Cited 81 time in
Evaluation of Sentinel-2 and Landsat 8 Images for Estimating Chlorophyll-a Concentrations in Lake Chad, Africa
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Buma, Willibroad Gabila | - |
| dc.contributor.author | Lee, Sang-Il | - |
| dc.date.accessioned | 2023-04-27T22:40:41Z | - |
| dc.date.available | 2023-04-27T22:40:41Z | - |
| dc.date.issued | 2020-08 | - |
| dc.identifier.issn | 2072-4292 | - |
| dc.identifier.issn | 2072-4292 | - |
| dc.identifier.uri | https://scholarworks.dongguk.edu/handle/sw.dongguk/6394 | - |
| dc.description.abstract | Much effort has been applied in estimating the concentrations of chlorophyll-a (Chla) in lakes. The optical complexity and lack of in situ data complicate estimating Chlain such water bodies.We compared four established satellite reflectance algorithms-the two-band and three-band algorithms (2BDA, 3BDA), fluorescence line height (FLH), and normalized difference chlorophyll index (NDCI)-to estimate Chlaconcentration in Lake Chad. We evaluated the performance and applicability of Landsat-8 (L8) and Sentinel-2 (S2) images with the four Chlaestimation algorithms. For accuracy, we compared the concentration levels from the four algorithms to those from Worldview-3 (WV3) images. We identified two promising algorithms that could be used alongside L8 and S2 satellite images to monitor Chlaconcentrations in Lake Chad. With an averaged R(2)of 0.8, the 3BDA and NDCI Chlaalgorithms performed accurately with S2 and L8 images. For the S2 and L8 images, 3BDA had the highest performance when compared to the WV3 estimates. We demonstrate the usefulness of sensor images in improving water quality information for areas that are difficult to access or when conventional data are limited. | - |
| dc.language | 영어 | - |
| dc.language.iso | ENG | - |
| dc.publisher | MDPI | - |
| dc.title | Evaluation of Sentinel-2 and Landsat 8 Images for Estimating Chlorophyll-a Concentrations in Lake Chad, Africa | - |
| dc.type | Article | - |
| dc.publisher.location | 스위스 | - |
| dc.identifier.doi | 10.3390/rs12152437 | - |
| dc.identifier.scopusid | 2-s2.0-85089548163 | - |
| dc.identifier.wosid | 000567213000001 | - |
| dc.identifier.bibliographicCitation | REMOTE SENSING, v.12, no.15 | - |
| dc.citation.title | REMOTE SENSING | - |
| dc.citation.volume | 12 | - |
| dc.citation.number | 15 | - |
| dc.type.docType | Article | - |
| dc.description.isOpenAccess | Y | - |
| dc.description.journalRegisteredClass | scie | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.relation.journalResearchArea | Environmental Sciences & Ecology | - |
| dc.relation.journalResearchArea | Geology | - |
| dc.relation.journalResearchArea | Remote Sensing | - |
| dc.relation.journalResearchArea | Imaging Science & Photographic Technology | - |
| dc.relation.journalWebOfScienceCategory | Environmental Sciences | - |
| dc.relation.journalWebOfScienceCategory | Geosciences, Multidisciplinary | - |
| dc.relation.journalWebOfScienceCategory | Remote Sensing | - |
| dc.relation.journalWebOfScienceCategory | Imaging Science & Photographic Technology | - |
| dc.subject.keywordPlus | REFLECTANCE ALGORITHMS | - |
| dc.subject.keywordPlus | PHYTOPLANKTON BLOOMS | - |
| dc.subject.keywordPlus | REMOTE ESTIMATION | - |
| dc.subject.keywordPlus | WATER | - |
| dc.subject.keywordPlus | INDEX | - |
| dc.subject.keywordPlus | VALIDATION | - |
| dc.subject.keywordPlus | CLASSIFICATION | - |
| dc.subject.keywordPlus | VARIABILITY | - |
| dc.subject.keywordPlus | VEGETATION | - |
| dc.subject.keywordPlus | PATTERNS | - |
| dc.subject.keywordAuthor | Lake Chad | - |
| dc.subject.keywordAuthor | Landsat | - |
| dc.subject.keywordAuthor | Sentinel | - |
| dc.subject.keywordAuthor | WorldView | - |
| dc.subject.keywordAuthor | Chlorophyll-a | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
30, Pildong-ro 1-gil, Jung-gu, Seoul, 04620, Republic of Korea+82-2-2260-3114
Copyright(c) 2023 DONGGUK UNIVERSITY. ALL RIGHTS RESERVED.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.
