Науковий вісник НГУ

Establishing a plastic waste map using remote sensing data in the coastal area of Thanh Hoa province (Vietnam)

• 
• 

User Rating:  / 0

PoorBest 

Details

Category: Content №5 2024

Last Updated on 29 October 2024

Published on 30 November -0001

Hits: 86

Authors:

Thao Phuong Thi Do, orcid.org/0009-0009-0205-8656, Faculty of Geomatics and Land Administration, Hanoi University of Mining and Geology, Hanoi, the Socialist Republic of Vietnam

Hanh Hong Tran*, orcid.org/0000-0002-8771-8351, Faculty of Geomatics and Land Administration, Hanoi University of Mining and Geology, Hanoi, the Socialist Republic of Vietnam, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Anh Ngọc Do, orcid.org/0009-0003-0631-0739, National Remote Sensing Department, Hanoi, the Socialist Republic of Vietnam

Ngan Khanh Tran Ngo, orcid.org/0009-0006-0399-7282, Marie Curie High School, Hanoi, the Socialist Republic of Vietnam

* Corresponding author e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

повний текст / full article

Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2024, (5): 116 - 122

https://doi.org/10.33271/nvngu/2024-5/116

Abstract:

Plastic pollution, particularly in oceans, is a growing environmental threat. Monitoring this pollution is challenging due to the shortage of data and tools. Remote sensing offers a promising solution by using various types of satellite and aerial images to detect and track plastic waste movement.

Purpose. The study aims to establish a plastic waste map using remote sensing technology, focusing on the case study of the coastal area of Thanh Hoa province, Vietnam.

Methodology. The study involves several steps, including the collection of plastic waste data (samples in the case study and indices from remote sensing images) as well as topographic and base map collection, statistics of plastic samples, grid design, calculation, interpolation, accuracy assessment, and mapping. Field surveys involved taking pictures of plastic debris along designated routes and a grid system was used to classify and calculate waste samples. Satellite images, especially Sentinel-2 MSI optical satellite imagery, are utilized to identify water areas of high plastic concentration.

Findings. A map of plastic wastes in coastal areas of Thanh Hoa was created, with indices like NDWI (Normalized Difference Water Index) and FDI (Floating Debris Index) helping identify potential plastic waste signals. The resulting map reveals high concentrations of plastic waste in sea areas near the major river mouths of the Ma River basin and tourist areas, which aligns with areas of high human activity.

Originality. This is the first study of plastic waste in the coastal area using remote sensing data in Thanh Hoa province, Vietnam.

Practical value. This study can contribute to the effective management of marine plastic waste in Thanh Hoa while opening up opportunities for applying the method to create marine plastic waste maps throughout Vietnam and foster long-term monitoring and management.

Keywords: plastic waste, remote sensing, coastal area, Thanh Hoa, Vietnam

References.

1. Chamas, A., Moon, H., Zheng, J., Qiu, Y., Tabassum, T., Jang, J. H., & Suh, S. (2020). Degradation rates of plastics in the environment. ACS Sustainable Chemistry & Engineering, 8(9), 3494-3511. https://doi.org/10.1021/acssuschemeng.9b06635.

2. UNEP, UN Environment 2018. Annual Report (2018). Retrieved from https://www.unep.org/resources/un-environment-2018-annual-report.

3. Critchell, K., Bauer-Civiello, A., Benham, C., Berry, K., Eagle, L., Hamann, M., & Ridgway, T. (2019). Plastic pollution in the coastal environment: current challenges and future solutions. Coasts and estuaries, 595-609. https://doi.org/10.1016/B978-0-12-814003-1.00034-4.

4. Fu, W., Ma, J., Chen, P., & Chen, F. (2020). Remote sensing satellites for digital earth. Manual of digital earth, 55-123. https://doi.org/10.1007/978-981-32-9915-3_3.

5. Topouzelis, K., Papakonstantinou, A., & Garaba, S. P. (2019). Detection of floating plastics from satellite and unmanned aerial systems. International Journal of Applied Earth Observation and Geoinformation, 79, 175-183. https://doi.org/10.1016/j.jag.2019.03.011.

6. Goddijn-Murphy, L., & Dufaur, J. (2018). Proof of concept for a model of light reflectance of plastics floating on natural waters. Marine pollution bulletin, 135, 1145-1157. https://doi.org/10.1016/j.marpolbul.2018.08.044.

7. Moy, K., Neilson, B., Chung, A., Meadows, A., Castrence, M., Ambagis, S., & Davidson, K. (2018). Mapping coastal marine debris using aerial imagery and spatial analysis. Marine pollution bulletin, 132, 52-59.

8. Martin, C., Parkes, S., Zhang, Q., Zhang, X., McCabe, M. F., & Duarte, C. M. (2018). Use of unmanned aerial vehicles for efficient beach litter monitoring. Marine pollution bulletin, 131, 662-673. https://doi.org/10.1016/j.marpolbul.2018.04.045.

9. Davaasuren, N., Marino, A., Boardman, C., Alparone, M., Nunziata, F., Ackermann, N., & Hajnsek, I. (2018). Detecting microplastics pollution in world oceans using SAR remote sensing. IEEE International Geoscience and Remote Sensing Symposium, 938-941. https://doi.org/10.1109/IGARSS.2018.8517281.

10. Duong, T. P. A. (2024). Research on theoretical foundations and international experience in controlling plastic waste in the sea. Ministry of Natural Resources and Environment. Retrieved from https://isponre.gov.vn/en/.

11. Do, T. N., Nguyen, T. D. M., Pham, V. M., Pham, V. D., Bui, Q. T., Nghiem, V. T., & Pham, M. H. (2021). Study model for detection on coastal plastic waste using unmanned aerial vehicle image and deep convolutional neural network. Journal of Geodesy and Cartography, 49, 21-29.

12. Le, T. H. P. (2022) Analysis of plastic waste pollution in Vietnam and proposing recommendations. Journal of Environment, 9, 28-31.

13. Le, H. T., Van, T. N., Tran, X. B., Van, P. L., & Sach, T. N. (2022). A method for detecting plastic waste floating using Sentinel 2 high spatial resolution image: A case study in the coastal area of Vietnam. Remote methods in Earth research, 394-407. https://doi.org/10.35595/2414-9179-2022-1-28-394-407.

14. Amalo, L. F., Ma’rufah, U., & Permatasari, P. A. (2018). Monitoring 2015 drought in West Java using normalized difference water index (NDWI). IOP Conference Series: Earth and Environmental Science, 149(1), 012007. https://doi.org/10.1088/1755-1315/149/1/012007.

15. Ezzine, H., Bouziane, A., Ouazar, D., & Hasnaoui, M. D. (2017). Downscaling of open coarse precipitation data through spatial and statistical analysis, integrating NDVI, NDWI, elevation, and distance from sea. Advances in Meteorology, 2017(1), 8124962. https://doi.org/10.1155/2017/8124962.

16. Ciappa, A. C. (2021). Marine plastic litter detection offshore Hawai’i by Sentinel-2. Marine Pollution Bulletin, 168, 112457. https://doi.org/10.1155/2017/8124962.

17. Biermann, L., Clewley, D., Martinez-Vicente, V., & Topouzelis, K. (2020). Finding plastic patches in coastal waters using optical satellite data. Scientific reports, 10(1), 5364. https://doi.org/10.1038/s41598-020-62298-z.

18. Themistocleous, K., Papoutsa, C., Michaelides, S., & Hadjimitsis, D. (2020). Investigating detection of floating plastic litter from space using sentinel-2 imagery. Remote Sensing, 12(16), 2648. https://doi.org/10.3390/rs12162648.

• < Prev
• Next >