1 / 23

MONITORING CYANOBACTERIA IN INLAND WATERS BY REMOTE SENSING

30 th Congress of the International Association of Theoretical and Applied Limnology. 12-18 August 2007. Montreal, Canada. MONITORING CYANOBACTERIA IN INLAND WATERS BY REMOTE SENSING. Antonio Ruiz Verdú , Centre for Hydrographic Studies, CEDEX. Madrid. Spain. SUMMARY.

ekauffman
Télécharger la présentation

MONITORING CYANOBACTERIA IN INLAND WATERS BY REMOTE SENSING

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. 30th Congress of the International Association of Theoretical and Applied Limnology. 12-18 August 2007. Montreal, Canada MONITORING CYANOBACTERIA IN INLAND WATERS BY REMOTE SENSING Antonio RuizVerdú, Centre for Hydrographic Studies, CEDEX. Madrid. Spain

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

  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) Bacillariophyceae Chlorophyceae Chl-a Phycocyanin Cryptophyceae CYANOBACTERIA

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

  7. Remote sensing of Cyanobacteria Main facts: • 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

  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. Particle scattering Reflectance Relative pigment absorption Chl-a Chl-a Chl-b Chl-a Carotenoids PC Chl-c PC Absorption coefficient (m-1) 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) • Absorption of CDOM and detritus at 620 nm is often low but not negligible

  10. R(l2) R(l1) Approaches for algorithm development 1. BAND RATIO [PC] = f [R(l1) / R(l2)] R(l1) = Reflectance at absorption band R(l2) = Reflectance at reference band (no PC absorption)

  11. Approaches for algorithm development 2. BASELINE [PC] = f {0.5 x [R (l1) + R (l3)] - R (l2)} R(l1) = Reflectance at absorption band R(l2) = Reflectance at reference band 1 (no PC absorption) R(l3) = Reflectance at reference band 1 (no PC absorption) R(l3) R(l2) R(l1)

  12. M6 M9 M7 M12 Approaches for algorithm development 3. NESTED BAND RATIO (Simis et al., 2005) • Developed for MERIS bands • 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. 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 Validation of PC algorithms

  14. Validation of PC algorithms Simis et al. (2005) algorithm R2=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. Obtaining maps for Chl-a and PC Visible bands IR / VIS bands MERIS IMAGERY OVER ALBUFERA DE VALENCIA LAKE

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

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

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

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

  22. MAIN CONCLUSIONS • 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)

  23. 30th Congress of the International Association of Theoretical and Applied Limnology. 12-18 August 2007. Montreal, Canada MONITORING CYANOBACTERIA IN INLAND WATERS BY REMOTE SENSING Antonio RuizVerdú, Ramón Peña Martínez and Caridad De Hoyos Alonso Centre for Hydrographic Studies, CEDEX. Madrid. Spain

More Related