|
|
1.INTRODUCTIONMarine litter refers to waste originating from human activities that has been discharged into coastal or marine environments. Such litter may result from activities on either land or at sea. Currently, 60 to 80% of such marine litter consists of plastic, reaching 95% in some areas and has become a serious environmental hazard. Marine litter can be classified as floating and sinking litter based on its weight and shape. It has been estimated that marine litter is split into 15% floating on the sea surface, another 15% remaining in the water column and 70% subsides on the sea floor. Plastics are one of the most pervasive pollutants in the world’s oceans, and they pose a significant threat to marine ecosystems, wildlife, and human health. Plastic waste can harm marine life by entangling animals or being ingested, leading to injury or death. It can also disrupt the food chain by accumulating in the bodies of marine organisms and eventually entering the human food chain. Additionally, plastic waste can degrade marine habitats, altering the balance of ecosystems and leading to the loss of biodiversity. Also, the economic impact, marine plastic pollution can have significant economic impacts, including losses in fishing and tourism revenue, cleanup costs, and damage to infrastructure. Furthermore, for the human health impact, the chemicals found in plastics can leach into the marine environment, potentially impacting human health through the consumption of contaminated seafood or water. For the detection of plastic litter, we used several well-established indices for water feature extraction. The Normalized Difference Water Index (NDWI), Water Ratio Index (WRI), Normalized Difference Vegetation Index (NDVI), Automated Water Extraction Index (AWEI), Modified Normalization Deference Water Index (MNDWI) and Normalization Deference Moisture Index (NDMI), the Simple Ratio (SR). Also, the Plastic Index (PI) and Reversed Normalized Difference Vegetation Index (RNDVI). 2.METHODOLOGY2.1Study AreaAn area of interest (AoI) Sentinel-2 image was processed throughout this research. AoI-1 is located South of the Limassol Old Port in Cyprus. Sentinel-2 data from the Copernicus Open Access Hub is available via the web interface. The satellite images used are: 2.2MethodsUsing the Copernicus Open Access Hub service, it is now feasible to access satellite data in fully automated and near realtime mode and deliver plastic litter information through a web portal interface, using freely available Sentinel-2 imagery data. The Sentinel Application Platform (SNAP) was used to conduct the study. For the detection of plastic litter, were used several well-established indices for water feature extraction. The Normalized Difference Water Index (NDWI) [1], Water Ratio Index (WRI) [2], Normalized Difference Vegetation Index (NDVI) [3], Automated Water Extraction Index (AWEI) [4], Modified Normalization Deference Water Index (MNDWI) [5] and Normalization Deference Moisture Index (NDMI) [6], the Simple Ratio (SR) [7]. Also, the Plastic Index (PI) [8] and Reversed Normalized Difference Vegetation Index (RNDVI) [9]. Table 1.Indices for detection of plastic litter for water feature extraction.
3.RESULTSThe results when applying the above indicators are satisfactory and can separate the plastic waste in the sea. All of the above indicators detected plastic waste, except AWEI. It was found that indices with B04 performed better since the spatial resolution was 10 m. The sensitivity analysis performed on the indices showed that the best indices for detecting plastic waste were PI (Plastic Index) and RNDVI (Normal Difference Vegetation Index). 4.CONCLUSIONSThe results are significantly enhanced and show that the use of different indicators provide a thorough detection analysis so that they can be used for maritime safety. Plastics are one of the most pervasive pollutants in the world’s oceans and pose a significant threat to marine ecosystems, wildlife and human health, so through oversight, inspection and preventative procedures, threats to marine safety will be minimized. 5.FUTURE WORKSImproving the resolution of satellite images could allow smaller plastic debris to be detected. Also, such observations provide a “snapshot” of local conditions at a given time and are difficult to use to infer the origin of waste. Combining methods and data will enable more accurate and timely information on the location and movement of plastic debris in oceans and waterways. REFERENCESThemistocleous, K. et al.,
“Investigating detection of floating plastic litter from space using sentinel-2 imagery,”
MDPI. Multidisciplinary Digital Publishing,
(2020) https://www.mdpi.com/2072-4292/12/16/2648 (Accessed: March 2023). Google Scholar
Papakonstantinou, A.; Moustakas, A.; Kolokoussis, P.; Papageorgiou, D.; de Vries, R.; Topouzelis, K.,
“Airborne Spectral Reflectance Dataset of Submerged Plastic Targets in a Coastal Environment,”
Data, 2023
(8), 19
(2023). https://doi.org/10.3390/data8010019 Google Scholar
Papageorgiou, D.; Topouzelis, K.; Suaria, G.; Aliani, S.; Corradi, P.,
“Sentinel-2 Detection of Floating Marine Litter Targets with Partial Spectral Unmixing and Spectral Comparison with Other Floating Materials (Plastic Litter Project 2021),”
Remote Sens., 2022
(14), 5997
(2022). https://doi.org/10.3390/rs14235997 Google Scholar
Kremezi, M., Kristollari, V., Karathanassi, V., Topouzelis, K., Kolokoussis, P., Taggio, N., Aiello, A., Ceriola, G., Barbone, E., & Corradi, P.,
“Increasing the Sentinel-2 potential for marine plastic litter monitoring through image fusion techniques,”
Marine Pollution Bulletin, 182 113974
(2022). https://doi.org/10.1016/j.marpolbul.2022.113974 Google Scholar
K. Topouzelis and D. Papageorgiou,
“PLASTIC LITTER PROJECTS: Dedicated experiments for the detection of floating marine plastic litter, ISPRS-SC SPECTRUM, Vol15, No2, Remote Sensing of Coastal,”
Environments,
(2021) http://sc.isprs.org/sc-newsletter.html Google Scholar
Kremezi, M., Kristollari, V., Karathanassi, V., Topouzelis, K., Kolokoussis, P., Taggio, N., Aiello, A., Ceriola, G., Barbone, E., Corradi, P.,
“Pansharpening PRISMA Data for Marine Plastic Litter Detection Using Plastic Indexes,”
IEEE Access, 9 61955
–61971
(2021). https://doi.org/10.1109/ACCESS.2021.3073903 Google Scholar
|
