scholarly journals Simultaneous atmospheric correction and quantification of suspended particulate matter in the Guadalquivir estuary from Landsat images

2015 ◽  
Vol 368 ◽  
pp. 15-20 ◽  
Author(s):  
M. Carpintero ◽  
M. J. Polo ◽  
Mhd. Suhyp Salama
Keyword(s):  
Particulate Matter ◽  
Suspended Particulate Matter ◽  
Atmospheric Correction ◽  
Temporal Distribution ◽  
Monitoring Network ◽  
Data Series ◽  
Landsat Images ◽  
Guadalquivir Estuary ◽  
Suspended Particulate ◽  
Analytical Approaches

Abstract. Earth observations (EOs) following empirical and/or analytical approaches are a feasible alternative to obtain spatial and temporal distribution of water quality variables. The limitations observed in the use of empirical approaches to estimate high concentrations of suspended particulate matter (SPM) in the estuarine water of Guadalquivir have led the authors to use a semi-analytical model, which relates the water constituents’ concentration to the water leaving reflectance. In this work, the atmospheric correction has been carried out simultaneously and the aerosol reflectance and backscattering coefficients of SPM obtained. The results are validated using in situ SPM data series provided by a monitoring network in the study area. The results show that the model allows us to successfully estimate backscattering coefficients of SPM in the estuary, differentiating clear and turbid water and using two ε(4,5) .These considerations improve the value of R2 from 0.68 (single ε(4,5)) to 0.86 (two ε( 4,5)) on 18 May 2009. This method could be used as a preliminary approach to obtain SPM concentration in the Guadalquivir estuary with the limitations that the model shows for turbid waters.

scholarly journals Remote Retrieval of Suspended Particulate Matter in Inland Waters: Image-Based or Physical Atmospheric Correction Models?

Water ◽  
2021 ◽  
Vol 13 (16) ◽  
pp. 2149
Author(s):  
Anas El Alem ◽  
Rachid Lhissou ◽  
Karem Chokmani ◽  
Khalid Oubennaceur
Keyword(s):  
Particulate Matter ◽  
Suspended Particulate Matter ◽  
Landsat Imagery ◽  
Atmospheric Correction ◽  
Physical Models ◽  
Cost Models ◽  
Blind Test ◽  
Validation Data ◽  
Suspended Particulate ◽  
Spm Concentration

The objective of this paper was to compare the limits of three image-based atmospheric correction models (top of the atmosphere (ToA), dark object subtraction (DOS), and cosine of the sun zenith angle (COST)), and three physical models (atmospheric correction for flat terrain (ATCOR), fast line-of-sight atmospheric analysis of spectral hypercubes (FLAASH)), and ACOLITE) for retrieving suspended particulate matter (SPM) concentrations in inland water bodies using Landsat imagery. For SPM concentration estimates, all possible combinations of 2-band normalized ratios (2bNR) were computed, and a stepwise regression was applied. The correlation analysis allowed highlighting that the red/blue 2bNR was the best spectral index to retrieve SPM concentrations in the case of image-based models, while the red/green 2bNR was the best in the case of physical models. Contrary to expectations, image-based atmospheric models outperformed the accuracy of physical models. The cross-validation results underlined the good performance of the DOS and COST models, with R2 > 0.83, NASH-criterion (Nash) > 0.83, bias = −0.01 mg/L, and RMSE < 0.27 mg/L. This outperformance was confirmed using blind test validation data, with an R2 > 0.86 and Nash > 0.58 for the DOS and COST models. The challenges and limitations involved in the remote monitoring of SPM spatial distribution in turbid productive waters using satellite data are discussed at the end of the paper.

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

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1662
Author(s):  
Hanghang Wang ◽  
Jie Wang ◽  
Yuhuan Cui ◽  
Shijiang Yan
Keyword(s):  
Particulate Matter ◽  
Suspended Particulate Matter ◽  
Atmospheric Correction ◽  
Solar Spectrum ◽  
Landsat 8 ◽  
Suspended Particulate Matter Concentration ◽  
Retrieval Model ◽  
Suspended Particulate ◽  
Spm Concentration ◽  
Sentinel 2

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.

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