This study addresses the observation of floating plastic debris in freshwater environments using an Unmanned Aerial Vehicle (UAV) multi-sensor strategy. An experimental campaign is described where an heterogeneous plastic assemblage, namely a plastic target, and a naturally occurring leaf-litter mat are observed by a UAV platform in the Lake Calore (Avellino, Southern Italy) within the framework of the “multi-layEr approaCh to detect and analyze cOastal aggregation of MAcRo-plastic littEr” (ECOMARE) Italian Ministry of Research (MUR)-funded project. Three UAV platforms, equipped with optical, multispectral, and thermal sensors, are adopted, which overpass the two targets with the objective of analyzing the sensitivity of optical radiation to plastic and the possibility of discriminating the plastic target from the natural one. Georeferenced orthomosaics are generated across the visible, multispectral (Green, Red, Red Edge, Near-Infrared—NIR), and thermal bands. Two novel indices, the Plastic Detection Index (PDI) and the Heterogeneity Plastic Index (HPI), are proposed to discriminate between the detection of plastic litter and natural targets. The experimental results highlight that plastics exhibit heterogeneous spectral and thermal responses, whereas natural debris showed more homogeneous signatures. Green and Red bands outperform NIR for plastic detection under freshwater conditions, while thermal imagery reveals distinct emissivity variations among plastic items. This outcome is mainly explained by the strong NIR absorption of water, the wetting of plastic surfaces, and the lower sensitivity of the Mavic 3′s NIR sensor under high-irradiance conditions. The integration of optical, multispectral, and thermal data demonstrate the robustness of UAV-based approaches for distinguishing anthropogenic litter from natural materials. Overall, the findings underscore the potential of UAV-mounted remote sensing as a cost-effective and scalable tool for the high-resolution monitoring of plastic pollution over inland waters.

Beach litter (BL) poses a significant threat to coastal ecosystems and marine biodiversity. Monitoring its density, composition, and distribution is crucial to develop effective management strategies and support the sustainable use of the beach environments. Traditional in situ visual surveys allow detailed identification and classification of BL items but are often limited in spatial coverage and require significant time investment. Recent advancements, including the use of Unmanned Aerial Vehicles (UAV), have enabled more efficient assessments of coastal litter and related geomorphological features.This study investigates the characteristics and distribution of BL and its relationship with coastal morphodynamics along two unmanaged beaches located along the Molise coast (southern Italy): Petacciato and Ramitelli beaches. These sites were selected based on their distinct morphodynamic characteristics, and their free beach status.The monitoring methodology considered international guidelines [1, 2]. UAV surveys were conducted before and after a significant storm event to assess its impact not only on beach morphology but also on BL distribution. Flights were carried out with a Yuneec Typhoon H520 hexacopter using a flight height of 15 meters [2]. High-resolution orthophotos were analysed to manually identify BL larger than 2.5 cm and classify them according to the Joint List for Marine Macrolitter Monitoring [2]. Items were categorized by material type, size, and weight, and unusual objects were documented in detail. Shoreline and dune foot variations along with morphological changes of the beach were also quantified to evaluate the role of coastal processes in BL dispersion and accumulation patterns.First results reveal significant differences in BL density and composition between the two study sites, but with plastic materials dominating both the collected items, consistent with broader Mediterranean trends [3]. The post-storm survey highlighted the role of weather events in redistributing litter, particularly at the southern limit of the Ramitelli beach which is in contact with the jetty of the Saccione River mouth that drives the accumulation of beach litter on the adjacent shoreline. This study underscores the importance of integrating UAV-based monitoring with geomorphological analyses to better understand the interplay between coastal dynamics and BL distribution. The monitoring of these relationships can provide essential data to support and improve coastal management and design targeted beach clean-up strategies. Key WordsRemote Sensing, Coastal monitoring, Coastal geomorphology, UAV images, Visual assessment, Litter beach analysis. [1] Vlachogianni T. (2017) - Methodology for Monitoring Marine Litter on Beaches. Macro-Debris (> 2.5 cm). DeFishGear, 1-16.[2] Fleet D., Vlachogianni T. & Hanke G. [Eds] (2021) - A joint list of litter categories for marine macrolitter monitoring. JRC Technical Reports, Publications Office of the European Union, Luxembourg, 30348, 52.[3] Rizzo A., Sozio A., Anfuso G., La Salandra M., Sasso C. (2022) – The use of UAV images to assess preliminary relationships between spatial litter distribution and beach morphodynamic trends: the case study of Torre Guaceto beach (Apulia Region, Southern Italy). Geogr. Fis. Dinam. Quat. 45 (2022). 237-250.