Development of Marine Debris Monitoring Methods Using Satellite and Drone Images
![]() |
Kim, Heung-Min
(Research Institute, IREMTECH Co. Ltd.)
Bak, Suho (Research Institute, IREMTECH Co. Ltd.) Han, Jeong-ik (Research Institute, IREMTECH Co. Ltd.) Ye, Geon Hui (Research Institute, IREMTECH Co. Ltd.) Jang, Seon Woong (IREMTECH Co. Ltd.) |
1 | Jang, S.W., S.K. Lee, S.Y. Oh, D.H. Kim, and H.J. Yoon, 2011. The Application of Unmanned Aerial Photography for Effective Monitoring of Marine Debris, Journal of the Korean Society of Marine Environment & Safety, 17(4): 307-314. https://doi.org/10.7837/kosomes.2011.17.4.307 DOI |
2 | KOEM (Korea Marine Environment Management Corporation), 2020. 2020 National Coastal Litter Control and Monitoring Investigation Service, Korea, https://www.koem.or.kr/site/koem/ex/board/View.do?cbIdx=370&bcIdx=30182, Accessed on Nov. 16, 2022. |
3 | Lee, Y.B., S. Park, C.R. Ryu, H.T. Kim, and H.S. Yoon, 2007. Characteristics of Marine Debris collected from the Coastline of Sandbar in the Nakdong River Estuary, Journal of the Korean Society for Marine Environmental Engineering, 10(3): 148-154. |
4 | Lee, Y.S., W.K. Baek, and H.S. Lee, 2019. Forest Vertical Structure Classification in Gongju City, Korea from Optic and RADAR Satellite Images Using Artificial Neural Network, Korean Journal of Remote Sensing, 35(3): 447-455. https://doi.org/10.7780/kjrs.2019.35.3.8 DOI |
5 | MOF (Ministry of Oceans and Fisheris), 2021. Last year, 138,000 tons of marine debris were collected, about 45% more than in 2018, Korea, https://www.mof.go.kr/statPortal/bbs/report/view.do?ntt_id=973, Accessed on Nov. 16, 2022. |
6 | Son, M.B., J.H. Chung, Y.G. Lee, and S.J. Kim, 2021. A Comparative Analysis of Vegetation and Agricultural Monitoring of Terra MODIS and Sentinel-2 NDVIs, Journal of the Korean Society of Agricultural Engineers, 63(6): 101-115. https://doi.org/10.5389/KSAE.2021.63.6.101 DOI |
7 | Papakonstantinou, A., M. Batsaris, S. Spondylidis, and K. Topouzelis, 2021. A citizen science unmanned aerial system data acquisition protocol and deep learning techniques for the automatic detection and mapping of marine litter concentrations in the coastal zone, Drones, 5(1): 6. https://doi.org/10.3390/drones5010006 DOI |
8 | Ronneberger, O., P. Fischer, and T. Brox, 2015. U-net: Convolutional networks for biomedical image segmentation, Proc. of 2015 International Conference on Medical Image Computing and Computer-assisted Intervention, Munich, Germany, Oct. 5-9, pp. 234-241. https://doi.org/10.48550/arXiv.1505.04597 DOI |
9 | Sasaki, K., T. Sekine, L.J. Burtz, and W.J. Emery, 2022. Coastal Marine Debris Detection and Density Mapping With Very High Resolution Satellite Imagery, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 15: 6391-6401. https://doi.org/10.1109/JSTARS.2022.3193993 DOI |
10 | Stoian, A., V. Poulain, J. Inglada, V. Poughon, and D. Derksen, 2019. Land cover maps production with high resolution satellite image time series and convolutional neural networks: Adaptations and limits for operational systems, Remote Sensing, 11(17): 1986. https://doi.org/10.3390/rs11171986 DOI |
11 | Park, S. and H.S. Yoon, 2007. Distribution of Marine Debris collected from the Sandbar Coastline of Nakdong River Estuary after the Typhoons' Passage, Journal of Korea Society of Marine Environment & Safety, 13(4): 1-7. |
12 | Kim, H.M., H.J. Yoon, S.W. Jang, and Y.H. Chung, 2017. Detection Method of River Floating Debris Using Unmanned Aerial Vehicle and Multispectral Sensors, Korean Journal of the Remote Sensing, 33(5): 537-546. https://doi.org/10.7780/kjrs.2017.33.5.1.7 DOI |
13 | Biermann, L., D. Clewley, V. Martinez-Vicente, and K. Topouzelis, 2020. Finding plastic patches in coastal waters using optical satellite data, Scientific Reports, 10(1): 1-10. https://doi.org/10.1038/s41598-020-62298-z DOI |
14 | Fallati, L., A. Polidori, C. Salvatore, L. Saponari, A. Savini, and P. Galli, 2019. Anthropogenic Marine Debris assessment with Unmanned Aerial Vehicle imagery and deep learning: A case study along the beaches of the Republic of Maldives, Science of The Total Environment, 693: 133581. https://doi.org/10.1016/j.scitotenv.2019.133581 DOI |
15 | Goncalves, G. and U. Andriolo, 2022. Operational use of multispectral images for macro-litter mapping and categorization by Unmanned Aerial Vehicle, Marine Pollution Bulletin, 176: 113431. https://doi.org/10.1016/j.marpolbul.2022.113431 DOI |
16 | Jang, S.W., D.H. Kim, Y.H. Chung, and H.J. Yoon, 2014. Behavior Characteristics of Floating Debris Spilled from the Nakdong River, Korean Journal of Remote Sensing, 30(1): 127-136. https://doi.org/10.7780/kjrs.2014.30.1.10 DOI |
17 | Lin, T.Y., P. Goyal, R. Girshick, K. He, and P. Dollar, 2017. Focal loss for dense object detection, Proc. of 2017 IEEE International Conference on Computer Vision, Venice, Italy, Oct. 22-29, pp. 2980-2988. https://doi.org/10.48550/arXiv.1708.02002 DOI |
18 | Goncalves, G., U. Andriolo, L. Pinto, and D. Duarte, 2020. Mapping marine litter with Unmanned Aerial Systems: A showcase comparison among manual image screening and machine learning techniques. Marine Pollution Bulletin, 155: 111158. https://doi.org/10.1016/j.marpolbul.2020.111158 DOI |
19 | Kang, J., G. Kim, Y. Jeong, S. Kim, Y. Youn, S. Cho, and Y. Lee, 2021. U-Net Cloud Detection for the SPARCS Cloud Dataset from Landsat 8 Images, Korean Journal of Remote Sensing, 37(5): 1149-1161. https://doi.org/10.7780/kjrs.2021.37.5.1.25 DOI |
20 | Chen, L.C., G. Papandreou, F. Schroff, and H. Adam, 2017. Rethinking atrous convolution for semantic image segmentation, arXiv preprint arXiv:1706.05587. https://doi.org/10.48550/arXiv.1706.05587 DOI |
21 | Seo, D.C. and J.P. Kim, 2019. Comparison and Analysis Monitoring Methods for Marine Debris on Beach, Journal of Korea Society of Waste Management, 36(8): 802-810. https://doi.org/10.9786/kswm.2019.36.8.802 DOI |
22 | Zhang, P., Y. Ke, Z. Zhang, M. Wang, P. Li, and S. Zhang, 2018. Urban land use and land cover classification using novel deep learning models based on high spatial resolution satellite imagery, Sensors, 18(11): 3717. https://doi.org/10.3390/s18113717 DOI |
23 | Lee, J.H., Y.W. Lee, M.H. Choe, S.C. O., H.U. Kim, J.G. Gang, and G.H. Park, 2021. Coastal debris detection experiment using ENVI's deep learning image recognition module, Water for Future, 54(12): 22-28. |
![]() |