1. APEX EnMAP
Sentinel-3PRISMA
1. Abstract
Mantua Lakes are formed by three shallow fluvial lakes
(surface 6.2 km2,
averaged depth 3 m), located in the centre of
the Padana plain, their water status is strongly affected by ag-
riculture. Excess growth of macrophyte vegetation and dys-
trophic water conditions makes the waters very productive;
the most intense phytoplankton blooms, characterized by
high biomass in surface, occur in the summer *1+.
4. Method
2. Study Area
Fig. 1: Location of the study area.
Fig. 2: Spectral absorption coefficient aph*() per each functional group (i). Fig. 4: Processing scheme, input simulation, model run, output decomposition and sensitivity index retrieval (R language - R 2014).
3. Data
1.Bresciani M., Rossini M., Cogliati S., Colombo R., Morabito G., Matta E., Pinardi M., Giardino C. (2013) - Analysis of
intra- and inter-daily chlorophyll-a dynamics in Mantua Superior Lake with spectroradiometric continuous measures.
Marine and Freshwater Research, 64: 1-14.
2.Giardino, C., Bresciani, M., Valentini, E., Gasperini, L., Bolpagni, R., & Brando, V. E. (2015). Airborne hyperspectral da-
ta to assess suspended particulate matter and aquatic vegetation in a shallow and turbid lake. Remote Sensing of
Environment, 157, 48-57.
3.Manzo C., Bresciani M., Giardino C., Braga F., Bassani C. (2015) Sensitivity analysis of a bio-optical model for Italian
lakes focused on Landsat-8, Sentinel-2 and Sentinel-3. European Journal of Remote Sensing, 48, 17-32
4.R (2014). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna,
Austria. URL http://www.R-project.org/.
5.Saltelli A., Annoni P., Azzini I., Campolongo F., Ratto M., Tarantola S. (2010) - Variance based sensitivity analysis of
model output. Design and estimator for the total sensitivity index. Comp. Phys. Comm., 181(2): 259-270.
6.Zambrano-Bigiarini M. (2013) - Sobol_sensitivity.R. Available online at: http://ipsc.jrc.ec.europa.eu/fileadmin/
repository/eas/sensitivity/software/sobol_sensitivity.R (active at 7th of July 2013).
OutputOutput
decompositiondecomposition
SENSITIVITY INDEX RETRIEVALSENSITIVITY INDEX RETRIEVAL
The model works in the 400-750 nm wavelength range,
while the model parametrization is based on WQP concen-
trations and SIOPs. The SA is performed according *3,4,5+

The results provided information relating the sensitivity of water reflectance as observable
with band setting of the latest generation sensors depending on different PFT.
References
6. Conclusion
Table 1: Spectral ranges with Si values of principal main functional groups
Output variance due to Single
functional group Vi
Total output variance V
MainMain
Effect (SEffect (Sii))
These findings shows that the combined spectral response of sensor and the PFT interaction have a spectral effect
that must be considered for the retrieval of these parameters by means of semi-empirical indices based on the band
combinations. The research activity is part of the EU FP7 INFORM (Grant No. 606865, www.copernicus-inform.eu/).
The spectral interaction between PFT is
between 5 and 15% of total output. In particu-
lar PRISMA was the best in the spectral sensiti-
vity definition in the first part of the spectrum,
while APEX in the second and third domain.
The Sentinel-3 showed lower performances al-
though in the third domain it was able to iden-
tify some spectral features.
PFT with their specific absorption coefficients, aph*i(), were obtained by field survey carried out from May
to September of 2011 and 2014 and referred to samples in which these were dominant in the waters.
Chlorophyta (Green Algae), Cyanobacteria with phycocyanin (PC), Cyanobacteria and Cryptophytes with
phycoerythrin (PE), Diatoms with carotenoids and mixed phytoplankton (Phyto).
Range (nm)
Main Funciontal
Group
PRISMA APEX EnMAP Sentintel-3
450<wl<500 Phyto 0,7 0,69 0,7 0,72
560<wl<565 PE 0,47 0,47 0,51 0,46
585<wl<595 PE-PC 0,46 0,52 0,5 -
615<wl<625 PC 0,42 0,41 0,45 0,44
635<wl<650 PC 0,33 - 0,44 0,36 - 0,44 0,39 - 0,40 -
690<wl<715 Phyto- PE - Diatom 0,28 - 0,25- 0,23 0,31 - 0,28- 0,19 0,29 - 0,27- 0,21 0,17 - 0,25 - 0,28
Fig. 6: PFTs Interaction graphs.
The analysis of Main Effect show (Table 1) that the contribution
of Phyto in all sensors is high in the first part of the spectum up
to 500 nm. PC have a sensitivity peak in the range 600 - 650 nm
visible in all sensors. PE have a peak in the range 560 - 590 and
670 - 690 nm. APEX is the best in the spectral shape definition
due to its higher spectral resolution. In the range 690—715 nm
the Phyto, PE and Diatom have high main effects. The graph of
Figure 5 show an example for Sentinel-3.Fig. 5: Spectral Main effect of PFTs for Sentinel –3 sensor
The types of phytoplankton and their concentrations are used to describe the status of water and the processes inside of this. This
work investigates bio-optical modeling of Phytoplankton Functional Types (PFT) in terms of pigment composition demonstrating
the capability of remote sensing to recognize freshwater phytoplankton. We studied the sensitivity of simulated water reflec-
tance (with band setting of APEX, EnMAP, PRISMA and Sentinel-3 (S3)) of Mantua lakes (Italy) by variance based method *3,4,5+.
The bio-optical model takes into account the reflectance dependency on PFT (which affect the absorption coefficients) and fixing
the geometric conditions of light field, concentrations of water quality parameters (WQPs) and the other inherent optical proper-
ties (IOPs). Results highlight the sensitivity of new generation sensors to different pigments of PFT in the water.
INTERACTION (1- Si)
EnMAPAPEX PRISMA Sentinel-3
5. Results
Max
Average
Min
Wavelength (nm)
Wavelength (nm)
Absorptioncoefficient
Wavelength (nm)
Wavelength (nm) Wavelength (nm)
Fig. 3: Spectral responses of Sensor Data.
Wavelength (nm)
Spectralresponse
SpectralresponseSpectralresponse
Spectralresponse
APEX
EnMAP
Sentinel-3
Output Reflectance
R (0-;)
PRISMA
Spectral Response
Ciro Manzo1
*, Cristiana Bassani1
, Monica Pinardi2
, Claudia Giardino2
, Mariano Bresciani2
1
CNR-IIA, Institute of Atmospheric Pollution Research, Research Area of Rome 1, Via Salaria Km 29,300, 00016-Monterotondo Scalo, Rome, Italy - phone: +39 06 90672712
2
Optical Remote Sensing Group, CNR-IREA, Via Bassini 15, 20133-Milan, Italy
Sensitivity in forward modeled hyperspectral reflectance due to phytoplankton groups
The output
is explained only
by single variability
The output
is due also to va-
riable interaction