It is difficult to assess the characteristics of marine debris, especially on hard-to-reach places such as uninhabited islands, rocky coasts, and seashore cliffs. In this study, to overcome the difficulties, we developed a method for marine debris assessment using a segmentation model and images obtained by UAVs. The method was tested and verified on an uninhabited island in Korea with a rocky coast and a seashore cliff. Most of the debris was stacked on beaches with low slopes and/or concave shapes. The number of debris items on the whole coast estimated by the mapping was 1295, which was considered to be the actual number of coastal debris items. However, the number of coastal debris items estimated by conventional monitoring method-based statistical estimation was 6741 (±1960.0), which was severely overestimated compared with the mapping method. The segmentation model shows a relatively high F1-score of ~0.74 when estimating a covered area of ~177.4 m². The developed method could provide reliable estimates of the class of debris density and the covered area, which is crucial information for coastal pollution assessment and management on hard-to-reach places in Korea.

Fishing activities have been recognized as one of the primary contributors to marine environmental pollution. Studies have been conducted on the impact of fishing activities on the accumulation of marine debris, but most of these studies have been conducted at specific points in time. This study collected marine debris data over four years in the coastal area of Korea. Data on the magnitude of nearshore fishing activities during the same period were collected and analyzed. Regression models were constructed to explore the impact of nearshore fishing activities on coastal waste accumulation over time. This research aimed to understand the influence of nearshore fishing activities on the accumulation of ocean-sourced coastal waste, leading to the development of a time series regression model. The results indicated that time series models have substantially more explanatory power compared to conventional models, emphasizing the importance of temporal considerations in quantifying the relationship between fishing activities and coastal litter over time.

The majority of marine debris is found in shallow waters; however, submerged debris accumulated at the sea bottom is affected by this kind of pollution. To mitigate the harmful effect of marine debris, we have to recognize its characteristics. However, it is hard to estimate the quantity of submerged marine debris because the monitoring of submerged marine debris requires greater cost and time compared to the monitoring of beach or coastal debris. In this study, we used the data for submerged marine debris surveyed in the sea near the Korean Peninsula from 2017 to 2020 and the data of fishing vessels passing through the areas from 2018 to 2020. In addition, the correlation of major factors affecting the amount of submerged marine debris was analyzed based on the fishing vessel data and the removal project data for submerged marine debris. Moreover, we estimated the amount of submerged marine debris based on the fishing vessels at the collection sites surveyed two or more times using a stepwise regression model. The average amount of submerged marine debris estimated by the model was 6.0 tonnes more than that by the removal project, for which the error was ~26.5% compared to the amount collected by the removal project. The estimation method for submerged marine debris developed in this study can provide crucial information for an effective collection project by suggesting areas that require a collection project for submerged marine debris based on the information of fishing vessels.