Abstract
The movement of suspended sediment along the coastal water is an indicator of erosion and deposition of the coastal landforms. The current study deals with the spatio-temporal movement of suspended sediments in the shallow along the southwest coast of Thiruvananthapuram district, Kerala state in India. The customized model here systematically analyses the spectral properties of multiple bands to mapping the suspended sediments at various concentration and spatial distributions. The study on sediment drift and its impacts on the coast through conventional method are difficult; meanwhile, multi-temporal images may provide effective results for studying sediments concentration and their movement along the coastal water. The geoprocessing modelling of sediment dynamics has executed mathematical algorithm on Landsat OLI image to retrieve SSC from coastal water and demarcate movement of sediments along the coast during pre- and post-monsoon. The study reveals that sediment concentration has estimated at higher rate along the offshore area with depth lower than 30 m, and this is gradually decreasing towards the sea at the depth beyond 30 m. It is observed that the suspended sediment drift produces depositional landforms at the low wave-energy zone and erosional landforms at high wave-energy zone. This study proves the effectiveness of geospatial technology to estimate sediment concentration and transportation in the shallow coastal water.
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The authors declare that there is no conflict of interests regarding the publication of this paper. BT and KR designed and proposed the research; BT processed data; PK, KR and BT implemented techniques; PK and BT analysed results; and PK and JSR drafted and edited the article.
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Rani, M., Kaliraj, S., Ahmed, R., Tripathy, B., Tripathy, B.R., Pippal, G.S. (2019). A Sediment Dynamic Modelling of Landsat OLI Image for Suspended Sediment Drift Along the Southwest Coast of India. In: Kumar, P., Rani, M., Chandra Pandey , P., Sajjad, H., Chaudhary, B. (eds) Applications and Challenges of Geospatial Technology. Springer, Cham. https://doi.org/10.1007/978-3-319-99882-4_9
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