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Estimation of microphytobenthos biomass using in situ and airborne
Watersat Imaging Spectrometer Experiment (WISE) hyperspectral
imagery
B. Légaré 1,2, S. Mukherjee 1,2, C. Nozais 1,2, S. Bélanger 1,2
1 Département de Biologie, Chimie et Géographie, Université du Québec à Rimouski, Québec, Canada
2 Québec-Océan, Pavillon de Alexandre-Vachon, Université Laval, Québec, Canada
DATA AQUISITION AND STUDY AREA
METHODS DISCUSSION
CONCLUSION
August 2019
18th August 2019
First fieldwork mission
Collect of :
•In situ spectra with the VNIR
Analytical Spectral devices (ASD)
handheld 2
•Sediment core for the MPB
biomass and granulometry
Low tide flight of the
Manicouagan Peninsulawith
the Watersat Imaging
Spectrometer
Experiment (WISE) sensor
144 spectral bands from 361 to
991 nm
August 2022
July 2022
Second fieldwork mission
Collect of :
•In situ spectra with the VNIR
Spectra Vista Corporation (SVC) HR-
512i
•Sediment core for the MPB
biomass, granulometry, pigment
•Real-time measurement of
benthic algal concentrations
with the bbe moldaenke benthotorch
Third fieldwork mission
Identical to the second
fieldwork
RESULTS
This research combines ground-based measurements such as in situ spectra and in vivo MPB biomass with high-resolution airborne observations, opening
new frontiers in our capacity to estimate MPB biomass across the coast of the Manicouagan Peninsula. By exploring this approach, we aim to shed light on
the pivotal role of MPB in coastal ecosystems, the difficulties in assessing the biomass, and the potential of WISE
hyperspectral imagery to enhance our knowledge of these microscopic but ecologically significant organisms.
Rsurf in situ
August 2019
(ASD)
Rsurf in situ
July 2022
(SVC)
Rsurf in situ
August 2022
(SVC)
Conversion to the
SVC wavelength
Normalization
of the Rsurf
using the
Multiplicative Scatter
Correction
(MSC) by Fyfe (2003)
Conversion to the
WISE wavelengths
Spectra
similarities/differences
using the Spectral Angle Mapper
(SAM)
MPB index
Develop by Méléder
et al. (2011) and
Vander Wal et al.
(2010)
WISE images
Geometrically
corrected,
georeferenced and
radiometrically
calibrated
(Soffer et al., 2021)
ACWISE
atmospheric
correction
SABER bottom
reflectance retrieval,
based on the semi-analytical
algorithm of Albert and Mobley
(2003)
In Vivo MPB
biomass
•MPB biomasses measured in 2019 at PO and PL
are generally lower than in 2022.
•Biomass varied slightly according to the month of
harvest and the sampling sites.
•In 2019 and 2022, the PO site has the highest biomass,
followed by the PL site in August 2022.
•We note that the highest SAM values appear to be
those collected in 2019 at the PO site.
•Low SAM values were observed between sites and
sampling periods.
•It is possible to identify a red absorption band (between
676 nm and 683 nm) for spectra with chl-a concentrations
above 2 μg cm-2.
• In general, there is a difference between the maximum
and minimum Chl-a spectra for all sites
MPB biomass in vivo Spectral similarities and differences
Reflectance spectra VS. MPB biomass
In situ spectral index VS. WISE index
In situ spectra VS. WISE ACWISE corrected
VS. WISE ACWISE & SABER corrected
•We observe significant variability in the indices provides
from the WISES images.
•The IDiatom index produces the best linear relationship.
Brigitte Légaré (PhD fellow)
Brigitte.leg.95@gmail.com
•We observe very low reflectance values in WISE images
following the atmospheric correction.
•The SABER correction seems to adjust the low values of
the atmospheric correction, but a discrepancy is still
observable.
•There is considerable variability in spectral values on the
corrected WISE SABER corrected images for all three
sites.
•The average MPB biomass was around 6.56 μg/cm2for all sites and all
field campaigns, which is globally lower than the value measured in other
studies in Europe such as Kazemipour et al. (2010), Launeau et al. (2018) et
Méléder et al. (2018) .
•The indexes applied in this study were developed to estimate MPB
biomass universally by using absorption bands identified by dominant
diatom pigments located in the green (549 nm) and red (600 and 673 nm) to
quantify and enhance the presence of diatom biofilms on the sediment
surface (Méléder et al., 2011; Van der Wal et al., 2010). We observe a little
shift in the absorption band location, which might explain the low
values we obtain. Regional adjustment based on in situ data will be
needed to provide an accurate map of MPB biomass for the Manicouagan
Peninsula.
•As mentioned, we can observe a discrepancy in the WISE images. We
are still uncertain as to the reason why, and we are currently
investigating the data. A vicarious calibration using in situ spectra will be
performed, and other atmospheric correction algorithms will be applied to
the images to see if the problem still exists.
Acknowledgments
The authors thank the students that contributed to the feild work and the aboratories analysis: Lauriane Belles-Isles, Alicia Boismenu et
Josiane Lavoie-Bélanger. Futhermore, the authors thank the Fisheries and Oceans Canada (DFO), the Natural Science and Engineering
Research Council (NSERC) and the Canadian Space Agency (CSA) for financially support this project.
References
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Here we showed how a universal MPB index can provide an overview of the
MPB biomass, but regional adjustments are necessary to map accurately the
MPB in a temperate region such as the Manicouagan Peninsula (which is the next
step in this project).
In conclusion, the estimation of MPB biomass using in situ, in vivo and
airborne hyperspectral imagery, such as the WISE sensor, is a promising tool
for studying and monitoring these critical components of coastal ecosystems.
Figure 2. True-color image of
the Manicouagan Peninsula
from Sentinel-2 captured on 4th
September 2022. The outer box
delimits the subset used for
the study area Pointe-aux-
Outardes (PO; in blue), Baie St-
Ludger (BSL; in green) and
Pointe-Lebel (PL; in lilac).
Figure 1. Schematic timeline of the data acquisition
Figure 3.
Methodological
flow chart used in
this study
Figure 4. MPB biomass for the three sampling sites during the three
field campaigns
Figure 6. SAM analyses applied to mean reflectance spectra for the
three study sites during the three field campaigns.
Figure 5. Reflectance spectra normalized using the MSC method
according to MPB biomass for the three study sites during the three
field campaigns.
Figure 8. Relationship between the indices calculated with the in situ spectra
and the indices calculated using the WISE ACWISE and SABER corrected images
for the three study sites during the 2022 field campaigns. (The gray data represent the
2019 field campaign and are not included in the analysis.)
Figure 9. Mean reflectance spectra (in situ (MSC corrected), atmosphere
corrected WISE (ACWISE) and bottom reflectance retrieval (SABER)) of
sediments and their standard deviations (shaded area) for the three study sites.
INTRODUCTION
•MPB plays a crucial role in primary production within coastal
ecosystems (Cariou-Le Gall and Blanchard 1995; Guarini et al. 1998)
•MPB can contribute up to 50% of the total primary production
(Underwood and Kromkamp 1999).
•The global MPB production was estimated at approximately 0.5 Gt
C yr-1 (Cahoon, 1999).
•Therise of remote sensing technology has revolutionized our
ability to monitor the coast.
•Hyperspectral sensors like the Watersat Imaging Spectrometer
Experiment (WISE) can potentially identify components that would
go unnoticed with multispectral images at low spectral
resolutions, such as the MPB, which generates a particular
signature in the red range (Launeau et al. 2018).
In situ spectral index VS. MPB biomass
•Méléder et al. (2011) and Van der Wal et al. (2010) have
produced index to identify and quantify MPB :
Méleder et al. (2011) 𝐼𝐷𝑖𝑎𝑡𝑜𝑚 =2 𝑥 𝑅600
𝑅549+ 𝑅673
− 1
Van der Wal et al. (2010) MPBI =2 𝑥 𝑅586
𝑅495+ 𝑅673
− 1
•We observe significant variability in the indices for a
constant MPB biomass.
•The IDiatome index produces the best linear
relationship.
Figure 7. Relationship between the indices and the MPB biomass for the
three study sites during the 2022 field campaigns. (The gray data represent the
2019 field campaign and are not included in the analysis.)
