Modeling dissolved organic carbon in inland waters using an unmanned aerial vehicles-borne hyperspectral camera

Remote sensing can provide an alternative solution to quantify Dissolved Organic Carbon (DOC) in inland waters. Sensors embedded on Unmanned Aerial Vehicles (UAV) and satellites that can capture the DOC have already shown good relationships between DOC and the Colored Dissolved Organic Matter absorption (aCDOM.) coefficients in specific spectral regions. However, since the signal recorded by the sensors is reflectance-based, DOC estimates accuracy decreases when inverting the aCDOM. coefficients to reflectance. Thus, the main objective is to study the potential of a UAV-borne hyperspectral camera to retrieve the DOC in inland waters and to develop reflectance-based models using UAV and satellite (Landsat-8 OLI and Sentinel-2 MSI) data. Ensemble based systems (EBS) were favored in this study. The EBS<sub>UAV</sub> calibration results showed that six spectral regions (543.5, 564.5, 580.5, 609.5, 660, and 684 nm) are sensitive to DOC in waters. The EBS<sub>UAV</sub> test results showed a good concordance between measured and estimated DOC with an R<sup>2</sup> = Nash-criterion (NASH) = 0.86, and RMSE (Root Mean Squares Error) = 0.68 mg C/L. The EBS<sub>SAT</sub> test results also showed a strong concordance between measured and estimated DOC with R<sup>2</sup> = NASH = 0.92 and RMSE = 0.74 mg C/L. The spatial distribution of DOC estimates showed no dependency to other optically active elements. Nevertheless, estimates were sensitive to haze and sun glint.

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Publication Details

Journal
The Science of The Total Environment
Published
2024-09-13
DOI
https://doi.org/10.1016/j.scitotenv.2024.176258
Citations
2
Primary Topic
Water Quality Monitoring and Analysis
Type
article
Field-Weighted Citation Impact
0.59

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article

Modeling dissolved organic carbon in inland waters using an unmanned aerial vehicles-borne hyperspectral camera

Peter G. C. Campbell, Aarthi Venkatesan, Rachid Lhissou, Sarah Martins et al.
2 citations
The Science of The Total Environment
Water Quality Monitoring and Analysis
0.59
article

Modeling dissolved organic carbon in inland waters using an unmanned aerial vehicles-borne hyperspectral camera

Peter G. C. Campbell, Aarthi Venkatesan, Rachid Lhissou, Sarah Martins, Scott R. Smith, Karem Chokmani, James C. McGeer, Jeffrey A. Cardille, Anas El Alem
article en
2 citations

Abstract

Remote sensing can provide an alternative solution to quantify Dissolved Organic Carbon (DOC) in inland waters. Sensors embedded on Unmanned Aerial Vehicles (UAV) and satellites that can capture the DOC have already shown good relationships between DOC and the Colored Dissolved Organic Matter absorption (aCDOM.) coefficients in specific spectral regions. However, since the signal recorded by the sensors is reflectance-based, DOC estimates accuracy decreases when inverting the aCDOM. coefficients to reflectance. Thus, the main objective is to study the potential of a UAV-borne hyperspectral camera to retrieve the DOC in inland waters and to develop reflectance-based models using UAV and satellite (Landsat-8 OLI and Sentinel-2 MSI) data. Ensemble based systems (EBS) were favored in this study. The EBS<sub>UAV</sub> calibration results showed that six spectral regions (543.5, 564.5, 580.5, 609.5, 660, and 684 nm) are sensitive to DOC in waters. The EBS<sub>UAV</sub> test results showed a good concordance between measured and estimated DOC with an R<sup>2</sup> = Nash-criterion (NASH) = 0.86, and RMSE (Root Mean Squares Error) = 0.68 mg C/L. The EBS<sub>SAT</sub> test results also showed a strong concordance between measured and estimated DOC with R<sup>2</sup> = NASH = 0.92 and RMSE = 0.74 mg C/L. The spatial distribution of DOC estimates showed no dependency to other optically active elements. Nevertheless, estimates were sensitive to haze and sun glint.

The Science of The Total EnvironmentVol. 954
Institut National de la Recherche Scientifique (CA), NGC Aerospace (Canada) (CA), Wilfrid Laurier University (CA)
Natural Sciences and Engineering Research Council of Canada
Life below water, Clean water and sanitation
Openalex Percentile: Top 30%
Water Quality Monitoring and Analysis
0.59
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