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INTRODUCTION

The overall objectives of the "VEGETATION" system are to provide accurate measurements of basic characteristics of vegetation canopies on an operational basis,

  • either for scientific studies involving both regional and global scales experiments over long time periods (for example development of models of the biosphere dynamics interacting with climate models),

 

  • or for systems designed to monitor important vegetation resources, like crops, pastures and forests.

The "VEGETATION" system, consisting of a satellite-borne sensor and of its associated ground segment, will provide long term basic measurements adapted to biosphere studies. Opportunities for scale integration are provided by the combination with the main SPOT instruments (HRVIR) which allow high spatial resolution for detailed modelling activities or multilevel sampling procedures. Availability of data to different types of users is facilitated through the centralisation of reception and archiving global data sets. The launch date (24th March 1998 for VEGETATION 1 and 4th May 2002 for VEGETATION 2) and duration of the system (min. 5 years of estimated instrument life time) are adapted to a systematic and extensive long term monitoring of the biosphere.

Clearly this system will benefit from detailed studies based on other systems that are dedicated to specific studies of the characteristics of remote sensing measurements or to their relationships with surface or processes' parameters. It must be envisaged that the evolution of the mission specifications will have to take into account results of such studies to provide improved characterisation of the biosphere state and dynamics.

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MISSION OBJECTIVES ssmenu

Surface parameters mapping: ssmenu

this is the basic requirement, especially for climate and meteorological studies where boundary conditions have to be prescribed as in the case of General Circulation Models or forecasting models. Factors such as albedo, surface roughness, resistances to heat exchanges (sensible and latent) are important variables for these models and they can be either determined directly from the measurements or inferred from identification of land cover. The seasonal and long-term variations of such variables are related to vegetation dynamics. The capability to identify, through these variations, physical characteristics of land cover is a key to accurate prescription of these variables. Scales addressed in GCM or forecasting models (typically about 100 km) require that land cover and its variability must be determined with a sampling of about 8 to 10 km : the basic spatial resolution needed for identification of land cover and its variability is 1 km.

Agricultural, pastoral and forest production: ssmenu

since the beginning of the land surface satellite remote sensing era (1972), important projects (for example LACIE, AGRISTARS for USDA, MARS and TREES  for CEC, just to mention the oldest ones...) have been set up to develop methodologies and strategies to use remote sensing data either for mapping of land use in anthropogenized or natural ecosystems or for estimation of production potential. Their specific objective was to determine the evolution of productions. This objective had to be adapted to the management of crop production for agricultural exporting countries, to the monitoring of pastoral resources and their dependence from meteorological evolution, to the evaluation of possible global impacts of deforestation and more generally to the need for information related to political or social orientations and decisions.

Terrestrial biosphere monitoring and modelisation: ssmenu

the contribution of the continental biosphere to the biogeochemical cycles (exchanges of carbon and other trace gases) and to water and energy exchanges is one of the objectives of the development of global models. Interaction with human activities is also one of the main points to be studied, because the effect of human pressure on the biosphere might be one of the means by which man is acting on climate in the long term. Biosphere processes and land cover characterisation are the basis for quantification : estimations of land cover variables as well as the dynamics of these variables have to be made in order to obtain a good understanding of these processes upon which models may be built. Predictions of impact of climate change on the biosphere and of interactions of the biosphere with the climate (either due to natural factors or to human pressure) can only be inferred from quantification and formalisation of the mechanisms by which vegetation cover and ecosystems are functioning. Multilevel series of models have to be developed and linked, ranging from ground studies, local parameterisation and exchange models to regional or global dynamics and interaction models. Remote sensing of the vegetation as shown above offers a unique tool for these developments, providing the specification of the systems be adapted to each particular need.

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VEGETATION: MAIN SYSTEM CHARACTERISTICS ssmenu

More details can be found in the "technical information" pages

Radiometry ssmenu

Spectral characteristics

 

Spectral bands specified

 VEGETATION 1

(actual values)

 VEGETATION 2

(actual values)

Surface reflectance range
BLUE (B0) 0.430 - 0.470 µm 0.437 - 0.480 µm 0.438 - 0.475 µm 0.0 - 0.5
RED (B2) 0.610 - 0.680 µm 0.615 - 0.700 µm 0.615 - 0.690 µm 0.0 - 0.5
NIR (B3) 0.780 - 0.890 µm 0.772 - 0.892 µm 0.782 - 0.890 µm 0.0 - 0.7
SWIR (MIR) 1.580 - 1.750 µm 1.600 - 1.692 µm 1.582 - 1.685 µm 0.0 - 0.6

Radiometric resolution (NEdR)
BLUE 0.003 for the entire range
RED 0.001 up to reflectance of 0.10, linear increase up to 0.003 for reflectance of 0.5
NIR, SWIR 0.003 for the entire range
Intra-image consistency within an entire image, corresponding to a NEdR of 0.005 for any reflectance value
Calibration accuracy interband and multitemporal : better than 3%
absolute : better than 5% .

 

Geometry ssmenu

Spatial resolution in both directions 1.15km at nadir
minimum variations for off-nadir observations
Field of view maximum off-nadir observation angle of about 50.5°
~2200 km swath width
Geometric accuracies local distortion less than 0.3 pixel
multispectral registration 0.1 km, desired
0.3 km specified
collocation with HRVIR 0.3 km for simultaneous acquisitions
multitemporal registration 0.3 km desired
0.5 km specified
location accuracy better than 500m desired
1000m specified
Spatial coverage about 90% of the equatorial areas are imaged each day, the remaining 10 % being imaged the next day. For latitudes higher than 35° (North and South), all regions are acquired at least once a day

 

Operation specifications ssmenu

Equator crossing time

(descending node) : 10:30 local solar time

Image transmission All spectral bands at full spatial resolution acquired on terrestrial areas will be stored onboard in a solid state memory, allowing the use of only one receiving station to which data will be transmitted in X band. All the spectral bands will also be transmitted in L band, for possible local receiving stations

 

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VEGETATION Products ssmenu

More details can be found in the "technical information" pages

The standard products have now been defined by the International Users' Committee. They are adapted to the particular missions described above and coherent as much as possible with the needs of existing projects. Two general categories of users could be identified :

  • research teams which are developping methodologies for the use of VEGETATION data or scientific biosphere studies : they generally have a study site (about 500 x 500 km2) and need long time series ( one year of daily or weekly data ),
  • projects which are based on the use of both VEGETATION and other data sets, for which the data delivery has to be fully operational and for long periods, for comparison or historical studies ( one continent every day). 

The overall organisation of the different levels as well as the general characteristics of the products are now defined, as shown in the following figure. To illustrate the special characteristics of the instrument, high priority was given to design products that would allow direct multitemporal registration as well as simple superposition with simultaneously acquired high resolution data.

 

Overall Organisation

 

VGT-P products ssmenu

They are adapted for the first type of users for which physical quality of data is important. They provide top-of-atmosphere reflectance values and correspond thus to data which would have been acquired by an ideal instrument : they are corrected for system errors (misregistration of the different channels, calibration of all the detectors along the line-array detectors for each spectral bands) and resampled to geographic projections for multitemporal analysis as well as for comparison with high resolution data. The accuracies given above apply to this data level. Annotations giving full information on applied corrections (calibration information, geometric parameters taking into account attitude and position on the orbit), or for further non-system corrections are attached to the data sets.

VGT-S products ssmenu

They are most probably the data sets which will be frequently used operationally : they correspond to VGT-P data to which corrections have been applied using ancillary information so as to generate top-of-canopy reflectance values and for which various synthesis types are provided :

  • a daily synthesis using the best available measurement on one day for a specific location (maximum NDVI criterion),
  • a 10-day synthesis, based on the selection of the "best" measurement of the entire period. The selection is based on the maximum NDVI value, as it is commonly accepted today..
  • 10-day syntheses at degraded spatial resolution (4 and 8 km)

VGT-D Products ssmenu

These are the most advanced products currently offered in the VEGETATION data catalog. There are only 10-day BDC syntheses (BDC for Bi Directional Composites), generated from the raw data according to the following process:

  • improved cloud masking, including identification of cloud shadows and thin clouds (Lissen & al, 2001.)
  • atmospheric correction with SMAC (rahman & Dedieu 1994) and based on aerosol load assessment derived from the relationship between B0 and MIR (Maisongrande & al 2001)
  • standardization of reflectance values by computing the BRDF (Duchemin & al 2001 & 2002)
  • 10-day compositing by averaging of the BRDF-standardized cloud-free reflectance values (Duchemin & al 2001 & 2002)

 

Key bibliographic reference on VEGETATION products: ssmenu

see the bibliography page in the "around VEGETATION" menu.

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