Marine Litter Dataset

## Overview

Marine Litter Dataset is a dataset for object detection tasks - it contains Garbage annotations for 4,945 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Global Lagrangian dataset of Marine litter

This dataset regroups 12 yearly files (global-marine-litter-[2010–2021].nc) combining monthly releases of 32,300 particles initially distributed across the globe following global Mismanaged Plastic Waste (MPW) inputs. The particles are advected with OceanParcels (Delandmeter, P and E van Sebille, 2019) using ocean surface velocity, a wind drag coefficient of 1%, and a small random walk component with a uniform horizontal turbulent diffusion coefficient of Kh = 1m2s-1 representing unresolved turbulent motions in the ocean (see Chassignet et al. 2021 for more details).

Global oceanic current and atmospheric wind

Ocean surface velocities are obtained from GOFS3.1, a global ocean reanalysis based on the HYbrid Coordinate Ocean Model (HYCOM) and the Navy Coupled Ocean Data Assimilation (NCODA; Chassignet et al., 2009; Metzger et al., 2014). NCODA uses a three-dimensional (3D) variational scheme and assimilates satellite and altimeter observations as well as in-situ temperature and salinity measurements from moored buoys, Expendable Bathythermographs (XBTs), Argo floats (Cummings and Smedstad, 2013). Surface information is projected downward into the water column using Improved Synthetic Ocean Profiles (Helber et al., 2013). The horizontal resolution and the temporal frequency for the GOF3.1 outputs are 1/12° (8 km at the equator, 6 km at mid-latitudes) and 3-hourly, respectively. Details on the validation of the ocean circulation model are available in Metzger et al. (2017).

Wind velocities are obtained from JRA55, the Japanese 55-year atmospheric reanalysis. The JRA55, which spans from 1958 to the present, is the longest third-generation reanalysis that uses the full observing system and a 4D advanced data assimilation variational scheme. The horizontal resolution of JRA55 is about 55 km and the temporal frequency is 3-hourly (see Tsujino et al. (2018) for more details).

Marine Litter Sources

The marine litter sources are obtained by combining MPW direct inputs from coastal regions, which are defined as areas within 50 km of the coastline (Lebreton and Andrady 2019), and indirect inputs from inland regions via rivers (Lebreton et al. 2017).

File Format

The locations (lon, lat), the corresponding weight (tons), and the source (1: land, 0: river) associated with the 32,300 particles are described in the file initial-location-global.csv. The particle trajectories are regrouped into yearly files (marine-litter-[2010–2021].nc) which contain 12 monthly releases, resulting in a total of 387,600 trajectories per file. More precisely, in each of the yearly files, the first 32,300 lines contain the trajectories of particles released on January 1st, then lines 32,301–64,600 contain the trajectories of particles released on February 1st, and so on. The trajectories are recorded daily and are advected from their release until 2021-12-31, resulting in longer time series for earlier years of the dataset.

References

Chassignet, E. P., Hurlburt, H. E., Metzger, E. J., Smedstad, O. M., Cummings, J., Halliwell, G. R., et al. (2009). U.S. GODAE: global ocean prediction with the hybrid coordinate ocean model (HYCOM). Oceanography 22, 64–75. doi: 10.5670/oceanog.2009.39

Chassignet, E. P., Xu, X., and Zavala-Romero, O. (2021). Tracking Marine Litter With a Global Ocean Model: Where Does It Go? Where Does It Come From?. Frontiers in Marine Science, 8, 414, doi: 10.3389/fmars.2021.667591

Cummings, J. A., and Smedstad, O. M. (2013). “Chapter 13: variational data assimilation for the global ocean”, in Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications, Vol. II, eds S. Park and L. Xu (Berlin: Springer), 303–343. doi: 10.1007/978-3-642-35088-7_13

Delandmeter, P., and van Sebille, E. (2019). The Parcels v2.0 Lagrangian framework: new field interpolation schemes. Geosci. Model Dev. 12, 3571–3584. doi: 10.5194/gmd-12-3571-2019

Helber, R. W., Townsend, T. L., Barron, C. N., Dastugue, J. M., and Carnes, M. R. (2013). Validation Test Report for the Improved Synthetic Ocean Profile (ISOP) System, Part I: Synthetic Profile Methods and Algorithm. NRL Memo. Report, NRL/MR/7320—13-9364 Hancock, MS: Stennis Space Center.

Metzger, E. J., Smedstad, O. M., Thoppil, P. G., Hurlburt, H. E., Cummings, J. A., Wallcraft, A. J., et al. (2014). US Navy operational global ocean and Arctic ice prediction systems. Oceanography 27, 32–43, doi: 10.5670/oceanog.2014.66.

Metzger, E., Helber, R. W., Hogan, P. J., Posey, P. G., Thoppil, P. G., Townsend, T. L., et al. (2017). Global Ocean Forecast System 3.1 validation test. Technical Report. NRL/MR/7320–17-9722. Hancock, MS: Stennis Space Center, 61.

Lebreton, L., and Andrady, A. (2019). Future scenarios of global plastic waste generation and disposal. Palgrave Commun. 5:6, doi: 10.1057/s41599-018-0212-7.

Lebreton, L., van der Zwet, J., Damsteeg, J. W., Slat, B., Andrady, A., and Reisser, J. (2017). River plastic emissions to the world’s oceans. Nat. Commun. 8:15611, doi: 10.1038/ncomms15611.

Tsujino H., S. Urakawa, H. Nakano, R.J. Small, W.M. Kim, S.G. Yeager, G. Danabasoglu, T. Suzuki, J.L. Bamber, M. Bentsen, C. Böning, A. Bozec, E.P. Chassignet, E. Curchitser, F. Boeira Dias, P.J. Durack, S.M. Griffies, Y. Harada, M. Ilicak, S.A. Josey, C. Kobayashi, S. Kobayashi, Y. Komuro, W.G. Large, J. Le Sommer, S.J. Marsland, S. Masina, M. Scheinert, H. Tomita, M. Valdivieso, and D. Yamazaki, 2018. JRA-55 based surface dataset for driving ocean-sea-ice models (JRA55-do). Ocean Modelling, 130, 79-139, doi: 10.1016/j.ocemod.2018.07.002.

MARIne Debris Archive (MARIDA) is a marine debris-oriented dataset on Sentinel-2 satellite images. It also includes various sea features that co-exist. MARIDA is primarily focused on the weakly supervised pixel-level semantic segmentation task.

Citation: Kikaki K, Kakogeorgiou I, Mikeli P, Raitsos DE, Karantzalos K (2022) MARIDA: A benchmark for Marine Debris detection from Sentinel-2 remote sensing data. PLoS ONE 17(1): e0262247. https://doi.org/10.1371/journal.pone.0262247

For the quick start guide visit marine-debris.github.io

The dataset contains:

i. 1381 patches (256 x 256) structured by Unique Dates and S2 Tiles. Each patch is provided along with the corresponding masks of pixel-level annotated classes (*_cl) and confidence levels (*_conf). Patches are given in GeoTiff format.

ii. Shapefiles data in WGS’84/ UTM projection, with file naming convention following the scheme: s2_dd-mm-yy_ttt, where s2 denotes the S2 sensor, dd denotes the day, mm the month, yy the year and ttt denotes the S2 tile. Shapefiles include the class of each annotation along with the confidence level and the marine debris report description.

iii. Train, Validation and Test split for evaluating machine learning algorithms.

iv. The assigned multi-labels for each patch (labels_mapping.txt).

The mapping between Digital Numbers and Classes is:

1: Marine Debris
2: Dense Sargassum
3: Sparse Sargassum
4: Natural Organic Material
5: Ship
6: Clouds
7: Marine Water
8: Sediment-Laden Water
9: Foam
10: Turbid Water
11: Shallow Water
12: Waves
13: Cloud Shadows
14: Wakes
15: Mixed Water

The mapping between Digital Numbers and Confidence level is:

1: High
2: Moderate
3: Low

The mapping between Digital Numbers and marine debris Report existence is:

1: Very close
2: Away
3: No

The final uncompressed dataset requires 4.38 GB of storage.

Floating marine debris is a global pollution problem which leads to the loss of marine and terrestrial biodiversity. Large swaths of marine debris are also navigational hazards to ocean vessels. The use of Earth observation data and artificial intelligence techniques can revolutionize the detection of floating marine debris on satellite imagery and pave the way to a global monitoring system for controlling and preventing the accumulation of marine debris in oceans. This dataset consists of images of marine debris which are 256 by 256 pixels in size and labels which are bounding boxes with geographical coordinates. The images were obtained from PlanetScope optical imagery which has a spatial resolution of approximately 3 meters. In this dataset, marine debris consists of floating objects on the ocean surface which can belong to one or more classes namely plastics, algae, sargassum, wood, and other artificial items. Several studies were used for data collection and validation. While a small percentage of the dataset represents the coastlines of Ghana and Greece, most of the observations surround the Bay Islands in Honduras. The marine debris detection models created and the relevant code for using this dataset can be found here.

Marine floating litter refers to items that have been produced and used by humans and have been intentionally or unintentionally discarded or lost at sea, in rivers, or on the shore. These items can be transported to the sea through various means such as wind, rainwater, rivers, or sewage. Monitoring of floating marine litter (FML) in the south-western Black Sea was carried out in the period 09.2021 - 12.2023. Eight transects, each with a length of 2250 m and an area of 13500 m2 were observed. A total of 502 objects were described. 88.72% of the floating marine litter was made of plastic. The amount of FML varied between tansects and values ranged between 168 - 730 Items.km-2. The average amount of floating marine litter over the entire monitoring period was 403 ± 692 Items.km-2. Seasonal and annual differences in the amount of floating debris were observed. In 2022, the amount varied between 0 and 252 Items.km-2, with an average of 120±191 Items.km-2 across all transects. In 2023, the floating marine litter in the transects ranged from 352 to 1407 Items.km-2, with an average of 791±957 Items.km-2. The highest concentration of FML during the monitoring period was observed in September, with a concentration of 636± 1053 Items.km-2. The lowest concentration occurred in April, with a concentration of 70± 145 Items.km-2. The most common types of litter, in order of relevance, were plastic pieces measuring 2.5 to 50 cm, cover/packaging, plastic bags, wood boards, plastic bottles, synthetic rope, cups and cup lids, plastic caps and lids, balloons and balloon sticks, and food containers. The concentration of FML in the sea is strongly influenced by local severe weather events, which can result in concentrations 2 to 3 times higher than the average values. These higher concentrations were recorded in September 2023 (870±559 Items.km-2) and November 2023 (1481±1458 Items.km-2).

The dataset contains information regarding marine litter on the Romanian beaches, collected during 3 seasons: winter, spring and autumn. The methodology used is MSFD related and 9 beach sectors were monitored, from Vama Veche (South) to Edighiol (DanuBe Delta Biosphere Reserve).

Marine Litter Collecting Market Outlook

The global marine litter collecting market size was valued at approximately USD 1.6 billion in 2023 and is expected to reach around USD 3.7 billion by 2032, growing at a compound annual growth rate (CAGR) of 9.2% during the forecast period. The rise in awareness regarding the detrimental effects of marine litter on the environment and human health, coupled with technological advancements in marine litter collection methods, are key growth factors driving the market.

One of the primary growth drivers of the marine litter collecting market is the increasing global awareness about environmental sustainability. Governments and non-governmental organizations (NGOs) are initiating numerous campaigns to educate the public about the importance of marine biodiversity and the negative impacts of marine litter. This awareness is propelling demand for effective solutions to tackle the issue, thereby boosting market growth. Moreover, international agreements and regulations aimed at reducing marine pollution are creating favorable conditions for market expansion.

Technological advancements are also significantly contributing to the growth of the marine litter collecting market. The development and deployment of autonomous underwater vehicles (AUVs), surface vessels, and drones equipped with advanced sensors and AI capabilities have revolutionized the methods of marine litter collection. These technological innovations enhance the efficiency and effectiveness of marine litter collection processes, reducing manual labor and operational costs. As a result, there is a growing adoption of these advanced technologies by various stakeholders in the marine litter collection sector.

Furthermore, the increasing participation of the private sector in marine litter collection initiatives is another crucial growth factor. Many corporations are investing in marine litter collection technologies as part of their corporate social responsibility (CSR) initiatives. Additionally, the involvement of various industries such as shipping, tourism, and fisheries in addressing marine litter issues is driving market growth. These industries recognize the importance of clean marine environments for their operations and are consequently contributing to the demand for marine litter collection solutions.

In addition to the growing involvement of various industries, the need for specialized services such as Lagoon Cleanout Service is becoming increasingly apparent. Lagoons, often used for wastewater treatment and other industrial purposes, can accumulate significant amounts of debris and contaminants over time. Effective cleanout services are crucial for maintaining the ecological balance and preventing further pollution of marine environments. By implementing regular lagoon cleanouts, industries can ensure that their operations are not contributing to the larger issue of marine litter. This proactive approach not only supports environmental sustainability but also aligns with corporate social responsibility goals, fostering a cleaner and healthier ecosystem.

From a regional perspective, Asia Pacific is expected to witness significant growth in the marine litter collecting market. The region is home to some of the world's most polluted rivers and coastlines, making marine litter collection a critical issue. Governments in countries such as China and India are implementing stringent regulations to control marine pollution and are investing in advanced marine litter collection technologies. North America and Europe are also anticipated to show substantial growth due to the presence of well-established marine conservation programs and strong regulatory frameworks. In contrast, Latin America and the Middle East & Africa are likely to witness moderate growth, driven by emerging initiatives and investments in marine litter management.

Product Type Analysis

The marine litter collecting market is segmented by product type into Autonomous Underwater Vehicles (AUVs), surface vessels, drones, and others. AUVs are gaining significant traction owing to their ability to operate autonomously and reach underwater zones that are difficult for humans to access. These vehicles are equipped with advanced sensors and imaging systems that enhance their capability to detect and collect marine litter efficiently. The technological sophistication of AUVs makes them a preferred choice for deep-sea litter collection activities, thereby driving their demand in the m

Title: Marine Litter and Plastic Pollution Action PlansSummary: Visualization of the distribution of adopted Action Plans across the world. Based on the data currently on the GPML platform.Entity: United Nations Environment Programme (UNEP)Source URL: https://digital.gpmarinelitter.org/knowledge/library/resource/map/action-planTime Period: 1975-2022Methodology: Action plans analyzed and categorized from the GPML knowledge library.Frequency Update: NeverLast Update: 22-05-2023Geo-Coverage: GlobalLicensing: Public

This dataset is part of the 2018 Belgian submission for the Marine Strategy Framework Directive (MSFD) linked to descriptor 10, criterion 1. The seafloor dataset describes the litter gathered between 2012 and 2014 during beam trawl (BTS) fishery surveys in the Belgian part of the North Sea (BPNS). It provides the date, location and haul information, type of litter found and information in the size of the items. Additionally the ship name and cruise references are reported. The data is recorded following ICES guidelines allowing future inclusion in the ICES online database DATRAS (International Council for the Exploration of the Sea, Database of Trawl Survery).The sludge dataset describes the litter found between 2013 and 2016 on dredge disposal sites located in the coastal area of the Belgian part of the North Sea (BPNS). It provides the date, location, amount and type of litter as well as methodological information (e.g. mesh size). Additionally, the ship name and cruise references are reported.The beach litter dataset contains information on beach litter for the period 2012-2016 washed ashore on two reference beaches (Oostende Halve Maan & Oostende Raversijde). 40 surveys (100m transects) have been executed until January 2017. Monitoring & data recording has been done according to the OSPAR Guideline for Monitoring Marine Litter on the beaches in the OSPAR maritime area (Convention for the Protection of the Marine Environment of the North-East Atlantic, 2010). Besides the number of litter items, the category is also noted. The dataset is characterized by a high variation in the number of items. The data are reported to OSPAR beach litter database.Conclusions: see https://odnature.naturalsciences.be/msfd/nl/assessments/2018/page-d10

These data provide a snap shot of beach litter surveys submitted by Citizen Scientist ‘Monitoring Groups’ up to April, 2019. As defined by the United Nations Environment Programme (UNEP, 2009), marine litter is any persistent, manufactured or processed solid material discarded, disposed of, abandoned or lost in the marine and coastal environment. Marine litter washed onto beaches is one of the most obvious signs of marine pollution, and can have either land or sea-based origins. Land-based sources of marine litter include input from rivers, sewage and storm water outflows, tourism and recreation, illegal dumping, and waste disposal sites. Sea-based sources include commercial shipping, fisheries and aquaculture activities, recreational boating and offshore installations.

UNEP, 2009. Marine Litter: A Global Challenge. Nairobi: UNEP. 232 pp.

More information on this dataset and how it relates to our environmental reporting indicators and topics can be found in the attached data quality pdf.

Compilation of Action Plans from different entities for the GPML Digital PlatformSource URL : https://digital.gpmarinelitter.org/browse?topic=policyTime Period : Data Collection from 2019, and is currently ongoingGeo-Coverage : GlobalSub-Layers:Marine Litter and Plastic Pollution Policies(MLPP_IR_POL_GPML_FS)Marine Litter and Plastic Pollution Country Summary(MLPP_RES_CS_GPML_FS)

This dataset contains 1 .xlsx file (data_itamaraca_Marine_Litter_2022.xlsx), divided into 5 sheets. The General contains information about ID, Date, Beach, latitude, and longitude of transect begin (lat_begin, lon_begin), latitude and longitude of transact end (lat_end, lon_end), number of transects (transect), presence of oil, seaweed_wrack, natural_vegetation in the sampled area and the Urbanization in each beach.UNEP_cat is a supportive spreadsheet with The United Nations Environment Programme (UNEP) code as descriptions of marine litter types. It included some region-specific items.litter_sand and litter_underwater provide information about the marine litter in the sand and underwater respectively. The data is presented in a number of items. Information about the sampled area is included, allowing the calculation of items per square meter, or in the case of underwater litter the sampling effort per time. brand_audit provides detailed information about the brand, size, color, and extra description of all items collected underwater. Marine litter was collected in Itamaracá island, Pernambuco, Brazil. Three beaches (Forte, Jaguaribe, and Sossego) were sampled in March, June, September, and December. In December extra underwater sampling was done.

This dataset contains information for Pacific island countries and territories to take a major step forward to protect our Pacific Ocean from marine litter.

Technical resources range from pilot projects, policy recommendations, assessments, calculation models and tools, operational and technical guidelines, toolkits for decision-makers, best practices, ma...

Compilation of Initiatives from different entities for the GPML Digital Platform.

This dataset includes marine litter data collected from 20 beaches around the island of Cyprus, in the Mediterranean. The beaches were monitored over four monitoring sessions, from January to September 2021, to assess marine litter amounts, categories and spatiotemporal distribution.

The objective of the MARLISAT project was to further develop Marine Plastic Monitoring through satellite technologies, i.e., using satellites to detect Marine litter, track it and forecast its pathways. The project was led by CLS, with Pixalytics developing the remote sensing-based detection approach. It was funded through the European Space Agency, contract number 4000131481/20/NL/GLC. The associated paper is available at https://doi.org/10.3390/rs14194772

This statistic shows the share of marine litter/plastic collected on beaches in Iceland in 2017, by source. The largest share, reaching 36 percent, were from consumer waste. The second largest share came from fisheries, and composed 35 percent of the waste.

Marine Litter Solutions Market Outlook

The global marine litter solutions market size was valued at approximately USD 2.5 billion in 2023 and is expected to reach USD 5.4 billion by 2032, growing at a compound annual growth rate (CAGR) of 8.5% during the forecast period. This market is driven by increasing awareness about the environmental hazards posed by marine litter, stringent government regulations, and the escalating efforts by non-governmental organizations (NGOs) and the private sector to mitigate ocean pollution.

One of the primary growth factors for the marine litter solutions market is the rising global awareness of the adverse impacts of marine litter on ecosystems and human health. Governments and international bodies have been implementing stricter regulations to curb marine pollution, thereby driving the demand for effective marine litter solutions. The proliferation of environmental awareness campaigns has sensitized the public and businesses to the urgent need for marine litter management, spurring investments in innovative cleanup and prevention technologies.

Technological advancements in marine litter solutions also play a pivotal role in market growth. Innovations in cleanup equipment, monitoring tools, and recycling technologies have made it more feasible to address marine litter efficiently and cost-effectively. For instance, the development of autonomous drones and underwater robots has revolutionized the ways to detect and remove litter from the oceans, rivers, and coastal areas. Additionally, the advent of advanced biodegradable materials is reducing the dependency on traditional plastics, significantly mitigating the marine litter problem at its source.

The increasing participation and funding from the private sector and non-governmental organizations have further accelerated the growth of the marine litter solutions market. Many corporations are now integrating sustainability into their business models, investing in cleanup and recycling initiatives as part of their corporate social responsibility (CSR) efforts. NGOs, on the other hand, are playing a crucial role in driving grassroots movements, mobilizing volunteers, and advocating for policy changes, thereby complementing governmental efforts in addressing marine litter.

The market for Recycled Ocean Plastic Sales is gaining momentum as companies and consumers alike become more environmentally conscious. This trend is driven by the increasing demand for sustainable products and the growing awareness of the impact of plastic waste on marine ecosystems. Businesses are recognizing the value of incorporating recycled ocean plastics into their product lines, not only as a means of reducing their environmental footprint but also as a way to appeal to eco-conscious consumers. The use of recycled ocean plastic is being embraced across various industries, from fashion and footwear to packaging and automotive, highlighting its versatility and potential to drive significant change in reducing marine litter.

Regionally, the Asia Pacific is expected to witness the highest growth rate in the marine litter solutions market, driven by rapid industrialization, urbanization, and the consequent increase in marine pollution. Countries in this region are ramping up their efforts to combat marine litter through stringent regulations and large-scale cleanup initiatives. North America and Europe also represent significant market shares, owing to their advanced waste management infrastructure and strong regulatory frameworks. Latin America, the Middle East, and Africa are gradually catching up, with increasing investments in marine litter solutions and growing international collaborations.

Product Type Analysis

The marine litter solutions market is segmented by product type into cleanup equipment, biodegradable products, recycling technologies, and monitoring and assessment tools. Cleanup equipment, including skimmers, litter traps, and autonomous drones, constitutes a significant segment. The rising adoption of innovative and efficient cleanup technologies is driven by the increasing need for rapid and large-scale removal of marine litter. Autonomous drones and underwater robots, for example, have become indispensable tools in detecting and collecting litter from hard-to-reach areas, significantly enhancing cleanup operations.

Biodegradable products are gaining traction as a critical segment in the marine litter solutions market. With growing concerns over th

The size and share of the market is categorized based on Type (Plastics, Chemicals) and Application (Nonprofit, Non-public) and geographical regions (North America, Europe, Asia-Pacific, South America, and Middle-East and Africa).

Marine litter at the seafloor comprises different materials. Plastic is the most frequent material of marine litter found at the seafloor of the Baltic Sea (55,6%). "Abandoned, lost, discarded or otherwise lost fishing gear" (ALDFG) is a subgroup of plastic litter with special importance for environmental assessment because it has a defined source and may pose a health risk to animals. With the data provided, marine litter at the seafloor of the Baltic Sea was quantified and characterized with special regard to fishery as source. 72 litter items (LI) were collected within fishery catches by bottom trawling during three cruises in 2020 and 2021. The data were used to quantify litter at the seafloor of the Baltic Sea (9.2 LI/km²) including 2.2 LI/km² ALDFG and 0.4 LI/km² fishery nets. We conclude that fishery is an important source of litter and ALDFG represent a considerable share of marine litter with 22.2%.