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

Water

Anas El Alem¹  Rachid Lhissou¹  Karem Chokmani¹  Khalid Oubennaceur¹ 

[1] Institut National de la Recherche Scientifique, Centre Eau Terre Environnement, 490 Rue de la Couronne, Québec, QC G1K 9A9, Canada;

关键词: remote sensing;    SPM modeling;    ToA;    DOS;    COST;    ATCOR;   

DOI  :  10.3390/w13162149

来源: DOAJ

【 摘 要 】

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 ($2b_{NR}$) were computed, and a stepwise regression was applied. The correlation analysis allowed highlighting that the red/blue $2b_{NR}$ was the best spectral index to retrieve SPM concentrations in the case of image-based models, while the red/green $2b_{NR}$ 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.

【 授权许可】

Unknown