1. Antonio Ruiz Verdú, Centre for Hydrographic Studies, CEDEX. Madrid. Spain 30 th Congress of the International Association of Theoretical and Applied Limnology. 12-18 August 2007. Montreal, Canada

2. 1.Reflectance spectra of Spanish inland waters 2.Phycocyanin (PC) as an indicator of cyanobacterial biomass 3.Approaches for PC estimation from remotely sensed data 4.Validation of algorithms in Spain 5.Examples of applications (thematic maps) SUMMARY

3. Reflectance spectra: Optical signature of natural waters

4. Reflectance spectra of Spanish inland waters

5. Examples of reflectance spectra for waters dominated by a single phytoplankton group (>90% of biovolume) Chlorophyceae Bacillariophyceae Cryptophyceae CYANOBACTERIA Chl-a Phycocyanin

6. Reflectance spectra of cyanobacterial blooms (July 2007, Spain)

7. Phycocyanin (PC) is a characteristic pigment of Cyanobacteria PC could be used as a proxy for cyanobacterial biomass PC absorption is noticeable in reflectance spectra (at around 625 nm) If adequate spectral bands are present, algorithms could be developed for PC retrieval from spaceborne sensors Envisat-MERIS (ESA) is currently the only operational spaceborne sensor capable of retrieving PC Remote sensing of Cyanobacteria Main facts:

8. PC as a proxy for cyanobacterial biomass Intracellular PC content in Cyanobacteria is typically higher than Chl-a BUT, PC:Chl-a ratios are not constant If Cyanobacteria are not dominant, the variability of PC:Chl-a ratios is higher HOWEVER, in the studied reservoirs in Spain, PC:Chl-a ratios are relatively constant for [Chl-a] > 2 mg m -3

9. Absorption coefficient (m-1) Reflectance Chl-a PC Carotenoids Chl-a Particle scattering Retrieving PC absorption from reflectance at 620 nm PC absorption can be detected in R spectra BUT, other pigments absorb as well (mainly Chl-a and Chl-b) Chl-a Chl-b Chl-c PC Relative pigment absorption Absorption of CDOM and detritus at 620 nm is often low but not negligible

10. Approaches for algorithm development 1. BAND RATIO R( 2 ) R( 1 ) R( 1 ) = Reflectance at absorption band R( 2 ) = Reflectance at reference band (no PC absorption) [PC] = f [R( 1 ) / R( 2 )]

11. Approaches for algorithm development 2. BASELINE R( 1 ) = Reflectance at absorption band R( 2 ) = Reflectance at reference band 1 (no PC absorption) R( 3 ) = Reflectance at reference band 1 (no PC absorption) R( 2 ) R( 1 ) R( 3 ) [PC] = f {0.5 x [R ( 1 ) + R ( 3 )] - R ( 2 )}

12. Approaches for algorithm development 3. NESTED BAND RATIO (Simis et al., 2005) Developed for MERIS bands M6 M7 M9 M12 Backscattering is calculated from band 12 Chl-a absorption is calculated from the ratio of bands 7 and 9 PC absorption is calculated from the ratio of bands 6 and 9 and corrected with the estimated chl-a absorption at 620 nm [PC] is calculated from PC absorption Simis, S. G. H., S. W. M. Peters, & H. J. Gons. (2005). Limnology and Oceanography, 50, 237-245.

13. Validation of PC algorithms 65 reservoirs and lakes sampled in the period 2001-2007 in Spain ( 200 sampling points ) Concurrent field measurements: Optical (reflectance, absorption…) Pigment quantification Taxonomic Image processing

14. Validation of PC algorithms Simis et al. (2005) algorithm R 2 =0.94 p<0.001

15. Validation of PC algorithms Simis algorithm has been validated with a common dataset from Spanish and Dutch inland water bodies The influence of other pigments in the algorithm has been investigated Comparison with other published algorithms is currently ongoing Simis, S.G.H., A. Ruiz-Verdú, J.A. Domínguez-Gómez, R. Peña-Martinez, S.W.M. Peters, and H.J. Gons. (2007). Remote Sensing of Environment 106, 414–427.

16. Obtaining maps for Chl-a and PC PC and Chl-a algorithms have been applied to MERIS and Chris/Proba imagery Chris/Proba: Experimental ESA satellite - 18 bands (similar to MERIS) - 17 m spatial resolution (MERIS=300 m) - Limited number of images Major requirement: An accurate atmospheric correction method is needed

17. MERIS IMAGERY OVER ALBUFERA DE VALENCIA LAKE Visible bands IR / VIS bands Obtaining maps for Chl-a and PC

18. CHRIS/PROBA IMAGERY OVER ALBUFERA DE VALENCIA LAKE Obtaining maps for Chl-a and PC Visible bands

19. Obtaining maps for Chl-a and PC PC March 1 st 2007 Chl-a March 1 st 2007 CHRIS / PROBA

20. Obtaining maps for Chl-a and PC Chl-a June 24 th 2007 PC June 24 th 2007 MERIS

21. Obtaining maps for Chl-a and PC Monitoring a eutrophic reservoir: Rosarito

22. Cyanobacterial biomass can be monitored from spaceborne sensors, by detecting the pigment Phycocyanin (PC) MERIS and CHRIS/PROBA imagery have been used successfully in Spanish lakes and reservoirs Algorithms are less accurate for low PC concentrations (i.e. early bloom stages) MAIN CONCLUSIONS

23. Antonio Ruiz Verdú, Ramón Peña Martínez and Caridad De Hoyos Alonso Centre for Hydrographic Studies, CEDEX. Madrid. Spain 30 th Congress of the International Association of Theoretical and Applied Limnology. 12-18 August 2007. Montreal, Canada