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Coastal sand dunes are highly dynamic aeolian landforms where different spatial patterns can be observed due to the complex interactions and relationships between landforms and land cover. Sediment distribution related to vegetation types is explored here on a single ridge dune system by using an airborne hyperspectral and light detection and ranging (LiDAR) remote sensing dataset. A correlation model is applied to describe the continuum of dune cover typologies, determine the class metrics from landscape ecology and the morphology parameters, and extract the relationship intensity among them. As a main result, the mixture of different vegetation types such as herbaceous, shrubs, and trees classes shows to be a key element for the sediment distribution pattern and a proxy for dune sediment retention capacity, and the anthropic fingerprints can play an even major role influencing both ecological and morphological features. The novelty of the approach is mostly based on the synergistic use of LiDAR with hyperspectral that allowed (i) the benefit from already existing processing methods to simplify the way to obtain thematic maps and coastal metrics and (ii) an improved detection of natural and anthropic landscape.

[1] A suite of modern, shore-normal channels was discovered on the southern shoreface of Sable Island, Canada. Repetitive multibeam and side scan surveys of these features, as well as box coring and sampling, showed that the depressions were perennial features of the shoreface. They occurred in fine and medium sand and were most abundant indepths less than 20 m. They were up to 1 m deep and 50 m wide, increased in size seawards, and generally followed the seabed slope. The channels dominated the inner shoreface becoming wider and deeper seawards to depths in excess of 40 m. There is a continuum of scales in width and depth of these channels, the smallest of which are equated with gutters preserved in the geological record. The internal structure of the shoreface sediments where the gutters are found is characterized by normally graded tempestites composed of cut-and-fill structures overlying an erosion surface. Thus, the environmental setting, internal structure, and scale are similar to ancient counterparts. Gutters have been interpreted to result from downwelling over palaeo-shorefaces during ancient storms [Myrow, 1992b]. The composition of gutter infill, as well as the stability, evolution, associated bed forms, and hydrodynamic conditions under which they formed, were examined to verify genetic interpretations of the ancient counterparts. The multisensor benthic lander RALPH was deployed within a field of shore normal channels for 17 days during late winter 1998. RALPH burst-sampled flow at hourly intervals while imaging the seabed. Resulting sequential imagery revealed the genesis of a group of five gutters during storm spin-down that was coincident with the formation of largescale wave ripples. This was followed by infilling of the gutters and wave ripple destruction within 20 hours by longshore sand transport. The gutters were located within, and parallel to, a larger channel (50 m wide and 0.50 m deep). They were formed by coastal set-up and subsequent downwelling that was triggered by the rotation of storm winds from seawards (onshore wind) to landwards (offshore wind). The gutters formed within 2-3 hours during spin-down of a winter storm under ''live-bed'' conditions of sand transport. Wave height and mean tidal flows were well below those of the storm peak and so they were not directly responsible for creating the gutters. The mechanism we propose for the evolution of gutters supports the geological interpretations; that is, a storm-driven, downwelling event as described by Swift and Niedoroda [1985]. However, the downwelling event appeared to take place suddenly (rapid acceleration in flow), briefly (few hours duration), and within narrow corridors guided by wider and deeper channels of the shoreface. High turbidity during the time of gutter formation leads us to believe that the phenomenon of inner shelf turbidity currents [as suggested by Walker, 1985] exists and may be instrumental in channel formation. INDEX TERMS: 4546

The accumulation of Posidonia oceanica dead leaves on the beaches of the Mediterranean shores is a natural phenomenon. They are either temporary or permanent structures (banquettes) and represent a valuable resource, with important ecosystem functions including coastal protection against erosion. Nevertheless, the perception of these plant accumulations by the different stakeholders (beach managers, local administrations and tourists) is often negative; they consider these deposits a malevolent waste to be removed, rather than a natural and valuable component of the coastline. We propose an integrated/beneficial management model for posidonia deposits, called ECOLOGICAL BEACH, firstly proposed in France, and recently implemented and applied in Italy. The model promotes the preservation of posidonia beach casts on site, with a balanced coexistence of natural and anthropic elements. The model fosters the several important ecosystem services of the beach casts and contributes to coastal preservation. To successfully spread the model, several activities must be implemented: a regulatory framework, the collection of data about the occurrence of beach casts, management protocols and educational programs. The most important activity is the educational one, based on the dissemination of the ecological and economic value of the beach casts, aimed at switching the perception of this phenomenon towards positive appraisal.

An application of the FHyL (field spectral libraries, airborne hyperspectral images and topographic LiDAR) method is presented. It is aimed to map and classify bedforms in submerged beach systems and has been applied to Sabaudia coast (Tirrenyan Sea, Central Italy). The FHyl method allows the integration of geomorphological observations into detailed maps by the multisensory data fusion process from hyperspectral, LiDAR, and in-situ radiometric data. The analysis of the sandy beach classification provides an identification of the variable bedforms by using LiDAR bathymetric Digital Surface Model (DSM) and Bathymetric Position Index (BPI) along the coastal stretch. The nearshore sand bars classification and analysis of the bed form parameters (e.g., depth, slope and convexity/concavity properties) provide excellent results in very shallow waters zones. Thanks to well-established LiDAR and spectroscopic techniques developed under the FHyL approach, remote sensing has the potential to deliver significant quantitative products in coastal areas. The developed method has become the standard for the systematic definition of the operational coastal airborne dataset that must be provided by coastal operational services as input to national downstream services. The methodology is also driving the harmonization procedure of coastal morphological dataset definition at the national scale and results have been used by the authorities to adopt a novel beach management technique.

Remote sensing of coastal ecosystems provides fundamental information for the effective assessment of valuable natural habitat. A synoptic view of the shallow submerged and emerged coastal landscape can offer the quantitative ability to obtain spatially explicit data over large and complex areas, where the heterogeneity of habitat is mixed by vegetation and sediment/soil interactions at the interface with water and atmosphere. In the present paper, by combining field radiometry with contemporary airborne hyperspectral imagery and topographic and bathymetric LiDAR data, an innovative approach with the application of Spectral Mixture Analysis (SMA) and Multiple Linear Regression models is proposed in order to define shallow coastal seabed, beach and dune habitat at the finest scale. The implemented FHyL (Field spectral libraries, airborne Hyperspectral imagery and LiDAR altimetry) processing chain leads to an innovative mapping results obtained by an integration of multisensory data. Presence and typology of vegetated and unvegetated beach is represented as the abundance of each physical response within the hyperspectral reflectance by building multisensory and multidimensional hyperspectral -LiDAR mixture space. Mineralogical and sedimentological proprieties of the beach sediment was estimated by using field and airborne spectral libraries combined with sediment sampling in a multiple linear regression statistical model. Therefore, FHyL represents the multisensory data fusion process to classify and map vegetation presence and distribution, as well as sediment properties and geomorphology of complex coastal seabed, and beaches dunes systems. The present research is a novel input for multilayered analysis in biophysical studies and its application on multi temporal dataset modeling of coast evolution.