Comparison of MSG-SEVIRI and SPOT-VEGETATION data for vegetation monitoring over Africa

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Comparison of MSG-SEVIRI and SPOT-VEGETATION data for vegetation monitoring over Africa Bernard LACAZE CNRS UMR 8586 PRODIG Pôle Image et Campus Spatial, Université Paris Diderot Paris 7

Objectives Comparison of NDVI from coarse resolution satellites : MSG-SEVIRI, SPOT-VEGETATION NOAA-AVHRR, EOS-MODIS Comparison of FVC product delivered by LSA- SAF with an estimation of FVC derived from SPOT-VEGETATION

Comparison of NDVI from coarse resolution satellites Test area : West Africa (25 W to 25 E, 20 N to 5 S) Test period: may june 2006

Methods (NDVI) Re-sampling data at same spatial resolution (0.05 degree) Comparison of MSG NDVI with data from other sensors, taking into account different temporal compositing periods (10, 15 or 16 days) Analysis of temporal profiles (daily data) from MSG-SEVIRI for several land-use/land-cover classes (GLC-2000)

AMMASAT NDVI Archive from MSG SEVIRI source : LSA SAF+ POSTEL; start = sept. 2005 Image format : NetCDF Compositing period = 1 day (from normalized reflectances computed with a 5 days timescale) Projection = Plate carrée, Datum = WGS84 Pixel size = 0.05 degree (~ 5,6 km) Coverage: West Africa (25 W to 25 E, 20 N to 5 S) Nb. of samples = 1000 Nb. of lines = 500 Data type = signed integer (NDVI x 10000)

SPOT-VEGETATION NDVI S10 archive source : VITO; start = may 1998 Image format : HDF Compositing period = 10 days Projection = Plate carrée, Datum = WGS84 Pixel size = 0.008929 degree ( ~ 1km) Coverage : African continent Nb. of samples = 9633 Nb.of lines = 8177 Data type : byte NDVI = 0.004 * CN 0.1

NOAA-AVHRR NDVI archive source : NASA-GIMMS; start = july 1981 Image Format : GeoTIFF Compositing period= 15 days Projection = Plate carrée, Datum = WGS84 Pixel size = 0.07272727 degree ( ~ 8km) Global coverage Num. of samples = 4950 Num. of lines = 2091 Data type = signed integer (NDVI x 10000) Water and missing data NDVI = - 0.1

TERRA-MODIS NDVI Archive MOD13C1 source : NASA-WISP; start = march 2000 Image Format : HDF Compositing period= 16 days Projection = Plate carrée, Datum = WGS84 Pixel size = 0.05 degree (~ 5,6km) Global coverage Nb. of samples = 7200 Nb. of lines = 3600 Data type = signed integer (NDVI x10000)

Global Land Cover GLC 2000 from SPOT VEGETATION 2000 + radar data ERS et JERS + DMSP data+ global DEM GTOPO30 + auxilliary data (available maps) Spatial resolution~ 1 km 27 classes

NDVI from MSG-SEVIRI 4 may 23 june 2006 mean of 51 daily images

Comparison between MSG-SEVIRI and SPOT-VEGETATION 21 31 may 2006 MSG - SEVIRI Mean of 11 daily values In red, difference > 0.2 SPOT-VEGETATION 1 image (16 days compositing period)

Comparaison between MSG-SEVIRI and NOAA-AVHRR 16 31 may 2006 MSG - SEVIRI mean of 16 daily images In red, difference > 0.2 NOAA-AVHRR 1 image (16 days compositing period)

Comparison between MSG-SEVIRI and TERRA-MODIS 25 may 9 june 2006 MSG - SEVIRI mean of 16 daily images in red, difference > 0.2 TERRA-MODIS 1 image (16 days compositing period)

Daily NDVI from MSG-SEVIRI Period: may june 2006 Test areas defined using 3 GLC 2000 classes sandy desert dense herbaceous savanna dense evergreen forest

Daily NDVI from MSG-SEVIRI

Daily NDVI from MSG-SEVIRI Bernard Lacaze Land Surface Analysis SAF - 2010 User workshop

Daily NDVI from MSG-SEVIRI

Daily NDVI from MSG-SEVIRI

Daily NDVI from MSG-SEVIRI

Conclusions from NDVI comparison Results of test areas: mean NDVI values from coarse resolution sensors may differ from about 10% (MODIS = higher values, SPOT and AVHRR lower values, MSG intermediate values MSG-SEVIRI is the only data source giving reliable results in areas with persistent cloudiness (i. e. during monsoon period in West Africa); Unexpectedly high day to day variations in NDVI values derived from MSG-SEVIRI in some invariant areas like evergreen dense forest

Comparison of Fraction of Vegetation Cover derived from MSG-SEVIRI and SPOT-VEGETATION Period: may june 2007 MSG-SEVIRI daily values SPOT-VEGETATION: FVC from 10 days compositing period

Methods (FVC) Mosaicking and reprojection of FVC from MSG- SEVIRI Deriving FVC from NDVI of SPOT-VEGETATION Comparison of data at same temporal compositing period (10 days) Analysis of temporal profiles (daily data) from MSG-SEVIRI for several land-use/land-cover test areas (GLC-2000)

Methods (FVC from MSG-SEVIRI) Mosaic of 4 images

Methods (FVC from MSG-SEVIRI) Reprojection in Plate carrée, extraction of African continent and resampling at 0.025 3712 x 3712 pixels 3440 x 2920 pixels

Methods (FVC from MSG-SEVIRI) extraction of West Africa area and resampling at 0.05 Analysis of daily variations of FVC and computation of median value for 10 days 1000 x 500 pixels

Methods (FVC from SPOT-VEGETATION)

Methods (FVC from SPOT-VEGETATION) Adapted from BARTHOLOME et al., 2002 FVC = 0.85 = 0.10 (perennial vegetation cover, cloud-contaminated pixels) or per pixel adjustment procedure using temporal NDVI profile (36 dekadal values) (ephemeral vegetation, deserts)

Methods (FVC from SPOT-VEGETATION) Per pixel adjustment procedure to derive from temporal profile (36 dekadal values) : pixels with all 36 NDVI values < 0.20 (deserts) defined as median of 36 values pixels with at least 15 NDVI values < 0.20 (ephemeral vegetation cover) defined as minimum of these values below threshold pixels with 1 to 14 NDVI values < 0.20 (cloud-contaminated pixels) = 0.10 pixels with all 36 NDVI values > 0.20 (perennial vegetation cover) = 0.10

Methods (FVC from SPOT-VEGETATION)

Bare soil NDVI offset correction

FVC from SPOT-VEGETATION Year 2007 Maximum FVC Year 2007 Minimum FVC

FVC from SPOT-VEGETATION 21-31 may 2007- Fraction of Vegetation Cover (%)

Temporal profile of FVC 100 90 80 70 YEAR 2007 SPOT-VEGETATION closed evergreen forest 12394pixels FVC (%) 60 50 40 30 20 10 0 0 6 12 18 24 30 36 Dekades degraded evergreen forest 3438 pixels NOAA-AVHRR (GVF)

Temporal profile of FVC SPOT-VEGETATION YEAR 2007 60 FVC (%) 50 40 30 20 10 closed grassland 1917pixels open grassland+ shrubs 985 pixels open grassland 209pixels sparse grassland 425 pixels 0 0 6 12 18 24 30 36 Dekades

Temporal profile of FVC SPOT-VEGETATION

FVC from MSG-SEVIRI 21-31 may 2007

FVC from MSG-SEVIRI 21-31 may 2007- Fraction of Vegetation Cover (%)

Daily values of FVC 21-31 May 2007 MSG-SEVIRI

Comparison of FVCs 21-31 may 2007 MSG-SEVIRI SPOT-VEGETATION

Regression between FVCs (cloud-free pixels only) Y = 0.01 + 0.8 X MSG-SEVIRI r 2 = 0.94 SPOT-VEGETATION SPOT-VEGETATION

Conclusions of FVC comparison A biophysical measurement like FVC is better than an index like NDVI FVCs from MSG-SEVIRI and from SPOT-VEGETATION, although obtained through different approaches are highly correlated in cloud-free areas; investigations still needed to elucidate the difference in absolute values (about 20%) and in-depth comparison of seasonal and inter-annual trends Further inter-comparisons should be done with other sensors (AVHRR, MODIS, METOP, etc.) and need of validation of FVC estimates from high spatial resolution images and ground measurements

Questions Gaps in the data archive of FVC? Archive of FVC data before march 2007? Why not a full-disc image of FVC? Availability of 10 days and monthly FVCs? Availability of daily spectral albedos in 3 solar reflective channels?

Last, but not least FVC should be called GVF Fraction of Vegetation Cover is different from Green Vegetation Fraction. The former is a description of how green a land pixel is when seen from space. The latter just tells the fraction of the pixel that is occupied by vegetation, regardless whether such vegetation is green (e.g., full growth) or not green (e.g., partial growth or dormant).

Invitation to participate CNRS GDRI on MSG applications to environmental monitoring Project of implementing an international research network GDRI, to be submitted to CNRS in may 2011 Topic: multidisciplinary applications of MSG data for near-real time monitoring (geography, plant ecology, geology, epidemiology, natural hazards, etc.) If project accepted, CNRS funding available for meetings, exchanges, etc. (not for research) contact: lacaze.bernard@gmail.com

Thank you for attention