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Article: Estimation of Dissolved Organic Carbon Using Sentinel-2 in the Eutrophic Lake Ebinur, China

TitleEstimation of Dissolved Organic Carbon Using Sentinel-2 in the Eutrophic Lake Ebinur, China
Authors
Keywordsarid region
CDOM
DOC estimation
saline lake
Sentinel-2
Issue Date2024
Citation
Remote Sensing, 2024, v. 16, n. 2, article no. 252 How to Cite?
AbstractDissolved organic carbon (DOC) in lakes, as a regulatory agent and light-absorbing compound, is a key component of the global carbon cycling in lacustrine ecosystems. Hence, continuous monitoring of the DOC concentration in arid regions is extremely important. This study utilizes the QAA-CDOM semi-analytical model, which has good accuracy in retrieving the CDOM (colored dissolved organic matter) concentration of Lake Ebinur. We chose to invert the CDOM time-series data from May to October during the 2018–2022 period. A DOC estimation model was then established using the linear regression approach based on the CDOM inversion data and the field DOC measurements. In general, the DOC concentration in Lake Ebinur exhibited an increasing trend from 2018 to 2022, typically lower in May and higher in June. When comparing the average values of DOC in Lake Ebinur for the same months across different years, it can be observed that the month of September exhibits the greatest variability, whereas June shows the least variability. In sum, this study successfully retrieved CDOM concentrations for a saline lake within an arid region and developed a DOC estimation model, thereby providing a reference for investigating carbon cycling in typical lakes of arid areas.
Persistent Identifierhttp://hdl.handle.net/10722/351662

 

DC FieldValueLanguage
dc.contributor.authorCao, Naixin-
dc.contributor.authorLin, Xingwen-
dc.contributor.authorLiu, Changjiang-
dc.contributor.authorTan, Mou Leong-
dc.contributor.authorShi, Jingchao-
dc.contributor.authorJim, Chi Yung-
dc.contributor.authorHu, Guanghui-
dc.contributor.authorMa, Xu-
dc.contributor.authorZhang, Fei-
dc.date.accessioned2024-11-21T06:38:20Z-
dc.date.available2024-11-21T06:38:20Z-
dc.date.issued2024-
dc.identifier.citationRemote Sensing, 2024, v. 16, n. 2, article no. 252-
dc.identifier.urihttp://hdl.handle.net/10722/351662-
dc.description.abstractDissolved organic carbon (DOC) in lakes, as a regulatory agent and light-absorbing compound, is a key component of the global carbon cycling in lacustrine ecosystems. Hence, continuous monitoring of the DOC concentration in arid regions is extremely important. This study utilizes the QAA-CDOM semi-analytical model, which has good accuracy in retrieving the CDOM (colored dissolved organic matter) concentration of Lake Ebinur. We chose to invert the CDOM time-series data from May to October during the 2018–2022 period. A DOC estimation model was then established using the linear regression approach based on the CDOM inversion data and the field DOC measurements. In general, the DOC concentration in Lake Ebinur exhibited an increasing trend from 2018 to 2022, typically lower in May and higher in June. When comparing the average values of DOC in Lake Ebinur for the same months across different years, it can be observed that the month of September exhibits the greatest variability, whereas June shows the least variability. In sum, this study successfully retrieved CDOM concentrations for a saline lake within an arid region and developed a DOC estimation model, thereby providing a reference for investigating carbon cycling in typical lakes of arid areas.-
dc.languageeng-
dc.relation.ispartofRemote Sensing-
dc.subjectarid region-
dc.subjectCDOM-
dc.subjectDOC estimation-
dc.subjectsaline lake-
dc.subjectSentinel-2-
dc.titleEstimation of Dissolved Organic Carbon Using Sentinel-2 in the Eutrophic Lake Ebinur, China-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.3390/rs16020252-
dc.identifier.scopuseid_2-s2.0-85183328361-
dc.identifier.volume16-
dc.identifier.issue2-
dc.identifier.spagearticle no. 252-
dc.identifier.epagearticle no. 252-
dc.identifier.eissn2072-4292-

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