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Mapping aquatic phytoplankton blooms using Sentinel-2 satellite imagery.
* 1 , 2 , 3 , 4
1  universit√© de tours
2  Lebanese university
3  Lebanese CNRS
4  Lebanese CNRS, Remote sensing center
Academic Editor: Riccardo Buccolieri


Under the current high anthropogenic pressures, phytoplankton blooms are increasing in waters all over the world. This necessitates monitoring and management actions to prevent its environmentally negative impact. An efficient approach for monitoring water quality can be achieved through remote sensing. Satellite multispectral data acquired from Sentinel-2 were used to assess chlorophyll-a (chl-a) concentration in Karaoun Reservoir, largest water body in Lebanon. Radiometric and atmospheric corrections were applied to downloaded level 1 satellite images. Pre-processing steps of Sentinel-2 images consisted of radiometric calibration on SNAP, resampling bands on ENVI, atmospheric correction on 6S (Second Simulation of the Satellite Signal in the Solar Spectrum) and applying algorithm on ArcGIS.

Comparison between 6S code corrected images and field spectral signatures showed high correlation with R² = 0.74 and R² = 0.82 on two of validation dates indicating a good precision of the 6S code. Several simple linear regression algorithms were tested with all possible Sentinel-2 single bands and band combinations from band 1 to 8. A simple linear algorithm was then developed by comparing in-situ measurements to single bands and band ratio. On a single band level, Band 5 was correlated the most with in situ PC measurements with R2= 0.69. For band combinations, the best fit between bands reflectance and actual PC measurements was found for the band ratio B5/B4 with R2=0.862. Based on these findings, the empirical band ratio model was developed using a Red band 4 of spectral resolution (650-680 nm) with Vegetation Red Edge band 5 (698-713 nm) to estimate chl-a at Karaoun Reservoir. The algorithm gave good estimations for chl-a detection with R2 = 0.86 for calibration and R2 = 0.8 for validation. The algorithm was then used to map and investigate the spatial-temporal distribution of phytoplankton bloom throughout the reservoir. This multi-disciplinary approach can be applied to other water bodies as advanced monitoring and management approach.

Keywords: Chlorophyll-a; Sentinel-2; water quality; 6S.
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