Abstract
The dike surrounding the coast of the Vietnamese Mekong Delta (VMD) helps prevent saltwater intrusion and coastal erosion. In order to preserve these dikes, an area of protective forest is planted outside them, helping to maintain and strengthen them. Therefore, monitoring the change in the area of planted forest outside the dike will help to assess the stability of and possible threats to the coastal area and ecosystem. In this paper, using Sentinel remote sensing images, we propose a new approach; applying the Random Forest technique to assess the changes in the planted forest outside the dike. The experimental results obtained on a typical coastal area of the Vietnamese Mekong Delta will help to clearly identify the threats and the evolution of the coastline through the changes in forest area outside the dike.
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References
Besset M, Anthony EJ, Brunier G, Dussouillez P (2016) Shore-line change of the Mekong River delta along the Southern part of the South China Sea coast using satellite image analysis (1973 – 2014). Géomorphologie Relief Proc Environ 22:137–146. https://doi.org/10.4000/geomorphologie.11336
Besset M, Gratiot N, Anthony EJ, Bouchette F, Goichot M, Marchesiello P (2019) Mangroves and shoreline erosion in the Mekong River delta, Viet Nam. Estuar Coast Shelf Sci 226:106263. https://doi.org/10.1016/j.ecss.2019.106263
Breiman L (2001) Random forests – machine learning, vol 45. Kluwer Academic Publishers, pp 5–32
Breiman L, Friedman J, Olshen R, Stone C (1984) Classification and regression trees. Wadsworth, Belmont
Criminisi A, Shotton J, Konukoglu E (2016) Decision forests for classification, regression, density estimation, manifold learning and semi-supervised learning Microsoft Research technical report TR-2011-114. https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/decisionForests_MSR_TR_2011_114.pdf
Groenewold S, Albers T, Sorgenfrei R (2019) Protect the coastal area of the Mekong Delta. Hanoi
Huynh HX, Loi TTT, Huynh TP, Tran VS, Nguyen TNT, Niculescu S (2019) Predicting of flooding in the Mekong Delta using satellite images. In: Vinh P, Rakib A (eds) Context-aware systems and applications, and nature of computation and communication. Lecture notes of Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 298. Springer, pp 143–156. https://doi.org/10.1007/978-3-030-34365-1_11
Huynh HX, Nguyen KM, Nguyen KD, Luong HH, Tran NC, Nguyen LTT, Tran TM, Pham PTT, Niculescu S (2020) Discovered changes in rice occupation with satellite images based on Random Forest approach. Proceedings of the 4th ACM International Conference on Machine Learning and Soft Computing (ICMLSC 2020). 86–97
Lappe R, Ullmann T, Bachofer F (2022) State of the Vietnamese coast – assessing three decades (1986 to 2021) of coastline dynamics using the Landsat archive. Remote Sens 14:2476. https://doi.org/10.3390/rs14102476
Lee J, Jurkevich L, Dewaele P, Wambacq P, Oosterlinck A (1994) Speckle filtering of synthetic aperture radar images: a review. Remote Sens Rev 8:313–340. https://doi.org/10.1080/02757259409532206
Marchesiello P, Nguyen NM, Gratiot N, Loisel H, Edward J. Anthony, Dinh CS, Nguyen T, Almar R, Kestenare E (2019) Erosion of the coastal Mekong delta: assessing natural against man induced processes. Cont Shelf Res 181: 72–89 https://doi.org/10.1016/j.csr.2019.05.004
Nam VN (2010) Inventory on the biodiversity of mangrove flora in order to find out which species thrive in particular environments and propose solutions for sustainable use and management of these coastal resources in Bac Lieu province. Project on Sustainable management of coastal forest ecosystems in Bac Lieu province. GTZ – Germany
Niculescu S, Lam NC (2019) Geographic object-based image analysis of changes in land cover in the coastal zones of the Red River Delta (Vietnam). J Environ Prot 10(3):413–430. https://doi.org/10.4236/jep.2019.103024
Pettorelli N (2013) The normalized difference vegetation index:1–208. https://doi.org/10.1093/acprof:osobl/9780199693160.001.0001
Ragia L, Pavlos K (2019) Monitoring the changes of the coastal areas using remote sensing data and geographic information systems. Proceeding of the Seventh International Conference on Remote Sensing & Geoinformation of the Environment (RSCy 2019). 111740X. https://doi.org/10.1117/12.2533659
Vietnamese Official Gazette (2021) Decision No. 524/QD-TTg approving the project title “Planting a billion trees from 2021 to 2025” dated on April 01st 2021 by Vietnamese Prime Minister. Vietnamese Official Gazette No. 543+544
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Lam, N.C., Huynh, H.X., Niculescu, S., Do Nguyen, Q., Nguyen, N.C.V. (2023). A Random Forest Approach for Evaluating Forest Cover Changes Outside Dikes with Sentinel Images. In: Niculescu, S. (eds) European Spatial Data for Coastal and Marine Remote Sensing. Springer, Cham. https://doi.org/10.1007/978-3-031-16213-8_8
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DOI: https://doi.org/10.1007/978-3-031-16213-8_8
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