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Abstract Marine pollution is a growing global issue, impacting both marine ecosystem and human health. High quantities of debris, mainly composed by plastic items, have been identified both in the coastal area and in the sea environment. Remote sensing techniques represent an useful tool (complementary to the in-situ campaigns) to monitor litter in the coastal environment, especially if the spectral signatures of the debris are known. In this framework, harvested beach litter (plastic items especially) were collected from two sandy beaches. The samples were spectrally characterised by implementing two indoor laboratory experiments with the aim to infer the best wavelengths to be used for beach litter detection via the spectral angle mapper index. Due to lack of a scientific protocol concerning the spectral data acquisition, two experimental setups were carried out to simulate the direct and diffuse illumination conditions. For around 30% of the samples, the spectral signatures are influenced by the two experimental setups. Outcomes suggest that for the majority of the samples green, blue, red-edge and some infrared bands are suitable for the beach litter detection. more...

Abstract Coastal zones are dynamic interfaces shaped by the interplay of Land Cover (LC) and Land Use (LU), influenced by both natural processes and anthropogenic activities. Grasping the historical shifts in land is essential for safeguarding coastal benefits such as defense mechanisms, biodiversity conservation, and recreational spaces, alongside enhancing their management. LC and LU products offer a valuable option for monitoring urban development, vegetation coverage, and dry-beach areas. Herein, we present the first study of the spatiotemporal evolution of LC specifically tailored for coastal zones, using the coast of Sicily as an illustration. We used classified satellite imagery from Landsat and Sentinel missions as input for a semantic segmentation model based on deep neural networks. We trained the model with an extensive dataset of coastal images. Our classification and analysis of coastal LC dynamics from 1988 to 2022 provide insights at a high spatiotemporal resolution. We identified key factors driving urban transformation, underscoring the impact of urban expansion on vegetated areas, and explored its correlation with economic and demographic growth. This study includes a multiscale analysis of coastal changes, encompassing long-term trends and seasonal fluctuations across Sicilian beaches. Our findings can contribute to preserve coastal areas by informing policymaking aimed at sustainable management. more...