FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4284888618> ?p ?o ?g. }

• W4284888618 endingPage "107968" @default.
• W4284888618 startingPage "107968" @default.
• W4284888618 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." @default.
• W4284888618 created "2022-07-09" @default.
• W4284888618 creator A5029151593 @default.
• W4284888618 creator A5039622254 @default.
• W4284888618 creator A5045319949 @default.
• W4284888618 creator A5071168977 @default.
• W4284888618 creator A5076048501 @default.
• W4284888618 creator A5078072263 @default.
• W4284888618 creator A5083258456 @default.
• W4284888618 date "2022-09-01" @default.
• W4284888618 modified "2023-09-27" @default.
• W4284888618 title "Assessment of coastal variations due to climate change using remote sensing and machine learning techniques: A case study from west coast of India" @default.
• W4284888618 cites W1969063872 @default.
• W4284888618 cites W1971981396 @default.
• W4284888618 cites W2001113215 @default.
• W4284888618 cites W2006683105 @default.
• W4284888618 cites W2029389793 @default.
• W4284888618 cites W2062121030 @default.
• W4284888618 cites W2068963354 @default.
• W4284888618 cites W2084371936 @default.
• W4284888618 cites W2088187276 @default.
• W4284888618 cites W2110621574 @default.
• W4284888618 cites W2110696608 @default.
• W4284888618 cites W2139680942 @default.
• W4284888618 cites W2171468367 @default.
• W4284888618 cites W2379633397 @default.
• W4284888618 cites W2460558068 @default.
• W4284888618 cites W2591455638 @default.
• W4284888618 cites W2749408758 @default.
• W4284888618 cites W2808797525 @default.
• W4284888618 cites W2887650321 @default.
• W4284888618 cites W2889878597 @default.
• W4284888618 cites W2900032489 @default.
• W4284888618 cites W2911171462 @default.
• W4284888618 cites W2965932637 @default.
• W4284888618 cites W3010403880 @default.
• W4284888618 cites W3135356637 @default.
• W4284888618 cites W3159951467 @default.
• W4284888618 cites W3206963624 @default.
• W4284888618 cites W3211662479 @default.
• W4284888618 doi "https://doi.org/10.1016/j.ecss.2022.107968" @default.
• W4284888618 hasPublicationYear "2022" @default.
• W4284888618 type Work @default.
• W4284888618 citedByCount "3" @default.
• W4284888618 countsByYear W42848886182022 @default.
• W4284888618 countsByYear W42848886182023 @default.
• W4284888618 crossrefType "journal-article" @default.
• W4284888618 hasAuthorship W4284888618A5029151593 @default.
• W4284888618 hasAuthorship W4284888618A5039622254 @default.
• W4284888618 hasAuthorship W4284888618A5045319949 @default.
• W4284888618 hasAuthorship W4284888618A5071168977 @default.
• W4284888618 hasAuthorship W4284888618A5076048501 @default.
• W4284888618 hasAuthorship W4284888618A5078072263 @default.
• W4284888618 hasAuthorship W4284888618A5083258456 @default.
• W4284888618 hasConcept C100970517 @default.
• W4284888618 hasConcept C111368507 @default.
• W4284888618 hasConcept C114793014 @default.
• W4284888618 hasConcept C121332964 @default.
• W4284888618 hasConcept C123157820 @default.
• W4284888618 hasConcept C127313418 @default.
• W4284888618 hasConcept C132651083 @default.
• W4284888618 hasConcept C152382732 @default.
• W4284888618 hasConcept C154261466 @default.
• W4284888618 hasConcept C187320778 @default.
• W4284888618 hasConcept C205649164 @default.
• W4284888618 hasConcept C2776401274 @default.
• W4284888618 hasConcept C2777774347 @default.
• W4284888618 hasConcept C39432304 @default.
• W4284888618 hasConcept C44870925 @default.
• W4284888618 hasConcept C76886044 @default.
• W4284888618 hasConceptScore W4284888618C100970517 @default.
• W4284888618 hasConceptScore W4284888618C111368507 @default.
• W4284888618 hasConceptScore W4284888618C114793014 @default.
• W4284888618 hasConceptScore W4284888618C121332964 @default.
• W4284888618 hasConceptScore W4284888618C123157820 @default.
• W4284888618 hasConceptScore W4284888618C127313418 @default.
• W4284888618 hasConceptScore W4284888618C132651083 @default.
• W4284888618 hasConceptScore W4284888618C152382732 @default.
• W4284888618 hasConceptScore W4284888618C154261466 @default.
• W4284888618 hasConceptScore W4284888618C187320778 @default.
• W4284888618 hasConceptScore W4284888618C205649164 @default.
• W4284888618 hasConceptScore W4284888618C2776401274 @default.
• W4284888618 hasConceptScore W4284888618C2777774347 @default.
• W4284888618 hasConceptScore W4284888618C39432304 @default.
• W4284888618 hasConceptScore W4284888618C44870925 @default.
• W4284888618 hasConceptScore W4284888618C76886044 @default.
• W4284888618 hasLocation W42848886181 @default.
• W4284888618 hasOpenAccess W4284888618 @default.
• W4284888618 hasPrimaryLocation W42848886181 @default.
• W4284888618 hasRelatedWork W100509915 @default.
• W4284888618 hasRelatedWork W2051797732 @default.
• W4284888618 hasRelatedWork W2099778733 @default.
• W4284888618 hasRelatedWork W2291745079 @default.
• W4284888618 hasRelatedWork W2760063442 @default.
• W4284888618 hasRelatedWork W3128322280 @default.
• W4284888618 hasRelatedWork W4243100435 @default.
• W4284888618 hasRelatedWork W4284888618 @default.
• W4284888618 hasRelatedWork W4313561082 @default.

• next