Estimation of dissolved organic carbon using Sentinel-2 in the eutrophic Lake Ebinur, China

Naixin CAO, Xingwen LIN, Changjiang LIU, Mou Leong TAN, Jingchao SHI, Chi Yung JIM, Guanghui HU, Xu MA, Fei ZHANG

Research output: Contribution to journalArticlespeer-review

Abstract

Dissolved 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. Copyright © 2024 by the authors.

Original languageEnglish
Article number252
JournalRemote Sensing
Volume16
Issue number2
DOIs
Publication statusPublished - Jan 2024

Citation

Cao, N., Lin, X., Liu, C., Tan, M. L., Shi, J., Jim, C.-Y., Hu, G., Ma, X., & Zhang, F. (2024). Estimation of dissolved organic carbon using Sentinel-2 in the eutrophic Lake Ebinur, China. Remote Sensing, 16(2), Article 252. https://doi.org/10.3390/rs16020252

Keywords

  • Arid region
  • Saline lake
  • Sentinel-2
  • CDOM
  • DOC estimation

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