Estimation of Dissolved Organic Carbon Using Sentinel-2 in the Eutrophic Lake Ebinur, China
"> Figure 1
<p>(<b>a</b>) Xinjiang, China, (<b>b</b>) sampling points over the main lake area, (<b>c</b>) average wind direction and speed in Lake Ebinur from 2014 to 2022, and (<b>d</b>) field sampling weather condition statistics.</p> "> Figure 2
<p>Flowchart of this study.</p> "> Figure 3
<p>Absorption coefficients of (<b>a</b>) CDOM and (<b>b</b>) SPM.</p> "> Figure 4
<p>Comparison between the absorption coefficients of dewatering and pure water ((<b>a</b>) represents the absorption coefficient of dewatering, (<b>b</b>) represents a comparison between the absorption coefficient of pure water and that of non-water, where the blue curve represents the average value of the measured absorption coefficient of non-water).</p> "> Figure 5
<p>CDOM inversion model validation of the QAA-CDOM.</p> "> Figure 6
<p>Accuracy verification of DOC estimation model ((<b>a</b>) linear regression model, (<b>b</b>) quadratic regression model, (<b>c</b>) exponential regression model, (<b>d</b>) logarithmic regression model).</p> "> Figure 7
<p>Monthly DOC inversion results for Lake Ebinur from 2018 to 2022.</p> "> Figure 8
<p>Interannual DOC changes in Lake Ebinur from 2018 to 2021 (considering that the area of Lake Ebinur varies greatly, the minimum lake area for different months in the same year was selected as the boundary when the annual average data of Lake Ebinur from 2018 to 2021 were synthesized).</p> "> Figure 9
<p>Seasonal DOC changes in Lake Ebinur from 2018 to 2021 (considering the large seasonal variation in Lake Ebinur’s area, the minimum lake area of the same month in different years was selected as the boundary when compiling the monthly average data of Lake Ebinur from 2018 to 2021).</p> "> Figure 10
<p>Average monthly DOC statistics of Lake Ebinur from 2018 to 2022. ((<b>a</b>) Line chart of the monthly DOC concentration in Lake Ebinur; (<b>b</b>) box chart of the average DOC concentration in Lake Ebinur in different months; (<b>c</b>) variation coefficient of DOC in different regions from 2018 to 2022; (<b>d</b>) variation coefficient of DOC in different regions from May to October.).</p> "> Figure 11
<p>Accuracy verification of linear regression model.</p> ">
Abstract
:1. Introduction
2. Research Area Overview
3. Data and Methods
3.1. Data Sources
3.2. Inherent Optical Characteristics of the Water Body
3.3. CDOM Inversion Model
QAA-CDOM Model
3.4. Technical Approach
4. Results
4.1. Analysis of Inherent Optical Characteristics of Lake Ebinur
4.2. Validation of CDOM Inversion Models
4.3. Estimation Model for DOC and Accuracy Verification
4.4. Spatial Variability Characteristics of DOC
4.5. Temporal Variation Characteristics of DOC
5. Discussion
5.1. Applicability of Data and Models
5.2. Uncertainties in DOC Estimate
5.3. Applications and Limitations of this Study
6. Conclusions
- (1)
- By measuring the absorption coefficients of Lake Ebinur’s water body, the intrinsic optical characteristics of Lake Ebinur were investigated. Through this examination, it was observed that the absorption coefficients of SPM and CDOM approach zero at around 700 nm, where the dominance of pure water absorption coefficients in the total absorption of water becomes evident. In conjunction with the band configuration of Sentinel-2 remote sensing imagery, the wavelength of 833 nm was selected as the reference wavelength for Lake Ebinur.
- (2)
- In this study, observation data during 2021 and 2023 were used to verify the applicability of the QAA-CDOM model in Lake Ebinur, in which the validation set r2 value was 0.72 and the RMSE value was 0.13 m−1. Meanwhile, the independent verification sample r2 value was 0.51 and the RMSE value was 0.12 m−1. The above verification results show that the QAA-CDOM model is suitable for the inversion of the CDOM concentration in a long Lake Ebinur time series. In comparison with multiple DOC estimation models, the linear regression model demonstrated the most favorable performance, yielding an r2 value of 0.72. The measured data in 2022 were used as independent verification samples, and the verification results (r2 = 0.6 and RMSE = 11.4 mg/L) showed that the DOC estimation model could be used to estimate the long-term DOC concentration in Lake Ebinur.
- (3)
- By conducting a comparative analysis of the spatial variation in Lake Ebinur’s DOC, it could be inferred that from 2018 to 2022, Lake Ebinur’s DOC concentration exhibited an overall increasing trend. The concentration predominantly ranged between 30 and 90 mg/L, with a few regions displaying DOC concentrations exceeding 150 mg/L. Further comparison of Lake Ebinur’s spatial DOC variations from 2018 to 2021 revealed a year-on-year increase in DOC concentration. Additionally, upon contrasting the spatial distribution patterns of DOC across different months, it became evident that DOC concentrations in June and July of each year exceeded those in other months, while concentrations in May were notably lower.
- (4)
- Analyzing the temporal variations in Lake Ebinur’s DOC concentration revealed a distinct fluctuating trend, characterized by an overall increasing trajectory over time. Among these variations, the month of June stood out with the highest average DOC concentration (80 mg/L), whereas the lowest average concentration was observed in May (48 mg/L). From 2018 to 2021, the coefficient of variation in region 4 was the highest, and the coefficient of variation in region 1 was the smallest.
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
CDOM | Colored dissolved organic matter |
DOC | Dissolved organic carbon |
DOM | Dissolved organic matter |
QAA | Quasi-analytical algorithm |
SPM | Suspended particulate matter |
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Cao, N.; Lin, X.; Liu, C.; Tan, M.L.; Shi, J.; Jim, C.-Y.; Hu, G.; Ma, X.; Zhang, F. Estimation of Dissolved Organic Carbon Using Sentinel-2 in the Eutrophic Lake Ebinur, China. Remote Sens. 2024, 16, 252. https://doi.org/10.3390/rs16020252
Cao N, Lin X, Liu C, Tan ML, Shi J, Jim C-Y, Hu G, Ma X, Zhang F. Estimation of Dissolved Organic Carbon Using Sentinel-2 in the Eutrophic Lake Ebinur, China. Remote Sensing. 2024; 16(2):252. https://doi.org/10.3390/rs16020252
Chicago/Turabian StyleCao, Naixin, Xingwen Lin, Changjiang Liu, Mou Leong Tan, Jingchao Shi, Chi-Yung Jim, Guanghui Hu, Xu Ma, and Fei Zhang. 2024. "Estimation of Dissolved Organic Carbon Using Sentinel-2 in the Eutrophic Lake Ebinur, China" Remote Sensing 16, no. 2: 252. https://doi.org/10.3390/rs16020252