Spatial and size distribution of macro-litter on coastal dunes from drone images: A case study on the Atlantic coast

Mapping waste piles in an urban environment using ground surveys, manual digitization of drone imagery, and object based image classification approach

There is wide recognition of the threats posed by the open dumping of waste in the environment. However, tools to surveil interventions for reducing this practice are poorly developed. This study explores the use of drone imagery for environmental surveillance. Drone images of waste piles were captured in a densely populated residential neighborhood in the Republic of Malawi. Images were processed using the Structure for Motion (SfM) technique and partitioned into segments using Orfeo Toolbox mounted in QGIS software. A total of 509 segments were manually labeled to generate data for training and testing a series of classification models. Four supervised classification algorithms (Random Forest, Artificial Neural Network, Naïve Bayes, and Support Vector Machine) were trained, and their performances were assessed regarding precision, recall, and F-1 score. Ground surveys were also conducted to map waste piles using a Global Positioning System (GPS) receiver and determine the physical composition of materials on the waste pile surface. Differences were observed between the field survey done by community-led physical mapping of waste piles and drone mapping. Drone mapping identified more waste piles than field surveys, and the spatial extent of waste piles was computed for each waste pile. The binary Support Vector Machine model predictions were the highest performing, with a precision of 0.98, recall of 0.99, and F1-score of 0.98. Drone mapping enabled the identification of waste piles in areas that cannot be accessed during ground surveys and further allowed the quantification of the total land surface area covered by waste piles. Drone imagery-based surveillance of waste piles thus has the potential to guide environmental waste policy, offer solutions for permanent monitoring, and evaluate waste reduction interventions.

Riparian vegetation entraps macroplastics along the entire river course: Implications for eco-safety activities and mitigation strategies

Macroplastic litter causes detrimental effects on freshwater biota affecting human health. Despite the significant role of rivers in transporting plastic waste, most plastics remain in fluvial ecosystems, accumulating in infrastructure, river sediment, and (riverbank) vegetated areas. However, the entrapment of plastics by riparian vegetation was overlooked, particularly in upper and middle river courses. For the first time, we aimed to quantify the entrapment of plastics by riparian vegetation along the entire river course. Sampling riparian areas in the upper, middle, and lower river courses in central Italy, we found 1548 macrolitter items, with vegetation entrapping 93.9% of total litter. Riverbank and riparian plastics acted as long-term indicators of river plastics. We emphasized the trapping efficiency at the species level highlighting that the best plastic trapper species were trees, shrubs and reeds (Populus spp., Salix spp., Rubus ulmifolius, Phragmites australis, and Ficus carica), blocking 85.4% of the total macrolitter entrapped by plants. Plastic pieces, bags, bandages, sanitary items, and packaging were among the most trapped types. Furthermore, vegetation in the lower river course exhibited greater plastic entrapment compared to the upper and middle courses, following the fact that all the river courses contribute to plastic pollution. Recognizing the potential of riparian vegetation as a valuable ecosystem service in trapping macroplastics, further research should explore the characteristics and structures of riparian communities involved in this process. By developing eco-safe practices and mitigation strategies based on these findings, we might contribute significantly to managing, conserving, and restoring riverine ecosystems.

Monitoring macroplastics in aquatic and terrestrial ecosystems: Expert survey reveals visual and drone-based census as most effective techniques

Anthropogenic litter, such as plastic, is investigated by the global scientific community from various fields employing diverse techniques. The goal is to assess and finally mitigate the pollutants' impacts on the natural environment. Plastic litter can accumulate in different matrices of aquatic and terrestrial ecosystems, impacting both biota and ecosystem functioning. Detection and quantification of macroplastics, and other litter, can be realized by jointly using visual census and remote sensing techniques. The primary objective of this research was to identify the most effective approach for monitoring macroplastic litter in riverine and marine environments through a comprehensive survey based on the experiences of the scientific community. Researchers involved in plastic pollution evaluated four litter occurrence and flux investigation methods (visual census, drone-based surveys, satellite imagery, and GPS/GNSS trackers) through a questionnaire. Traditional visual census and drone deployment were deemed as the most popular approaches among the 46 surveyed researchers, while satellite imagery and GPS/GNSS trackers received lower scores due to limited field validation and short performance ranges, respectively. On a scale from 0 to 5, visual census and drone-based surveys obtained 3.5 and 2.0, respectively, whereas satellite imagery and alternative solutions received scores lower than 1.2. Visual and drone censuses were used in high, medium and low-income countries, while satellite census and GPS/GNSS trackers were mostly used in high-income countries. This work provides an overview of the advantages and drawbacks of litter investigation techniques, contributing i) to the global harmonization of macroplastic litter monitoring and ii) providing a starting point for researchers and water managers approaching this topic. This work supports the selection and design of reliable and cost-effective monitoring approaches to mitigate the ambiguity in macroplastic data collection, contributing to the global harmonization of macroplastic litter monitoring protocols.

How much does marine litter weigh? A literature review to improve monitoring, support modelling and optimize clean-up activities

The weight of marine litter has been marginally considered in comparison to counting and categorizing items. However, weight determines litter dynamics on water and coasts, and it is an essential parameter for planning and optimizing clean-up activities. This work reviewed 80 publications that reported both the number and weight of beached macro-litter worldwide. On average, a litter item weighed 19.5 ± 20.3 g, with a median weight of 13.4 g. Plastics composed 80% by number and 51% by weight of the global litter bulk. A plastic item weighed 12.9 ± 13.8 g on average, with a median weight of 9 g. The analysis based on continents and on water bodies returned similar values, which can be used to estimate litter weight on beaches from past and future visual census surveys, and from remote sensing imagery. Overall, this work can improve litter monitoring reports and support dynamics modelling, thereby contributing for environmental protection and mitigation efforts.

Effect of biodegradable and conventional microplastic exposure in combination with seawater inundation on the coastal terrestrial plant Plantago coronopus

Coastal ecosystems face a multitude of pressures including plastic pollution and increased flood risk due to sea level rise and the frequency and severity of storms. Experiments seldom examine multiple stressors such as these, but here we quantified the effect of microplastics (polyethylene terephthalate (PET): a durable plastic and polybutylene adipate terephthalate (PBAT): a biodegradable polymer), in combination with simulated seawater inundation on the coastal species Plantago coronopus. After 35-days exposure to plastic (0.02 g.Kg-1, <300 μm diameter), P. coronopus were flooded to pot height with artificial seawater for 72-h, drained and grown for a further 24-days. Plant mortality, necrosis and photosynthetic efficiency (Fv/Fm) were recorded throughout, with root:shoot biomass and scape production (flower stalks) quantified at harvest. There were significant interactions between microplastics and seawater on the root:shoot ratio; a measure of resource allocation. The allocation to belowground biomass increased significantly under the PET + inundation treatment compared to the PBAT + inundation and the no plastic + inundation treatments, with potential consequences on the capture of water, nutrients and sunlight, which can affect plant performance. Plant necrosis significantly increased, and Fv/Fm declined as a result of seawater inundation. While not significant, plant Fv/Fm responses were influenced by microplastics (17% and 7% reduction in PBAT and PET exposure respectively compared to the no plastic control). Plants mediated this stress response with no discernible treatment-specific effects detected in Fv/Fm 14-days after seawater introduction. Plastic exposure significantly influenced potential reproductive output, with lower average scape numbers across PBAT treatments, but higher in PET treatments. This study highlights the complex interactions and potential for microplastics to present an elevated risk when in combination with additional stressors like seawater flooding; establishing the threat presented to ecosystem resilience in a changing world is a priority.

Indoor laboratory experiments for beach litter spectroradiometric analyses

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.

Marine litter along the Peruvian coast: spatiotemporal composition, sources, hazard, and human modification relations

Marine litter (ML) represents an escalating environmental issue, particularly in Latin America, where comprehensive studies are scarce despite critical solid waste management challenges and continuous human modification occurring on the coasts. To contribute to the knowledge of ML in the southeast Pacific, this study examined contamination across 10 beaches on Peru's extensive coast. Overall, ML contamination was categorized as moderate (with an ML concentration of 0.49 ± 0.64 items∙m-2), while significantly differing between summer (dirty with an ML concentration of 0.56 ± 0.66 items∙m-2) and winter (moderate with an ML concentration of 0.47 ± 0.60 items∙m-2). Three beaches were extremely dirty (concentrations of ML exceeded 1.0 items∙m-2). Predominant materials, items, and sources were plastic, cigarette butts (CBs), and mixed packaging. The Peruvian coast faced CB leachate impact (CBPI = 3.5 ± 3.5), reaching severe levels on two beaches, with considerable hazardous litter (HALI = 3.0 ± 2.9). Additionally, a higher degree of human modification was associated with higher ML levels along the coast.

Tide of change: Urgency of a national marine litter policy in India

The rise of plastics in the 20th century revolutionized modern life but inadvertently exacerbated the marine litter crisis. The proliferation of wastes such as single-use plastics has escalated pollution along the coastline, demanding coordinated, decisive, and unified action. While the absence of specific national marine litter policies is concerning, there is growing recognition of urgency to address this issue. A group of experts and stakeholders was involved through a multi-staged workshop to assess the generated information based on scientific evidence and formulate a framework for the National Marine Litter Policy (NMLP). This paper proposes policy options (4 targets & 20 strategies) to address marine litter pollution, especially plastics, and aims to elucidate the urgency and significance of implementing an NMLP as a comprehensive strategy to combat plastics pollution. Implementing dedicated policies and action plans tailored to the unique challenges faced by each country is a vital step towards sustainable oceans.

Marine litter weight estimation from UAV imagery: Three potential methodologies to advance macrolitter reports

In the context of marine litter monitoring, reporting the weight of beached litter can contribute to a better understanding of pollution sources and support clean-up activities. However, the litter scaling task requires considerable effort and specific equipment. This experimental study proposes and evaluates three methods to estimate beached litter weight from aerial images, employing different levels of litter categorization. The most promising approach (accuracy of 80 %) combined the outcomes of manual image screening with a generalized litter mean weight (14 g) derived from studies in the literature. Although the other two methods returned values of the same magnitude as the ground-truth, they were found less feasible for the aim. This study represents the first attempt to assess marine litter weight using remote sensing technology. Considering the exploratory nature of this study, further research is needed to enhance the reliability and robustness of the methods.

Dune plants as a sink for beach litter: The species-specific role and edge effect on litter entrapment by plants

Anthropogenic litter accumulates along coasts worldwide. In addition to the flowing litter load, wind, sea currents, geomorphology and vegetation determine the distribution of litter trapped on the sandy coasts. Although some studies highlighted the role of dune plants in trapping marine litter, little is known about their efficiency as sinks and about the small-scale spatial distribution of litter across the dune area. Here, we explore these gaps by analysing six plant species widespread in Mediterranean coastal habitats, namely Echinophora spinosa, Limbarda crithmoides, Anthemis maritima, Pancratium maritimum, Thinopyrum junceum, and Salsola kali. The present study analyses for the first time the capture of litter by dune vegetation at a multi-species level, considering their morphological structure. Data on plastic accumulation on dune plants were compared with unvegetated control plots located at embryo-dune and foredune belts. We found that dunal plants mainly entrapped macrolitter (> 0.5 cm). Particularly, E. spinosa, L. crithmoides, A. maritima and P. maritimum mostly accumulated litter in the embryo dune while T. junceum and S. kali entrapped more in the foredune area. Moreover, beach litter was mainly blocked at the edge of the plant patches rather than in the core, highlighting the 'Plant-edge litter effect'. As A. maritima and S. kali entrapped respectively more litter in embryo and foredune habitats, these species could be used to monitor and recollect litter. In this light, our findings provide further insight into the role of dune plants in the beach litter dynamics, suppling useful information for beach clean-up actions.

Assessment of beach macrolitter using unmanned aerial systems: A study along the Bulgarian Black Sea Coast

Over the years, the Black Sea has been impacted by the issue of marine litter, which poses ecological and health threats. A mid-term monitoring program initiated in 2018 assessed the abundance, density, and composition of beach litter (BL) on 40 frequently visited beaches. From 2018 to 2022, there was a significant increase in average abundance, rising by 261 %. Artificial polymer materials accounted for the majority (84 %) of the litter. Land-based sources dominated 77 % of the litter. The Clean Coast Index (CCI) categorized the beaches as "moderate" with an average value of 8.9 for the period between 2018 and 2022. However, the years 2021 and 2022, during the COVID-19 epidemic, were identified as the "dirtiest period" with 11 beaches classified as "extremely dirty" due to high domestic tourist pressure. The study demonstrates a successful combination of standard in situ visual assessment supported by unmanned aerial systems for beach litter surveys.

Drones for litter monitoring on coasts and rivers: suitable flight altitude and image resolution

Multirotor drones can be efficiently used to monitor macro-litter in coastal and riverine environments. Litter on beaches, dunes and riverbanks, along with floating litter on coastal and river waters, can be spotted and mapped from aerial drone images. Items detection and classification are prone to image resolution, which is expressed in terms of Ground Sampling Distance (GSD). The GSD is determined by drone flight altitude and camera properties. This paper investigates what is a suitable GSD value for litter survey. Drone flight altitude and camera setup should be chosen to obtain a GSD between 0.5 cm/px and 1.25 cm/px. Within this range, the lowest GSD allows litter categorization and classification, whereas the highest value should be adopted for a coarser litter census. In the vision of drawing up a global protocol for drone-based litter surveys, this work sets the ground for homogenizing data collection and litter assessments.

Modelled and observed plastic pollution on remote Scottish beaches: The importance of local marine sources

Beach-cleans conducted on the west coast of Scotland investigated the distribution of land- and marine-sourced litter and compared these with a particle tracking model representing the presumed principal land-based source. Modelled particles dispersed widely, even reaching the remote northwest coast, with 'hotspots' and 'coldspots' on windward and leeward coasts respectively. In beach sampling, however, land-sourced litter represented only 19% of items by count and 8% by weight, while marine-sourced litter represented 46% by count and 62% by weight. The source of the remainder could not be identified. Windward coasts had an average count of 1859 litter items per 100 m, and weight of 14,862 g per 100 m. Leeward coasts had an average count of 32 litter items per 100 m and weight of 738 g per 100 m. Field observations and model predictions were consistent in many respects for land-sourced litter, however marine-sourced litter is dominant on many coastlines.

The octopus pot on the North Atlantic Iberian coast: A plague of plastic on beaches and dunes

This baseline focuses on the octopus pot, a litter item found on the North Atlantic Iberian coast. Octopus pots are deployed from vessels in ropes, with several hundred units, and placed on the seabed, to capture mostly Octopus Vulgaris. The loss of gears due to extreme seas state, bad weather and/or fishing-related unforeseen circumstances, cause the octopus pots contaminating beaches and dunes, where they are transported by sea current, waves and wind actions. This work i) gives an overview of the use of octopus pot on fisheries, ii) analyses the spatial distribution of this item on the coast, and iii) discusses the potential measures for tackling the octopus pot plague on the North Atlantic Iberian coast. Overall, it is urgent to promote conducive policies and strategies for a sustainable waste management of octopus pots, based on Reduce, Reuse and Recycle hierarchical framework.

Difference between invasive alien and native vegetation in trapping beach litter: A focus on a typical sandy beach of W-Mediterranean Basin

Beach litter is one of the most pervasive pollution issues in coastal environments worldwide. In this study, we aim to assess the amount and distribution of beach litter on Porto Paglia beach, its entrapment across psammophilous habitats, and whether the invasive Carpobrotus acinaciformis (L.) L.Bolus plays a different role in trapping litter than native vegetation. To this end, two seasonal samplings (in spring and autumn) were conducted using a paired sampling method that considers plots in all coastal habitats with and without C. acinaciformis. Our results confirm that the main beach litter category is plastic, and that its distribution varies across habitats: the white dune seems to play a greater role in trapping and filtering beach litter, reducing its amount in the backdune. A correlation was found between the Naturalness index (N) and the beach litter amount, supporting the finding that invaded habitats trap beach litter better than native ones.

Dunal plants as sink for anthropogenic marine litter: The entrapping role of Salsola kali L. (1753) in a Mediterranean remote beach (Sardinia, Italy)

The ability to retain anthropogenic marine litter by a halo-psammophilous plant formation dominated by a single prostrate species (Salsola kali) on a Sardinian beach was measured. We hypothesized that the anthropogenic litter (i) is trapped by plants to a greater extent than in control areas, and (ii) has more elongated size, mimicking the organic Posidonia wrack, largely occurring locally as 'banquettes'. Salsola kali patches show an apparently higher anthropogenic litter density than control sites without vegetation. Salsola kali plants trap litter items significantly longer and a larger number of size length categories than control plots. These effects may be due to the prostrate structure of the plant with small thorns at the apex. Also, litter entrapped by plants can interfere with the mechanisms of dune deposition and structuration, in turn affecting food chains by decreasing the availability of organic material for pedofauna.

Impacts of a massive beach music festival on a coastal ecosystem - A showcase in Portugal

Beach music festivals are numerous and popular worldwide. The concerns about the environmental sustainability of these events have been increasing among scientists, coastal managers and local communities. Nevertheless, the negative effects of beach music festivals on the coastal environment have been poorly studied. This work identified, analysed and discussed the eco-geomorphological impacts of a massive beach music festival held on a Portuguese beach-dune system over three days in July 2022. Drone-based orthophotos and pictures collected in the field were analysed to evaluate the impact of pre- and post-festival works, which turned the beach into a construction site over about twenty days. Digital Surface Model (DSM) analysis showed that beach configuration was approximately restored to the pre-festival configuration after the event. In contrast, the comparison of Normalized Difference Vegetation Index (NDVI) maps revealed that 18,500 m² of embryonic dune vegetation, which represented 35 % of the existing plant community, was removed by works on the beach and by trampling of festival attendees. To authors' knowledge, this is the first work that evaluates the eco-geomorphological impact of a massive beach music festival on the delicate coastal ecosystem. Overall, it contributes in raising awareness for making these events more respectful of the coastal environment.

Dunal plants intercepting macrolitter: Implications for beach clean-ups

Coastal vegetation intercepts macroplastics and, consequently, it may represent a reservoir of anthropogenic litter and organic wrack. We aimed at investigating (i) the abundance variation of macrolitter from the beach to foredune and backdune (three cross-shore plots over 20 long-shore sectors) and (ii) the role of the halo-psammophilous plants and Phragmites australis reedbed in intercepting the macrolitter, respectively, in the foredunes and backdunes. The vegetation in the foredunes (mainly halo-psammophilous species) acted as a first interception belt for macrolitter, while the bigger litter reached the backdunes. Our results might be of great concern with implications for beach clean-ups - which must also be mainly focused in foredunes and backdunes, however warning operators in advance that they could damage the vegetation by trampling on.

Understanding through drone image analysis the interactions between geomorphology, vegetation and marine debris along a sandy spit

Marine litter (ML) is recognized as one of the main socio-economic and environmental concerns and monitoring operations have been realized worldwide in order to collect information on the types, quantities and distribution of marine debris. In this study, we used Unmanned Aerial Vehicle (UAV) images to map the presence of ML on a coastal spit in relation to geomorphological aspects and vegetation. Our results show that ML is present everywhere, but concentrates in the beach wrack, dunes, and saltmarshes, highlighting the role of the vegetation in trapping ML. Moreover, ML will most probably remain trapped by the saltmarsh vegetation, since they are not visible and easily accessible to allow cleaning operations. On the contrary, cleaning operations may remove the ML present in the beach wrack. Finally, our results provide useful information to support decision-makers for improving beach cleaning activities in the Po river Delta areas (Italy).

The halophyte Cakile maritima Scop. 1772 as a trap of plastic litter on the Moroccan coast

Some plant communities of coastal dunes may affect the magnitude and distribution of litter on the ecosystem. In this study, the aim is to assess the aptitude of the halophyte Cakile maritima Scop. 1772 to be a trap and sink of plastic litter on the Moroccan Atlantic coast. Overall, a significant difference was noted between plastic litter trapped in C. maritima patches (1173 items) and control plots (502 items). Food containers and ropes were the most common trapped items. Shoreline and recreational activities, followed by dumping and ocean/waterway activities are the main sources of the trapped plastic items. The findings suggest the expansion of the cleaning operations to include coastal dunes, the need to change behavior among beachgoers in regard to food plastics disposal, as well the control of C. maritima distribution in the study area, and similar plant species in other regions.

Beach litter survey by drones: Mini-review and discussion of a potential standardization

The abundance of beach litter has been increasing globally during the last decades, and it is an issue of global concern. A new survey strategy, based on uncrewed aerial vehicles (UAV, aka drones), has been recently adopted to improve the monitoring of beach macro-litter items abundance and distribution. This work identified and analysed the 15 studies that used drone for beach litter surveys on an operational basis. The analysis of technical parameters for drone flight deployment revealed that flight altitude varied between 5 and 40 m. The analysis of final assessments showed that, through manual and/or automated items detection on images, most of studies provided litter bulk characteristics (type, material and size), along with litter distribution maps. The potential standardization of drone-based litter survey would allow a comparison among surveys, however it seems difficult to propose a standard set of flight parameters, given the wide variety of coastal environments, the different devices available, and the diverse objectives of drone-based litter surveys. On the other hand, in our view, a set of common outcomes can be proposed, based on the grid mapping process, which can be easily generated following the procedure indicated in the paper. This work sets the ground for the development of a standardized protocol for drone litter data collection, analysis and assessments. This would allow the provision of broad scale comparative studies to support coastal management at both national and international scales.

UAV remote sensing applications in marine monitoring: Knowledge visualization and review

With the booming development of information technology and the growing demand for remote sensing data, unmanned aerial vehicle (UAV) remote sensing technology has emerged. In recent years, UAV remote sensing technology has developed rapidly and has been widely used in the fields of military defense, agricultural monitoring, surveying and mapping management, and disaster and emergency response and management. Currently, increasingly serious marine biological and environmental problems are raising the need for effective and timely monitoring. Compared with traditional marine monitoring technologies, UAV remote sensing is becoming an important means for marine monitoring thanks to its flexibility, efficiency and low cost, while still producing systematic data with high spatial and temporal resolutions. This study visualizes the knowledge domain of the application and research advances of UAV remote sensing in marine monitoring by analyzing 1130 articles (from 1993 to early 2022) using a bibliometric approach and provides a review of the application of UAVs in marine management mapping, marine disaster and environmental monitoring, and marine wildlife monitoring. It aims to promote the extensive application of UAV remote sensing in the field of marine research.

Leached degradation products from beached microplastics: A potential threat to coastal dune plants

Plants play a fundamental role in maintaining coastal dunes but also accumulate littered microplastics (MPs). Migration tests suggest that naturally weathered MPs can leach out a broader range of potentially phytotoxic chemicals than virgin MPs. Thus, assessing MPs effects on plants using beached-collected particles rather than virgin ones is critically important. Here, the effects on plants of leachates from two pools of beach-collected and virgin MPs, high-density polyethylene (HDPE) and polypropylene (PP), and their mixture, were explored combining toxicity tests and chemical analyses. Phytotoxicity of MP leachates at different dilutions was evaluated under standard laboratory conditions using test species and under environmentally realistic conditions using the dune species Thinopyrum junceum. Leachates from beached PP and HDPE adversely affected all species, and the extent of these effects varied according to polymer type, concentration, and species. Virgin MPs had weaker effects than beached ones. Several potentially phytotoxic oxidized compounds were detected in water by GC/MS analysis, and their amount estimated. Results indicate that the molecular species leaching from beached MPs - at ppm concentration levels for the individual chemical species - can inhibit plant growth, and the effects of leachates from mixtures of degraded MPs can differ from those from individual polymers, highlighting the need for further investigation of MPs consequences for coastal ecosystems.

Detection of River Plastic Using UAV Sensor Data and Deep Learning

Plastic pollution is a critical global issue. Increases in plastic consumption have triggered increased production, which in turn has led to increased plastic disposal. In situ observation of plastic litter is tedious and cumbersome, especially in rural areas and around transboundary rivers. We therefore propose automatic mapping of plastic in rivers using unmanned aerial vehicles (UAVs) and deep learning (DL) models that require modest compute resources. We evaluate the method at two different sites: the Houay Mak Hiao River, a tributary of the Mekong River in Vientiane, Laos, and Khlong Nueng canal in Talad Thai, Khlong Luang, Pathum Thani, Thailand. Detection models in the You Only Look Once (YOLO) family are evaluated in terms of runtime resources and mean average Precision (mAP) at an Intersection over Union (IoU) threshold of 0.5. YOLOv5s is found to be the most effective model, with low computational cost and a very high mAP of 0.81 without transfer learning for the Houay Mak Hiao dataset. The performance of all models is improved by transfer learning from Talad Thai to Houay Mak Hiao. Pre-trained YOLOv4 with transfer learning obtains the overall highest accuracy, with a 3.0% increase in mAP to 0.83, compared to the marginal increase of 2% in mAP for pre-trained YOLOv5s. YOLOv3, when trained from scratch, shows the greatest benefit from transfer learning, with an increase in mAP from 0.59 to 0.81 after transfer learning from Talad Thai to Houay Mak Hiao. The pre-trained YOLOv5s model using the Houay Mak Hiao dataset is found to provide the best tradeoff between accuracy and computational complexity, requiring model resources yet providing reliable plastic detection with or without transfer learning. Various stakeholders in the effort to monitor and reduce plastic waste in our waterways can utilize the resulting deep learning approach irrespective of location.

What Are Lake Beaches Made of? An Assessment of Plastic Beach Litter on the Shores of Como Bay (Italy)

Plastic waste dispersion is a well-recognized environmental threat, despite continuous efforts towards improving waste disposal management over the last few decades. Plastic litter is known to strongly impact upon water bodies and shorelines, affecting the health of ecosystems and impacting upon the aesthetic value of sites. Moreover, plastic waste that is abandoned on beaches contributes towards different degradation processes that potentially lead to the formation of secondary microplastics (MPs), with likely cascade effects upon the whole ecosystem. In this view, this study aims to characterize the plastic beach litter found on the shores of the western basin of Como Lake (Italy) to better understand the origin of MPs in littoral sediments, including the recognition of object typologies and the chemical characterization of polymers using Fourier-transformed infrared analysis (FTIR). The results highlighted that the most abundant polymers on beaches are polypropylene (PP) and polyethylene (PE), representing 73% of the collected polymers. This confirms that floating, low-density polymers are more likely to accumulate on beaches. Moreover, almost 66% of litter is represented by commonly used manufactured items (disposable objects, packaging, and everyday items). This evidence, combined with the analysis of the main environmental features of the sampling sites (the main winds, distance to urban areas, and the presence of tributaries) indicate that abundance of beached litter is mainly linked to beach accessibility and the local winds. These results highlight that multiple factors affect the environmental fate of plastic litter and give insights into the assessment of secondary microplastics in beach sediments.

Quantity and type of coastal debris pollution in Taiwan: A rapid assessment with trained citizen scientists using a visual estimation method

Ongoing monitoring of the distribution and composition of coastal debris is a prerequisite for efficient management and cleanups. Therefore, we conducted a rapid assessment of coastal debris along the 1210 km coastline of Taiwan using a visual estimation method. Forty-nine citizen scientists were intensively trained to correctly identify the volume and types of debris. At 121 sampling locations randomly placed along Taiwan's coastline, the citizen scientists recorded the pollution level and the three most abundant debris types within a 100-m transect during four surveys in 2018-2019. Averaging over the four surveys, the mean amount of coastal debris was estimated to be 406.6 kg/km, and the three most abundant debris types were plastic bottles, foamed plastics, and fishing nets and ropes. Using a statistical test which avoids spatial pseudoreplication, we showed that north-facing coastlines had significantly higher pollution levels than the other coastlines, which we suggest is deposited there during strong winter winds. We also showed that fishery-related debris was a much more important part of coastal debris when the volume of it was determined instead of just the number of items. Mean pollution levels were further associated with wind speed, coastline type, and the distance to presumed pollution sources. Our results compare well with similar surveys conducted in Japan and South Korea. In each country, the debris was highly aggregated, which means it was concentrated in a few highly polluted localities. Therefore, the visual estimation method can effectively guide cleanup efforts to the most polluted areas and also reliably generate long-term monitoring data.

Beach debris quantity and composition around the world: A bibliometric and systematic review

Anthropogenic pollution of marine ecosystems caused by beach debris has become a serious environmental concern in the last few decades. Regarding the raising production of beach debris, the present work aimed to summarize the quantity and quality of beach debris reported from different beach areas of the world. Also, a bibliometric analysis was used to analyze research trends and upgrade knowledge in this research area. Using Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA), the eligible papers reviewed regarding beach debris abundance along with their composition from 2010, which were extracted from the Scopus database. The results of the study showed that plastic items represented the dominant material (61.25%), followed by food (5.88%), wood (5.78%), metals (5.2%), and glass (5%). Further, the beaches studied were classified into three degrees, including highly polluted (31.5 items/m2), moderate polluted (3.47 items/m2), and low polluted (0.37 items/m2), based on the average abundance of debris.

Where does marine litter hide? The Providencia and Santa Catalina Island problem, SEAFLOWER Reserve (Colombia)

The SEAFLOWER Biosphere Reserve (SBR) is the largest Marine Protected Area in the Caribbean Sea and the second largest in Latin America. Marine protected areas are under pressure from various stressors, one of the most important issues being pollution by marine litter, especially plastic. In this study our aim is to establish the distribution pattern and potential sources of solid waste in the different marine/coastal ecosystems of the islands of Providencia and Santa Catalina (SBR), as well as assess any interconnections between these ecosystems. At the same time, the distribution characteristics of marine litter in the different compartments facilitated a more dynamic understanding of the load of marine litter supplied by the islands, both locally and externally. We observed that certain ecosystems, principally back-beach vegetation and mangroves, act as crucial marine litter accumulation zones. Mangroves are important hotspots for plastic accumulation, with densities above eight items/m² (minimum 8.38 and maximum 10.38 items/m²), while back-beach vegetation (minimum 1.43 and maximum 7.03 items/m²) also removes and stores a portion of the marine litter that arrives on the beaches. Tourist beaches for recreational activities have a low density of marine litter (minimum 0.01 and maximum 0.72 items/m²) due to regular clean-ups, whereas around non-tourist beaches, there is a greater variety of sources and accumulation (minimum 0.31 and maximum 5.41 items/m²). The low density of marine litter found on corals around the island (0-0.02 items/m²) indicates that there is still no significant marine litter stream to the coral reefs. Identifying contamination levels in terms of marine litter and possible flows between ecosystems is critical for adopting management and reduction strategies for such residues.

On the 3D Reconstruction of Coastal Structures by Unmanned Aerial Systems with Onboard Global Navigation Satellite System and Real-Time Kinematics and Terrestrial Laser Scanning

A wide variety of hard structures protect coastal activities and communities from the action of tides and waves worldwide. It is fundamental to monitor the integrity of coastal structures, as interventions and repairs may be needed in case of damages. This work compares the effectiveness of an Unmanned Aerial System (UAS) and a Terrestrial Laser Scanner (TLS) to reproduce the 3D geometry of a rocky groin. The Structure-from-Motion (SfM) photogrammetry technique applied on drone images generated a 3D point cloud and a Digital Surface Model (DSM) without data gaps. Even though the TLS returned a 3D point cloud four times denser than the drone one, the TLS returned a DSM which was not representing about 16% of the groin (data gaps). This was due to the occlusions encountered by the low-lying scans determined by the displaced rocks composing the groin. Given also that the survey by UAS was about eight time faster than the TLS, the SFM-MV applied on UAS images was the most suitable technique to reconstruct the rocky groin. The UAS remote sensing technique can be considered a valid alternative to monitor all types of coastal structures, to improve the inspection of likely damages, and to support coastal structure management.

Beached and Floating Litter Surveys by Unmanned Aerial Vehicles: Operational Analogies and Differences

The abundance of litter pollution in the marine environment has been increasing globally. Remote sensing techniques are valuable tools to advance knowledge on litter abundance, distribution and dynamics. Images collected by Unmanned Aerial Vehicles (UAV, aka drones) are highly efficient to map and monitor local beached (BL) and floating (FL) marine litter items. In this work, the operational insights to carry out both BL and FL surveys using UAVs are detailly described. In particular, flight planning and deployment, along with image products processing and analysis, are reported and compared. Furthermore, analogies and differences between UAV-based BL and FL mapping are discussed, with focus on the challenges related to BL and FL item detection and recognition. Given the efficiency of UAV to map BL and FL, this remote sensing technique can replace traditional methods for litter monitoring, further improving the knowledge of marine litter dynamics in the marine environment. This communication aims at helping researchers in planning and performing optimized drone-based BL and FL surveys.

Operational use of multispectral images for macro-litter mapping and categorization by Unmanned Aerial Vehicle

The use of Unmanned Aerial Systems (UAS, aka drones) has shown to be feasible to perform marine litter surveys. We operationally tested the use of multispectral images (5 bands) to classify litter type and material on a beach-dune system. For litter categorization by their multispectral characteristics, the Spectral Angle Mapping (SAM) technique was adopted. The SAM-based categorization of litter agreed with the visual classification, thus multispectral images can be used to fasten and/or making more robust the manual RGB image screening. Fully automated detection returned an F-score of 0.64, and a reasonable categorization of litter. Overall, the image-based litter density maps were in line with the manual detection. Assessments were promising given the complexity of the study area, where different dunes plants and partially-buried items challenged the UAS-based litter detection. The method can be easily implemented for both floating and beached litter, to advance litter survey in the environment.

Pixel-level image classification for detecting beach litter using a deep learning approach

Mitigating and preventing beach litter from entering the ocean is urgently required. Monitoring beach litter solely through human effort is cumbersome, with respect to both time and cost. To address this problem, an artificial intelligence technique that can automatically identify different-sized beach litter is proposed. The technique was established by training a deep learning model that enables pixel-wise classification (semantic segmentation) using beach images taken by an observer on the beach. Eight segmentation classes that include two beach litter classes were defined, and the results were qualitatively and quantitatively verified. Segmentation performance was adequately high based on three metrics: Intersection over Union (IoU), precision, and recall, although there is room for further improvement. The potency of the method was demonstrated when it was applied to images taken in different places from training data images, and the coverage of artificial litter calculated and discussed using drone images provided ground truth.

Composition, sources, abundance and seasonality of Marine Litter in the Çakalburnu lagoon coast of Aegean Sea

The Aegean Sea is one of the most contaminated by marine litter (ML) in the World. In this study, the Turkish Aegean Region was evaluated in light of the sources, abundance and composition of ML along Çakalburnu Lagoon coast. Macroscopic ML with > 3 cm was collected and separated into composition and sources categories. ML abundance was calculated by its density in items/m² (Mean ± SD). Beach cleanliness was evaluated according to Clean-Coast Index (CCI). Seasonality was found as factor for ML composition, sources and abundance at Çakalburnu coast. Plastic was the most abundant material, followed by unidentifiable items. The major sources of ML were mixed packaging, domestic and fisheries activities. The mean ML density was 0.64 ± 0.09 items/m². Çakalburnu coast was classified as dirty during all seasons. Therefore, ML contamination on Çakalburnu coast represent a potential threat to coastal and marine environments. Thus, the present study can serve as a base for the elaboration of mitigating actions urgently needed at Çakalburnu Lagoon.

Is coastal erosion a source of marine litter pollution? Evidence of coastal dunes being a reservoir of plastics

This baseline reports scientific evidence of marine litter items embedded in the dune volume at two study sites on the North Atlantic Portuguese coast. We described how stranded litter participate in the sand dune growth/erosion processes on a natural beach-dune system. From the storm-eroded foredunes on the urbanized beach, we documented exhumed plastics with age up to 38 years. Whether litter burial was due to beach-dune morphodynamic processes, or to irresponsible and/or illegal dumping in the past, this work emphasises the need of improving buried litter census and monitoring on coastal dunes. Coastal erosion processes may further exhume litter buried in dune volumes and on other coastal environments over short- and long-term, re-exposing items into the marine environment. Thus, coastal erosion can be accounted as a secondary diffuse source of littering pollution, beside the multiple sources already identified in the environment.

Coastal dunes as a sink and secondary source of marine plastics: A study at Perran Beach, southwest England

Plastic food packaging and containers (n = 263) have been retrieved from the scarped foredunes at Perran Beach, SW England, following a storm surge. Samples displayed evidence of cracking, scratching, discolouration, staining and hydroxyl and carbonyl stretching, but legible text indicating their origin, dates of manufacture/expiration, packaging codes and logos, coupled with online product searches, allowed 25 food packets and 87 containers to be aged. Estimates of food packaging age spanned a 43-year period (1975-2018), with a median age of 25 years, while estimates for containers spanned 57 years (1962-2019), with a median age of 19 years. Plastic derived from local littering and offshore sources appears to be trapped within the foredunes for years to decades and subsequently released as "fresh" beach litter following surges sufficient to effect scarping. Dunal systems may act as significant reservoirs of historical plastics and play a critical role in their recycling and retention in the coastal zone.

Carpobrotus spp. patches as trap for litter: Evidence from a Mediterranean beach

Dunal plants may affect the patterns of deposition of beach litter. In this study, we aimed at evaluating if Carpobrotus spp. patches may act as a litter trap in coastal dune systems. To do so, we counted the number of macrolitter occurring in both Carpobrotus and control (embryo dune vegetation) patches classifying each item into categories according to the Marine Strategy. Totally, we observed a significant difference between litter trapped in Carpobrotus (331 items, representing 62.4% of the total beach litter) and control (199, 37.6%). Plastic fragments were the most trapped items by both Carpobrotus (46.2%) and control patches (47.2%). We also calculated the item co-occurrence, obtaining a random aggregated 'litter community'. The main emerging output is that Carpobrotus patches act as filter in respect to different anthropogenic materials (overall plastics), suggesting that alien plant management actions may contribute to solve beach litter issues as well.

A rapid assessment of litter magnitudes and impacts along the Torre Guaceto marine protected area (Brindisi, Italy)

This study focuses on assessing litter magnitudes along the Torre Guaceto Marine Protected Area (Brindisi, Italy). Collected litter was grouped into twenty different types and classified into four litter typologies according to the Guidance on Monitoring of Marine Litter in European Seas. All data were analyzed using an index-based approach that allowed the classification of a coastal stretch in terms of cleanliness, and presence of plastics as well hazardous items. The average litter abundance in the study area was 0.5 items/m², being plastics the most common litter item. Hazardous litter items were found along the study area, reaching 21.3% of the total collected items. The application of environmental indices allowed to define the study area with a "moderate cleanliness" and a "moderate" presence of hazardous litter items. Sampled litter typologies and related magnitudes suggest a combination of sources that mainly include direct activities on the nearby coastal zones and river basins (dumping).

Citizen Science for Marine Litter Detection and Classification on Unmanned Aerial Vehicle Images

Unmanned aerial vehicles (UAV, aka drones) are being used for mapping macro-litter in the environment. As drone images require a manual processing task for detecting marine litter, it is of interest to evaluate the accuracy of non-expert citizen science operators (CSO) in performing this task. Students from Italian secondary schools (in this work, the CSO) were invited to identify, mark, and classify stranded litter items on a UAV orthophoto collected on an Italian beach. A specific training program and working tools were developed for the aim. The comparison with the standard in situ visual census survey returned a general underestimation (50%) of items. However, marine litter bulk categorisation was fairly in agreement with the in situ survey, especially for sources classification. The concordance level among CSO ranged between 60% and 91%, depending on the item properties considered (type, material, and colour). As the assessment accuracy was in line with previous works developed by experts, remote detection of marine litter on UAV images can be improved through citizen science programs, upon an appropriate training plan and provision of specific tools.

UAV Approach for Detecting Plastic Marine Debris on the Beach: A Case Study in the Po River Delta (Italy)

Anthropogenic marine debris (AMD) represent a global threat for aquatic environments. It is important to locate and monitor the distribution and presence of macroplastics along beaches to prevent degradation into microplastics (MP), which are potentially more harmful and more difficult to remove. UAV imaging represents a quick method for acquiring pictures with a ground spatial resolution of a few centimeters. In this work, we investigate strategies for AMD mapping on beaches with different ground resolutions and with elevation and multispectral data in support of RGB orthomosaics. Operators with varying levels of expertise and knowledge of the coastal environment map the AMD on four to five transects manually, using a range of photogrammetric tools. The initial survey was repeated after one year; in both surveys, beach litter was collected and further analyzed in the laboratory. Operators assign three levels of confidence when recognizing and describing AMD. Preliminary validation of results shows that items identified with high confidence were almost always classified properly. Approaching the detected items in terms of surface instead of a simple count increased the percentage of mapped litter significantly when compared to those collected. Multispectral data in near-infrared (NIR) wavelengths and digital surface models (DSMs) did not significantly improve the efficiency of manual mapping, even if vegetation features were removed using NDVI maps. In conclusion, this research shows that a good solution for performing beach AMD mapping can be represented by using RGB imagery with a spatial resolution of about 200 pix/m for detecting macroplastics and, in particular, focusing on the largest items. From the point of view of assessing and monitoring potential sources of MP, this approach is not only feasible but also quick, practical, and sustainable.

Drones for litter mapping: An inter-operator concordance test in marking beached items on aerial images

Unmanned aerial systems (UAS, aka drones) are being used to map macro-litter on the environment. Sixteen qualified researchers (operators), with different expertise and nationalities, were invited to identify, mark and categorize the litter items (manual image screening, MS) on three UAS images collected at two beaches. The coefficient of concordance (W) among operators varied between 0.5 and 0.7, depending on the litter parameter (type, material and colour) considered. Highest agreement was obtained for the type of items marked on the highest resolution image, among experts in litter surveys (W = 0.86), and within territorial subgroups (W = 0.85). Therefore, for a detailed categorization of litter on the environment, the MS should be performed by experienced and local operators, familiar with the most common type of litter present in the target area. This work provides insights for future operational improvements and optimizations of UAS-based images analysis to survey environmental pollution.

Detecting stranded macro-litter categories on drone orthophoto by a multi-class Neural Network

The use of Unmanned Aerial Systems (UAS, aka drones) images for mapping macro-litter in the environment have been exponentially increasing in the recent years. In this work, we developed a multi-class Neural Network (NN) to automatically identify stranded plastic litter categories on an UAS-derived orthophoto. The best results were assessed for items that did not have substantial intra-class colour variability, such as octopus pots and fishing ropes (F-score = 61%, on average). Instead, performance was poor (37%) for plastic bottles and fragments, due to their changing intra-class colours. On average, the performance improved 24% when the binary detection (litter/non-litter, F-Score = 73%) was considered, however this approach did not discriminate the litter categories. This work gives a new perspective for the automated litter detection on drone images, suggesting that colour-based approach can be used to improve the categorization of stranded litter on UAS orthophoto.