| Title | Multispectral data by the new generation of high-resolution satellite sensors for mapping phytoplankton blooms in the Mar Piccolo of Taranto (Ionian Sea, southern Italy) |
| Abstract | The HR (High-Resolution) EO (Earth Observation) satellite systems Landsat 8 OLI and Sentinel 2 were tested for mapping the frequent phytoplankton blooms and Chl a distributions in the sea basin of the Mar Piccolo of Taranto (Ionian Sea, southern Italy), using the sea truth calibration data acquired in 2013. The data were atmospherically corrected for accounting of the aerosol load on optically complexes waters (case II). Various blue-green and additional spectral indices ratios, were then satisfyingly tested for mapping the distribution of Chl a and differently sized phytoplankton populations through PLS (Partial Least Square regression) models, regressive statistical models and bio-optical algorithms. The PLS models demonstrated higher robustness for assessing the distribution of all the phytoplankton and Chl a except for those related to sub-surface micro-phytoplankton. The distributions obtained via a bio-optical approach (OC3 algorithm and full physically based inversion) showed a general agreement with the previous ones produced by statistical methods. The reflectance signals, captured by OLI and Sentinel 2 sensors in the visible and shorter wavelengths once atmospherically corrected, were found to be useful to map the coastal variability at detailed scale of Chl a and different phytoplankton populations, in the optically complexes waters of the Mar Piccolo. |
| Source | European Journal of Remote Sensing 52 (1), pp. 400–418 |
| Keywords | Phytoplanktoncoastal shallow watersLANDSAT 8 OLIregressive partial least square and bio-optical models |
| Journal | European Journal of Remote Sensing |
| Editor | Italian Society for Remote Sensing, Firenze, Italia |
| Year | 2019 |
| Type | Articolo in rivista |
| DOI | 10.1080/22797254.2019.1625726 |
| Authors | Borfecchia, Flavio; Micheli, Carla; Cibic, Tamara; Pignatelli, Vito; De Cecco, Luigi; Consalvi, Natalizia; Caroppo, Carmela; Rubino, Fernando; Di Poi, Elena; Kralj, Martina; Del Negro, Paola |
| Text | 411171 2019 10.1080/22797254.2019.1625726 ISI Web of Science WOS 000475926300028 Phytoplankton coastal shallow waters LANDSAT 8 OLI regressive partial least square and bio optical models Multispectral data by the new generation of high resolution satellite sensors for mapping phytoplankton blooms in the Mar Piccolo of Taranto Ionian Sea, southern Italy Borfecchia, Flavio; Micheli, Carla; Cibic, Tamara; Pignatelli, Vito; De Cecco, Luigi; Consalvi, Natalizia; Caroppo, Carmela; Rubino, Fernando; Di Poi, Elena; Kralj, Martina; Del Negro, Paola ENEA Natl Agcy New Technol Energy Sustainable E; ENEA Natl Agcy New Technol Energy Sustainable E; Ist Nazl Oceanog Geofis Sperimentale OGS; Tuscia Univ; CNR The HR High Resolution EO Earth Observation satellite systems Landsat 8 OLI and Sentinel 2 were tested for mapping the frequent phytoplankton blooms and Chl a distributions in the sea basin of the Mar Piccolo of Taranto Ionian Sea, southern Italy , using the sea truth calibration data acquired in 2013. The data were atmospherically corrected for accounting of the aerosol load on optically complexes waters case II . Various blue green and additional spectral indices ratios, were then satisfyingly tested for mapping the distribution of Chl a and differently sized phytoplankton populations through PLS Partial Least Square regression models, regressive statistical models and bio optical algorithms. The PLS models demonstrated higher robustness for assessing the distribution of all the phytoplankton and Chl a except for those related to sub surface micro phytoplankton. The distributions obtained via a bio optical approach OC3 algorithm and full physically based inversion showed a general agreement with the previous ones produced by statistical methods. The reflectance signals, captured by OLI and Sentinel 2 sensors in the visible and shorter wavelengths once atmospherically corrected, were found to be useful to map the coastal variability at detailed scale of Chl a and different phytoplankton populations, in the optically complexes waters of the Mar Piccolo. 52 Published version https //www.tandfonline.com/doi/full/10.1080/22797254.2019.1625726 27/05/2019 Multispectral data by the new generation of high resolution satellite sensors for mapping phytoplankton blooms pdf articolo Multispectral data by the new generation of high resolution satellite sensors for mapping phytoplankton blooms in the Mar Piccolo of Taranto Ionian.pdf Articolo in rivista Italian Society for Remote Sensing 2279 7254 European Journal of Remote Sensing European Journal of Remote Sensing carmela.caroppo CAROPPO CARMELA fernando.rubino RUBINO FERNANDO DTA.AD006.053.001 CYANOLAKES |
