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Article

Consistency of Suspended Particulate Matter Concentration in Turbid Water Retrieved from Sentinel-2 MSI and Landsat-8 OLI Sensors

1
College of Resources and Environmental Engineering, Anhui University, Hefei 230601, China
2
Anhui Province Key Laboratory of Wetland Ecosystem Protection and Restoration, Anhui University, Hefei 230601, China
3
College of Science, Anhui Agricultural University, Hefei 230036, China
*
Author to whom correspondence should be addressed.
Academic Editor: Mariano Bresciani
Sensors 2021, 21(5), 1662; https://doi.org/10.3390/s21051662
Received: 31 January 2021 / Revised: 23 February 2021 / Accepted: 24 February 2021 / Published: 28 February 2021
(This article belongs to the Special Issue Remote Sensing of Water Quality and Water Environment)
Research on the consistency of suspended particulate matter (SPM) concentration retrieved from multisource satellite sensors can serve as long-time monitoring of water quality. To explore the influence of the atmospheric correction (AC) algorithm and the retrieval model on the consistency of the SPM concentration values, Landsat 8 Operational Land Imager (OLI) and Sentinel 2 MultiSpectral Imager (MSI) images acquired on the same day are used to compare the remote sensing reflectance (Rrs) SPM retrieval values in two high-turbidity lakes. An SPM retrieval model for Shengjin Lake is established based on field measurements and applied to OLI and MSI images: two SPM concentration products are highly consistent (R2 = 0.93, Root Mean Squared Error (RMSE) = 20.67 mg/L, Mean Absolute Percentage Error (MAPE) = 6.59%), and the desired results are also obtained in Chaohu Lake. Among the four AC algorithms (Management Unit of the North Seas Mathematical Models (MUMM), Atmospheric Correction for OLI’lite’(ACOLITE), Second Simulation of Satellite Signal in the Solar Spectrum (6S), Landsat 8 Surface Reflectance Code & Sen2cor (LaSRC & Sen2cor)), the two Rrs products, as well as the final SPM concentration products retrieved from OLI and MSI images, have the best consistency when using the MUMM algorithm in SeaWIFS Data Analyst System (SeaDAS) software. The consistency of SPM concentration values retrieved from OLI and MSI images using the same model or same form of models is significantly better than that retrieved by applying the optimal models with different forms. View Full-Text
Keywords: MSI sensor; OLI sensor; remote sensing; suspended particulate matter; turbid water; consistency MSI sensor; OLI sensor; remote sensing; suspended particulate matter; turbid water; consistency
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MDPI and ACS Style

Wang, H.; Wang, J.; Cui, Y.; Yan, S. Consistency of Suspended Particulate Matter Concentration in Turbid Water Retrieved from Sentinel-2 MSI and Landsat-8 OLI Sensors. Sensors 2021, 21, 1662. https://doi.org/10.3390/s21051662

AMA Style

Wang H, Wang J, Cui Y, Yan S. Consistency of Suspended Particulate Matter Concentration in Turbid Water Retrieved from Sentinel-2 MSI and Landsat-8 OLI Sensors. Sensors. 2021; 21(5):1662. https://doi.org/10.3390/s21051662

Chicago/Turabian Style

Wang, Hanghang, Jie Wang, Yuhuan Cui, and Shijiang Yan. 2021. "Consistency of Suspended Particulate Matter Concentration in Turbid Water Retrieved from Sentinel-2 MSI and Landsat-8 OLI Sensors" Sensors 21, no. 5: 1662. https://doi.org/10.3390/s21051662

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