@article{Tsapanou2018b,

title = {Evaluating Ocean-Color Algorithms to remotely sense the surface suspended particle matter in the northeast Aegean Sea},

author = {A. Tsapanou and E. Oikonomou and S. Poulos and P.G. Drakopoulos},

url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/10773/2326133/Evaluating-ocean-color-algorithms-to-remotely-sense-the-surface-suspended/10.1117/12.2326133.short?SSO=1},

doi = {https://doi.org/10.1117/12.2326133},

year  = {2018},

date = {2018-08-06},

journal = {Proceedings of SPIE},

volume = {10773},

abstract = {Oceanographic investigations have significantly benefited from multispectral satellite products that simplify monitoring in coastal regions thanks to their high spatial-temporal resolution. The surface Suspended Particulate Matter (SPM) is an important water quality parameter which can be derived from empirical or analytical algorithms by using the atmospherically-corrected remotely sensed reflectance Rrs(λ) retrieved from satellite imagery. In this study, in situ SPM and Rrs(λ) data were collected in the Gulf of Alexandroupolis, Northeastern Aegean Sea in Greece (Eastern Mediterranean Sea) during low discharge period (June 2016). We attempt to compute remotely sensed reflectance from Landsat OLI8 imagery, in order to quantify surface SPM concentrations via both a Semi-Analytical and a Multi-Band Empirical Algorithm. When comparing the satellite estimations against the field measurements, both algorithm approaches provide a non absolute correlation with in situ Rrs (~20-30 % offset). As a result, a generic semi-analytical equation for Alexandroupolis Gulf is developed, following algorithm calibration in low turbidity waters. The proposed algorithm can be then equally implemented to the new Sentinel-2A sensor, in order to assess its variations against Landsat 8 and to determine the applicability extend of our approach.},

note = {Greece},

keywords = {algorithm development, earth observing sensors, in situ remote sensing, landsat, reflectivity, remote sensing, satellite},

pubstate = {published},

tppubtype = {article}

}

@article{Drakopoulos2015c,

title = {Estimating chlorophyll concentrations in the optically complex waters of the North Aegean Sea from field and satellite ocean colour measurements},

author = {P.G. Drakopoulos and A.C. Banks and G. Kakagiannis and A.P. Karageorgis and A. Lagaria and A. Papadopoulou and S. Psarra and N. Spyridakis and V. Zervakis},

url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/9535/1/Estimating-chlorophyll-concentrations-in-the-optically-complex-waters-of-the/10.1117/12.2192571.short?SSO=1},

doi = {http://dx.doi.org/10.1117/12.2192571},

year  = {2015},

date = {2015-06-19},

journal = {Proceedings of SPIE},

volume = {9535},

abstract = {In the Aegean Sea and Eastern Mediterranean there are large discrepancies between in situ and satellite ocean colour derived chlorophyll concentrations. The quantity that is monitored by ocean colour satellites and that can be used in the estimation of chlorophyll concentration is the remote sensing reflectance, defined as the ratio of the water leaving spectral radiance to the downwelling spectral irradiance. It can be determined in the field, with either above or in-water radiance and irradiance measurements. The complex optical properties of the North-East Aegean Sea, including radiance and irradiance, were studied during the AegeanMarTech project. Chlorophyll concentration estimates were derived from simultaneous above and in-water radiometric measurements. These were validated against chlorophyll concentration field data and compared against concurrent MODIS data from which chlorophyll was derived using two simple empirical algorithms. It was found that the MedOC3 algorithm outperforms the operational OC3M-547 algorithm and produces the least bias when compared against HPLC derived in situ chlorophyll. It is concluded that the greatest uncertainty in the inversion arises due to CDOM absorption below the 488 nm band. The reflectance ratios indicated that there is always an excess of yellow matter present in the study area and the water type could not be characterized optically as ‘’typical open ocean” Case 1.},

keywords = {algorithm development, MODIS, ocean optics, reflectivity, remote sensing, satellites, water},

pubstate = {published},

tppubtype = {article}

}