of the new analyses and new measures, which, together with existing data, aim to inform the monitoring strategy.