Thông tin tài nguyên

Predicting coastal erosion susceptibility in Bangladesh under climate scenario via machine learning techniques

pmc-PMC12588506.pdf · Phiên bản 1 · 34 trang

18
Bản gốc
Trang 29 · Đoạn 61Vị trí nguồn

PLOS One | https://doi.org/10.1371/journal.pone.0334347 November 5, 2025 29 / 34 Visualization: Sakib Hosan, Sondipon Dey Pranta. Writing – original draft: Sakib Hosan, Sondipon Dey Pranta, Tahdia Tahmid, Mafrid Haydar, Al Hossain Rafi. Writing – review & editing: Sakib Hosan, Sondipon Dey Pranta, Mafrid Haydar, Al Hossain Rafi. References 1. Burkett V, Davidson M. Coastal Impacts, Adaptation, and Vulnerabilities. Island Press/Center for Resource Economics. 2012. https://doi. org/10.5822/978-1-61091-460-4 2. Islam MR, Khan NA, Reza MM, Rahman MM. Vulnerabilities of River Erosion–Affected Coastal Communities in Bangladesh: a Menu of Alternative Livelihood Options. Glob Soc Welf. 2020;7(4):353–66. https://doi.org/10.1007/s40609-020-00185-1 3. Roy S, Pandit S, Papia M, Rahman MM, Otto Rehder Ocampo JC, Razi MA, et al. Coastal erosion risk assessment in the dynamic estuary: The Meghna estuary case of Bangladesh coast. International Journal of Disaster Risk Reduction. 2021;61:102364. https://doi.org/10.1016/j. ijdrr.2021.102364 4. Safra de Campos R, et al. Where people live and move in deltas. 2020. 5. Mallick A, Mallick B. Staying despite riverbank erosion: evidence of coastal Bangladesh. SN Soc Sci. 2021;1(6). https://doi.org/10.1007/ s43545-021-00104-x 6. Rimi RA, Rafi AH, Sultana J. Factors affecting sustainable resource management in. 2024;(March). 7. Gantulga N, Iimaa T, Batmunkh M, Surenjav U, Tserennadmin E, Turmunkh T, et al. Impacts of natural and anthropogenic factors on soil erosion. Proc Mong Acad Sci. 2023;:3–18. https://doi.org/10.5564/pmas.v63i02.1416

Trang 29 · Đoạn 62Vị trí nguồn

8. Marks D, Bayrak MM, Connell J. Increasing livelihood vulnerabilities to coastal erosion and wastewater intrusion: The political ecology of Thai aquaculture in peri‐urban Bangkok. Geographical Research. 2023;61(2):259–72. https://doi.org/10.1111/1745-5871.12580 9. Nguyen Minh Q, Vu Van H, Nguyen Thi M, Ngo Thi D, Nguyen Thi Thu C, Dang Minh T, et al. Holocene sedimentary facies in the incised valley of Ma River Delta, Vietnam. Vietnam J Earth Sci. 2023. https://doi.org/10.15625/2615-9783/18923 10. Prasad DH, Kumar ND. Coastal Erosion Studies—A Review. IJG. 2014;05(03):341–5. https://doi.org/10.4236/ijg.2014.53033 11. Murshed S, Griffin AL, Islam MA, Wang XH, Paull D. Assessing multi-climate-hazard threat in the coastal region of Bangladesh by combining influ- ential environmental and anthropogenic factors. Progress in Disaster Science. 2022;16:100261. https://doi.org/10.1016/j.pdisas.2022.100261 12. Martínez ML, Intralawan A, Vázquez G, Pérez-Maqueo O, Sutton P, Landgrave R. The coasts of our world: Ecological, economic and social impor- tance. Ecological Economics. 2007;63(2–3):254–72. https://doi.org/10.1016/j.ecolecon.2006.10.022 13. Shampa MTA, Shimu NJ, Chowdhury KMA, Islam MM, Ahmed MK. A comprehensive review on sustainable coastal zone management in Bangla- desh: Present status and the way forward. Heliyon. 2023;9(8):e18190. https://doi.org/10.1016/j.heliyon.2023.e18190 PMID: 37554819 14. van Steenbergen F r a n k, Marandy J o h n. Loose and gain: coastal erosion in Bangladesh. The Water Channel. 2023. https://thewaterchannel.tv/

Trang 29 · Đoạn 63Vị trí nguồn

thewaterblog/loose-and-gain-coastal-erosion-in-bangladesh/ 15. Islam MdM, Rahman MdS, Kabir MdA, Islam MdN, Chowdhury RM. Predictive assessment on landscape and coastal erosion of Bangladesh using geospatial techniques. Remote Sensing Applications: Society and Environment. 2020;17:100277. https://doi.org/10.1016/j.rsase.2019.100277 16. Thanh BN, Van Phong T, Trinh PT, Costache R, Amiri M, Nguyen DD, et al. Prediction of coastal erosion susceptible areas of Quang Nam Prov- ince, Vietnam using machine learning models. Earth Sci Inform. 2023;17(1):401–19. https://doi.org/10.1007/s12145-023-01182-6 17. V.M. P, Aldehim G, Negm N, Subathradevi S. Integrating geospatial techniques and machine learning for assessing soil erosion and associated geomorphic risks. Journal of South American Earth Sciences. 2025;156:105463. https://doi.org/10.1016/j.jsames.2025.105463 18. Çelik Oİ, Gazioğlu C. Coast type based accuracy assessment for coastline extraction from satellite image with machine learning classifiers. The Egyptian Journal of Remote Sensing and Space Science. 2022;25(1):289–99. https://doi.org/10.1016/j.ejrs.2022.01.010 19. Sarkar SK, Ansar SB, Ekram KMM, Khan MH, Talukdar S, Naikoo MW, et al. Developing Robust Flood Susceptibility Model with Small Num- bers of Parameters in Highly Fertile Regions of Northwest Bangladesh for Sustainable Flood and Agriculture Management. Sustainability. 2022;14(7):3982. https://doi.org/10.3390/su14073982 20. Eloudi H, Hssaisoune M, Reddad H, Namous M, Ismaili M, Krimissa S, et al. Robustness of Optimized Decision Tree-Based Machine Learning

Trang 29 · Đoạn 64Vị trí nguồn

Models to Map Gully Erosion Vulnerability. Soil Systems. 2023;7(2):50. https://doi.org/10.3390/soilsystems7020050 21. Ghosh A, Maiti R. Soil erosion susceptibility assessment using logistic regression, decision tree and random forest: study on the Mayurakshi river basin of Eastern India. Environ Earth Sci. 2021;80(8). https://doi.org/10.1007/s12665-021-09631-5 22. Saha S, Roy J, Arabameri A, Blaschke T, Tien Bui D. Machine Learning-Based Gully Erosion Susceptibility Mapping: A Case Study of Eastern India. Sensors (Basel). 2020;20(5):1313. https://doi.org/10.3390/s20051313 PMID: 32121238 23. Gayen A, Pourghasemi HR, Saha S, Keesstra S, Bai S. Gully erosion susceptibility assessment and management of hazard-prone areas in India using different machine learning algorithms. Sci Total Environ. 2019;668:124–38. https://doi.org/10.1016/j.scitotenv.2019.02.436 PMID: 30851678