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Assessment of coastal variations due to climate change using remote sensing and machine learning techniques: A case study from west coast of India
Resource type
Journal Article
Authors/contributors
- Pradeep, Jibin (Author)
- Shaji, E. (Author)
- S, Subeesh Chandran C (Author)
- Ajas, H (Author)
- Chandra, S.S. Vinod (Author)
- Dev, S.G. Dhanil (Author)
- Babu, D. S. Suresh (Author)
Title
Assessment of coastal variations due to climate change using remote sensing and machine learning techniques: A case study from west coast of India
Abstract
Climate change and other environmental disturbances are causing sea level rise all over the world. Due to sea-level rise and other unprecedented atmospheric phenomena caused by climate change, Indian coasts are vulnerable to coastal erosion. The Kerala coast, at the southern tip of India's west coast, has experienced a sea change in the last decade. To address coastal variations, we investigate coastal erosion, coastal accretion, and shoreline changes (from 2006 to 2020) along this coast between Pozhiyoor and Anchuthengu (58 km). To monitor the status and predict changes along the coast, remote sensing, GIS, field checks, and machine learning tools were used. The data analysis reveals that the shoreline configuration, rate of beach accretion, and erosion have all changed significantly. When the rate of erosion in the 58-km-long coastal stretch was examined, it was discovered that approximately 42 km face acute erosion, 13 km face accretion, and approximately 3 km face neither accretion nor erosion and remain in equilibrium. According to the estimates, approximately 2.62 km2 of land has been eroded away from the shore over a 14-year period, while 0.7 km2 of land has been accreted. At locations where the influence of river discharge or groynes is minimal, the normal rate of accretion in the stretch is around 1–2 m/y. Nonetheless, the rate of accretion increased to 5–8 m/y where groynes or river mouths, or both, have a significant influence on shoreline stability. The normal rate of erosion in the stretch under consideration, however, is around 5 m/y. With a rate of 10.59 m/y, Pozhiyoor had the highest erosion rate. According to the data, the rate of erosion is faster between Pozhikkara and Veli. The increase in shoreline changes is primarily may be due to increased cyclone occurrences in the Arabian Sea, the formation of swell waves, changes in wave energy, and sea level rise due to climate change. The slow rate of sediment discharge by rivers, groyne construction, groyne spacing, groyne length, long shore currents, and preferential northward sediment transport all play a role in the formation and destruction of beaches along India's west coast. Using machine learning techniques, a prediction model for the year 2027 was created using data from the previous 14 years (2006–2020). According to the model, almost the entire stretch will experience severe erosion, with the rate remaining consistently high between Shanghumugham and Anchuthengu. As a result, soft and appropriate engineering solutions are required for coastal stability all along the beach, particularly at these two locations after a feasibilty study.
Publication
Estuarine, Coastal and Shelf Science
Volume
275
Pages
107968-107968
Date
2022-09-01
ISSN
0272-7714
Call Number
openalex: W4284888618
Extra
openalex: W4284888618
Citation
Pradeep, J., Shaji, E., S, S. C. C., Ajas, H., Chandra, S. S. V., Dev, S. G. D., & Babu, D. S. S. (2022). Assessment of coastal variations due to climate change using remote sensing and machine learning techniques: A case study from west coast of India. Estuarine, Coastal and Shelf Science, 275, 107968–107968. https://doi.org/10.1016/j.ecss.2022.107968
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