Assessing the Feasibility of Satellite-Based Machine Learning for Turbidity Estimation in the Dynamic Mersey Estuary (Case Study: River Mersey, UK).
Saved in:
| Title: | Assessing the Feasibility of Satellite-Based Machine Learning for Turbidity Estimation in the Dynamic Mersey Estuary (Case Study: River Mersey, UK). |
|---|---|
| Authors: | Nangir, Deelaram1 (AUTHOR), Andredaki, Manolia1 (AUTHOR), Carnacina, Iacopo1 (AUTHOR) i.carnacina@ljmu.ac.uk |
| Source: | Remote Sensing. Nov2025, Vol. 17 Issue 21, p3617. 29p. |
| Database: | Academic Search Ultimate |
|
Full text is not displayed to guests.
Login for full access.
|
|
| FullText | Links: – Type: pdflink Text: Availability: 1 |
|---|---|
| Header | DbId: asn DbLabel: Academic Search Ultimate An: 189611959 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Assessing the Feasibility of Satellite-Based Machine Learning for Turbidity Estimation in the Dynamic Mersey Estuary (Case Study: River Mersey, UK). – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Nangir%2C+Deelaram%22">Nangir, Deelaram</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Andredaki%2C+Manolia%22">Andredaki, Manolia</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Carnacina%2C+Iacopo%22">Carnacina, Iacopo</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> i.carnacina@ljmu.ac.uk</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Remote+Sensing%22">Remote Sensing</searchLink>. Nov2025, Vol. 17 Issue 21, p3617. 29p. |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=189611959 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/rs17213617 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 29 StartPage: 3617 Titles: – TitleFull: Assessing the Feasibility of Satellite-Based Machine Learning for Turbidity Estimation in the Dynamic Mersey Estuary (Case Study: River Mersey, UK). Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Nangir, Deelaram – PersonEntity: Name: NameFull: Andredaki, Manolia – PersonEntity: Name: NameFull: Carnacina, Iacopo IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 11 Text: Nov2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 20724292 Numbering: – Type: volume Value: 17 – Type: issue Value: 21 Titles: – TitleFull: Remote Sensing Type: main |
| ResultId | 1 |