Chlorophyll-a, Phycocyanin and Phytoplankton type products

Transcription

1 Chlorophyll-a, Phycocyanin and Phytoplankton type products Mariano Bresciani, Monica Pinardi, Claudia Giardino CNR IREA

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3 Aims Implementation of algorithms dedicated to phytoplankton's Integrate semi-empirical approaches and bio-optical modeling Exploitation of hyperspectral sensors Producing useful maps for users Qualification of Sentinel 2/3 for phytoplankton

4 Case studies: from blue to green waters MANTUA

5 Algorithm concept The parametrization was based on inherent optical properties measured in the study areas. An adaptive choice of wvl was adopted to consider the shift of Rrs features depending on pigment concentration. Regression lines for calibrating the 2- band algorithm for estimating Chl-a merging all the samples.

6 Bio-optical modelling Specific absorption spectra of four phytoplankton classes characterised by different algal pigments (color lines) and specific backscattering spectra of three different water types used to parametrise the model (dotted lines). List of scale and spectral parameters for running biooptical model.

7 Semi-empiric An adaptive choice of wvl with a relative maximum and minimum in the regions which are sensitive to pigments variations was adopted to consider the shift of Rrs features depending on pigment concentration.

8 Match-up of in situ Chl-a and imagery data Validation Curonia Mantua Chl-a APEX Chl-a Sentinel-2 and Sentinel-3

9 Validation Match-up of satellite imagery Southern lake Garda Sentinel Sentinel-3 Dolichospermum lemmermanni In situ Chl-a 4.8 (±0.7 mg/m 3 )

10 Mantua Lakes Chl-a from APEX Chlorophyll-a concentration map for the Mantua lakes system (APEX, 21 September 2011). Chlorophyll-a concentration map for the Mantua lakes system (APEX, 27 September 2014).

11 Mantua Lakes Chl-a from S2 mg/m 3

12 Time series

13 Mantua Lakes Phytoplankton types from APEX PC index RS: WGS84 / UTM zone 32N A proxy of PFT map of the Superior Lake derived from APEX 2014: Diatoms are mapped in turquoise; Cryptophyta species and Planktothrix sp., a cyanobacteria specie dominated by phycoerythrin (PE) pigments, are depicted in red.

14 Mantua Lakes Phytoplankton Type maps from S2 In situ In situ

15 Mantua Lakes WFD maps APEX, 27 September 2014 (Sentinel-2, 18 June 2016) (Sentinel-2, 9 September 2016)

16 Curonian Lagoon PC and Chl-a from APEX

17 Curonian Lagoon Chl-a from S2 Sentinel-2 17/08/2015 and S3 Sentinel-2 24/08/2016 Sentinel-3 03/09/2017 mg m mg m

18 Curonia Lagoon SCUM Cyanobacteria scum presence during June-October From 30 cloud free Landsat 8 MCI images in 13 images (corresponding 100%) cyanobacteria scum was detected.

19 Garda Lake products Sentinel-2 Sentinel-3 Landsat-8 Chl-a WFD

20 Conclusions The results confirm the robustness of bio-optical model and adaptive semi-empirical algorithms for Chl-a retrieval in oligo-mesotrophic and in meso-eutrophic waters, respectively. The results show that remote sensing data can help to monitor water quality. High spatial and spectral resolutions data were useful to recognize phytoplankton blooms Although not specifically designed for water quality, S2 is providing comparable result to ground truth. S3 needs more matchups data but it we expect that it will provide level 2 products in continuity with MERIS.