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COMPARISONOFGREENVEGETATIONFRACTIONRETRIEVALSFROMSPOT-VEGETATIONANDMSG-SEVIRISENSORS.pptx
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Transcript of COMPARISONOFGREENVEGETATIONFRACTIONRETRIEVALSFROMSPOT-VEGETATIONANDMSG-SEVIRISENSORS.pptx
(1) CNRS UMR 8586 PRODIG Pôle de Recherche pour l’Organisation et la Diffusion de l’Information Géographique, Paris, France
(2) Turkish State Meteorological Service, Remote Sensing Division, Ankara, Turkey
Comparison of Green Vegetation Fraction Retrievals from SPOT-VEGETATION and MSG-SEVIRI Sensors Bernard LACAZE (1) and Aydin ERTÜRK (2)
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SPOT-VEGETATION and MSG-SEVIRI NDVI data
SPOT-VEGETATION : deriving Green Vegetation Fraction (GVF) from scaled NDVI
MSG-SEVIRI : deriving GVF from spectral unmixing or scaled NDVI
Results : Comparison of dekadal NDVI and GVF data (MSG-SEVIRI and SPOT-VEGETATION)
Conclusion
Outline
IGARSS 2011 24-29 July, Vancouver, Canada 2
SPOT-VEGETATION sensor (since 1998)
IGARSS 2011 24-29 July, Vancouver, Canada
sun synchronous orbit
altitude 822 km
return interval 1 day
swath width 2250km
SPOT-4 and SPOT-5
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SPOT-VEGETATION 10-daily NDVI
IGARSS 2011 24-29 July, Vancouver, Canada
S10 :Maximum Value Compositing
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SPOT-VEGETATION 10-daily NDVI
IGARSS 2011 24-29 July, Vancouver, Canada
NDVI data : HDF format, 1 byte/pixel
Real NDVI = 0.004 * Digital Number -0.1
Status map : HDF format, 1 byte /pixel
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MSG-SEVIRI sensor (since 2004)
IGARSS 2011 24-29 July, Vancouver, Canada
MSG-1 and MSG-2
SEVIRI one image every 15mn Spinning Enhanced Visible and Infrared Imager
resolution at nadir 3km (1km for channel 12)
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- Land surface monitoring products are elaborated by EUMETSAT Land Surface Analysis Satellite Application Facility (LSA SAF) Lisbon, Portugal : NDVI is not a standard product of LSA SAF (vegetation parameters = FVC, LAI, FAPAR)
- daily NDVI derived from LSA-SAF spectral albedos is available from AMMASAT data base (area= West Africa, spatial resolution 0.05°, daily since september 2005)
- daily experimental NDVI data available from EUMETSAT, since February 2011 (+ pre-operational data from 2010 : 176 days, elaborated with Turkish State Metorological Service)
MSG-SEVIRI daily NDVI products
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covered area: West Africa 25° W to 25° E, 20° N to 5° S
resolution 0.05° 1000 samples x 500 lines
daily data since septembre 2005
NDVI calculated from spectral albedos produced by LSA-SAF (BRDF model Roujean et al., 1992, k0 parameter),
model fitted over 5 days)
NetCDF format, integer, NDVI*10000, NDVI≥0, -1 = ocean
MSG – SEVIRI NDVI daily data since sept. 2005 AMMASAT
database
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MSG – SEVIRI NDVI monthly synthesis january 2010 AMMASAT
database
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covered area:
whole MSG disk
MSG native projection 3712 samples x 3712 lines
176 days (February-August 2010)
NDVI calculated from top of atmosphere reflectances, with BRDF correction (daily mean, maximum and minimum NDVI, number of obervations)
HDF5 format, byte, NDVI*100, NDVI≥0
MSG – SEVIRI NDVI daily dataTurkish State Met. Service pre-
operational data (2010)
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MSG-SEVIRI NDVI 10-daily synthesis
IGARSS 2011 24-29 July Vancouver, Canada
Maximum NDVI 20-30 March 2010
0
0.7
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MSG-SEVIRI NDVI 10-daily synthesis
IGARSS 2011 24-29 July Vancouver, Canada
Maximum NDVI 20-30 March 2010
0
0.7
21-31 May 2007
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covered area: whole MSG disk
MSG native projection 3712 samples x 3712 lines
daily data since February 2011
NDVI calculated from top of atmosphere reflectances, with BRDF correction
HDF5 format, with 899 bytes header
MSG – SEVIRI NDVI daily dataNDVE :Eumetsat experimental data
(2011)
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MSG – SEVIRI NDVI daily dataEumetsat experimental data (2011)
surface type = IGBP land cover classification
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GVF is the fraction of green vegetation covering a unit area of horizontal soil, varying from 0 (bare soil) to 1 (full cover)
GVF is independent of leaf and soil optical properties although it is defined with reference to green elements
It is generally close to FAPAR (varying from 0 to 0.95) with the advantage of being defined independently of illumination conditions, making it an intrinsic canopy attribute
for these reasons, GVF is a very good candidate for substitution of classical vegetation indices like NDVI
From NDVI to Green Vegetation Fraction
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SPOT-VEGETATION : GVF is named fCover and available since October 2009 from Geoland 2 BIOPAR products database (archived data to be available end of 2011) ; Geoland2 is carried out in the context of GMES, a initiative of the European Commission, which aims to build up a European capacity for Global Monitoring of Environment and Security; other sites for obtaining or disseminating data : GEOSUCCESS, VGT4Africa, EUMETCAST, DevCoCast
MSG-SEVIRI: daily GVF (named FVC Fraction of Vegetation Cover) is an operational product since March 2007 available from LSA SAF archive http://landsaf.meteo.pt/
Availability of Green Vegetation Fraction data
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Deriving Green Vegetation Fraction (Fcover) from SPOT-VEGETATION data
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scaled NDVI
BioPar Product User Manual (2010)
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Deriving Green Vegetation Fraction (Fcover) from SPOT-VEGETATION data
IGARSS 2011 24-29 July, Vancouver, Canada
BioPar Product User Manual (2009)
NDVIsoil = min (NDVImin, 0.14)
NDVImax = 0.85
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Green Vegetation Fraction (FCover) from SPOT-VEGETATION data
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BioPar Product FCover
ADDITIONAL DATA:FCover-ERR (estimated uncertainty) SMB (Status Map or Quality Flag)NMOD (number of clear observations)LMK (Land cover map = GLC 2000 Global Land Cover Map)
Fcover : 30-days composite, updated every 10 days using a sliding window
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Green Vegetation Fraction (FCover) from SPOT-VEGETATION data
IGARSS 2011 24-29 July, Vancouver, Canada
BioPar Product FCover
GVF data available since oct. 2009; archived data available end of 2011
10° x 10° tiles
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Green Vegetation Fraction (FCover) from SPOT-VEGETATION : West Africa, July 1-10, 2010
IGARSS 2011 24-29 July, Vancouver, Canada
BioPar Product FCover
Example of SPOT-VEGETATION 10-daily GVF
DN=255 : Invalid
DN 0-250 = FVC*250
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Deriving Green Vegetation Fraction (FVC) from MSG-SEVIRI data
IGARSS 2011 24-29 July, Vancouver, Canada
EUMETSAT
The operational daily product FVC is based on the three short-wave channels (VIS 0.6µm, NIR 0.8µm, SWIR 1.6µm) using as input the k0 parameter of a parametric BRDF model (Roujean et al., 1992)
The algorithm relies on an optimised Spectral Mixture Analysis (SMA) technique. In a first step, an exhaustive training set for the soil and vegetation components is defined. Second, a Gaussian Mixture Model is fit to the training data. Third, a Bayesian model selection is used to compute the relative likelihood of membership in each soil/vegetation single-model. FVC is then estimated using a linear-weighted combination single-model estimate
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Daily Green Vegetation Fraction (FVC) from MSG-SEVIRI data
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EUMETSAT
4 sub-imagesHDF5 format
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10-day SPOT-VEGETATION S10 NDVI MVC, resampled at 0.025° resolution
Maximum of 10 daily NDVI values, MSG-SEVIRI experimental product, resampled at 0.025° resolution (daily mean of n available data during each day)
Results : comparison of NDVI products
IGARSS 2011 24-29 July, Vancouver, Canada
Example : 1-10 July 2010, West Africa area
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Results : SPOT-VEGETATION NDVI S10
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Example : 10-day NDVI (1-10 July 2010), West Africa area
DN
Cloud contaminated pixels
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Results : SPOT-VEGETATION NDVI
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Example : 10-day NDVI (1-10 July 2010), West Africa area cloudy pixels (from status map) in white
DN
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Results : MSG NDVI
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Example : 10-day NDVI (1-10 July 2010), West Africa area maximum of 10 daily mean values
NDVI x NDVI x 100
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Comparison of SPOT-VEG and MSG NDVI
IGARSS 2011 24-29 July, Vancouver, Canada
Example : 10-day NDVI (1-10 July 2010), West Africa area
Histograms of NDVI values (cloud-free pixels only)
SPOT-VEG
MSG-SEVIRI
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Comparison of SPOT-VEG and MSG NDVI
IGARSS 2011 24-29 July, Vancouver, Canada
Example : 10-day NDVI (1-10 July 2010), West Africa areacloud-free pixels only
MSG
SPOT-VEG
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10-daily SPOT-VEGETATION FVC (Geoland 2 BioPar FVC), resampled at 0.025° resolution
Mean of 10 daily MSG-SEVIRI operational product FVC (LSA-SAF) , resampled at 0.025° resolution
Mean of 10 daily MSG-SEVIRI scaled NDVI, using threshold values NDVImin = 0.098 and NDVI max = 0.71 ( values proposed by NOAA-NESDIS, Bob YU pers. comm.)
Results : comparison of FVC products
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Example : 1-10 July 2010, West Africa area
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BioPar Product FCover
Results : SPOT-VEG GVF (scaled NDVI)
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Example : 10-day FCOVER (1-10 July 2010), West Africa area
BioPar Product FCover
grey= no vegetation cover (GVF = 0) ; white = invalid data
GVF (%)
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Results : MSG-SEVIRI GVF (LSA SAF FVC)
IGARSS 2011 24-29 July, Vancouver, Canada
mean of daily FCOVER (1-10 July 2010), West Africa area
derived from FVC product
Grey= no vegetation cover (GVF=0)
GVF (%)
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Comparison of SPOT-VEG and MSG GVF
IGARSS 2011 24-29 July, Vancouver, Canada
Example : 10-day GVF 1-10 July 2010), West Africa areaCloud-free pixels with GVF>0 only
GVFmsg = 0.85 * GVFspot-veg + 10.49
r2 = 0.86
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Comparison of SPOT-VEG and MSG GVF
IGARSS 2011 24-29 July, Vancouver, Canada
Example : all Africa, years 2008,2009
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Results: MSG-SEVIRI GVF(scaled NDVI)
IGARSS 2011 24-29 July, Vancouver, Canada
mean of daily GVF (1-10 July 2010), West Africa area
Grey= no vegetation cover
GVF (%)
NDVImin = 0.098; NDVImax = 0.71(NOAA-NESDIS, 2011)
GVF (%)
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Comparison of SPOT-VEG and MSG FVC
IGARSS 2011 24-29 July, Vancouver, Canada
Example : 10-day GVF 1-10 July 2010), West Africa areaCloud-free pixels with GVF>0 only
MSG
SPOT-VEG
GVFmsg = 0.71 * GVFspot-veg + 17.88
r2 = 0.67
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Comparison SPOT-VEG vs MSG GVF
IGARSS 2011 24-29 July, Vancouver, Canada
Example : desert pixels (GVF = 0)
yellow : GVF = 0 for both data sourcesorange : only GVF SPOT-VEG=0
SPOT-VEG and MSG (FVC from LSA-SAF)
SPOT-VEG and MSG (GVF from scaled NDVI)
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It is suggested to make use of Green Vegetation Fraction as a substitute to NDVI
Both SPOT-VEGETATION (10-daily) and MSG-SEVIRI (daily) GVF data can be obtained on a near real-time basis: status of products = operational
MSG-SEVIRI has lower spatial resolution than SPOT-VEG, but provides a higher number of available observations in regions with high cloud occurrence, and can be used for high temporal resolution monitoring (1 to 5 days)
Conclusions 1
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Different procedures are used to extract FVC from spectral data: all methods suppose that atmospheric and BRDF corrections are efficient
Discrepancies between GVF results from MSG and SPOT-VEG are observed, mainly overestimation of GVF in arid areas when using MSG data
Further research is needed to validate FVC estimations and to ensure intercomparability of results between MSG, SPOT-VEG, MODIS, METOP,… using preferably the same preprocessing/ processing methods to derive GVF
Conclusions 2
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Télédétectionpeer-reviewed electronic open-access journalhttp://www.teledetection.net
IGARSS 2011 24-29 July, Vancouver, Canada
Thank you for your attention
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