Antonio Ruiz Verdú, Centre for Hydrographic Studies, CEDEX. Madrid. Spain 30 th Congress of the...
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Transcript of Antonio Ruiz Verdú, Centre for Hydrographic Studies, CEDEX. Madrid. Spain 30 th Congress of the...
MONITORING CYANOBACTERIA IN MONITORING CYANOBACTERIA IN INLAND WATERS BY REMOTE SENSINGINLAND WATERS BY REMOTE SENSING
Antonio Antonio RuizRuiz VerdúVerdú,,
Centre for Hydrographic Studies, CEDEX. Madrid. SpainCentre for Hydrographic Studies, CEDEX. Madrid. Spain
3030thth Congress of the International Association of Theoretical and Applied Congress of the International Association of Theoretical and Applied Limnology. 12-18 August 2007. Montreal, CanadaLimnology. 12-18 August 2007. Montreal, Canada
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 Spain5. Examples of applications (thematic
maps)
SUMMARY
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Longitud de onda (nm)
Ref
lect
anci
a (R
rs, s
r-1)
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CASI-2
MERIS
TM
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Re
fle
cta
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Wavelength (nm)
12
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lect
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lect
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lect
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CASI-2
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cta
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Wavelength (nm)
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Reflectance spectra: Optical signature of natural waters
Reflectance spectra of Spanish inland waters
Examples of reflectance spectra for waters dominated by a single phytoplankton group (>90% of biovolume)
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Wavelength (nm)
R(
) / R
(67
5)
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Wavelength (nm)
R(
) / R
(67
5)
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Wavelength (nm)
R(
) / R
(67
5)
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Wavelength (nm)
R(
) / R
(67
5)
Chlorophyceae Bacillariophyceae
Cryptophyceae CYANOBACTERIA
Chl-a
Phycocyanin
Reflectance spectra of cyanobacterial blooms (July 2007, Spain)
• 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:
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Cyanobacte ria l chlorophyll a (mg m-3)
PC
AV
G (m
g m
-3)
y = 2.1412x
R2 = 0.9027
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Cyanobacte ria l chlorophyll a (mg m-3)
PC
AV
G (m
g m
-3)
y = 2.1412x
R2 = 0.9027
1 0
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
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Abso
rpti
on c
oeffi
cient
(m-
1)
Reflect
ance
Chl-Chl-aa
PCPCCarotenoidCarotenoid
ss
Chl-Chl-aa
Particle scatteringParticle 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-cPC
Relative pigment absorption
• Absorption of CDOM and detritus at 620 nm is often low but not negligible
Approaches for algorithm development
1. BAND RATIO
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R(2)R(1)
R(1) = Reflectance at absorption band
R(2) = Reflectance at reference band (no PC absorption)
[PC] = f [R([PC] = f [R(11) / R() / R(22)])]
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)
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R(2)R(1)
R(3)
[PC] = f {0.5 x [R ([PC] = f {0.5 x [R (11) + R () + R (33)] - R ()] - R (22)})}
Approaches for algorithm development
3. NESTED BAND RATIO (Simis et al., 2005)
• Developed for MERIS bands
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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.
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
Validation of PC algorithms
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PC measured (PCREF mg m-3)
PC r
etri
eved
(PC
RA
D ,
mg
m-3
)
Simis et al. (2005) algorithm
R2=0.94p<0.001
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.
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
MERIS IMAGERY OVER ALBUFERA DE VALENCIA LAKE
Visible bandsVisible bands IR / VIS bandsIR / VIS bands
Obtaining maps for Chl-a and PC
CHRIS/PROBA IMAGERY OVER ALBUFERA DE VALENCIA LAKE
Obtaining maps for Chl-a and PC
Visible bandsVisible bands
Obtaining maps for Chl-a and PC
[PC] (mg/m3)0 50 100 150 250 <255
[PC] (mg/m3)0 50 100 150 250 <255
[PC] (mg/m3)0 50 100 150 250 <255
PCPC March 1 March 1stst 2007 2007
[Cla] (mg/m3)0 50 100 150 250 <255
[Cla] (mg/m3)0 50 100 150 250 <255
[Cla] (mg/m3)0 50 100 150 250 <255
Chl-aChl-a March 1 March 1stst 2007 2007
0 20 60 100 140 180 220 >250 mg m-30 20 60 100 140 180 220 >250 mg m-3
CHRIS / PROBACHRIS / PROBA
0 20 60 100 140 180 220 >250 mg m-30 20 60 100 140 180 220 >250 mg m-3
Obtaining maps for Chl-a and PC
Chl-aChl-a June 24 June 24thth 2007 2007 PCPC June 24 June 24thth 2007 2007
MERISMERIS
Obtaining maps for Chl-a and PCEVOLUTION OF MEASURED AND ESTIMATED PHYCOCYANIN (SAMPLING POINT B )
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22/04/2004 22/05/2004 21/06/2004 21/07/2004 20/08/2004 19/09/2004 19/10/2004 18/11/2004
DATE
PC
(m
g m
-3)
MEASURED PCESTIMATED PC
Monitoring a eutrophic reservoir: Rosarito
• 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
MONITORING CYANOBACTERIA IN MONITORING CYANOBACTERIA IN INLAND WATERS BY REMOTE SENSINGINLAND WATERS BY REMOTE SENSING
Antonio Antonio RuizRuiz VerdúVerdú, Ramón Peña Martínez and Caridad De Hoyos , Ramón Peña Martínez and Caridad De Hoyos AlonsoAlonso
Centre for Hydrographic Studies, CEDEX. Madrid. SpainCentre for Hydrographic Studies, CEDEX. Madrid. Spain
3030thth Congress of the International Association of Theoretical and Applied Congress of the International Association of Theoretical and Applied Limnology. 12-18 August 2007. Montreal, CanadaLimnology. 12-18 August 2007. Montreal, Canada