Super typhoon Haiyan makes landfall
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Lake Maggiore - Italy, 3-6 April 2000

STEM-VGT : Satellite measurements and terrestrial ecosystem modelling using VEGETATION instrument

G. DEDIEU (LERTS/ CESBIO Toulouse France)
Co investigators:JC Gérard (LPAP / IAL Liège),
D. Graetz (Gondwana Lab, CSIRO, Canberra, Australia)
Participants : B. Berthelot, P. Cayrol, S. Lafont, P.Maisongrande (CESBIO)
L. Kergoat (LET)
A. Chebouni (IRD)

Paper (pdf file, 2.55 M)

Our general objective is to develop process models of vegetation functioning that can be used at regional and global scales for predicting carbon and water exchanges between land surface and the atmosphere. The specific objective of this project is to develop and validate VEGETATION based methods for validating, driving, or calibrating such vegetation process models.

During the VEGETATION pre-launch phase, we used NOAA/AVHRR data as a surrogate of VEGETATION at both global and regional scales. The algorithms developed have been applied to actual VEGETATION data to address global and regional topics.

Atmospherically corrected VEGETATION measurements were used to estimate daily and seasonal vegetation net primary productivity (NPP) at the global scale with 0.5x0.5° resolution. The TURC model (Ruimy et al., 1996) is driven by NDVI through estimation of the fraction of Photosynthetically Active Radiation absorbed by plant canopies. Soil respiration, SR, is computed as a function of temperature and soil humidity. Net Ecosystem Productivity, the difference between NPP and SR, is used as input of an atmospheric transport model in order to check results through comparison to atmospheric measurements of CO2.

At local and regional scale, ground experiments acquired in 1998 and 1999 during the SALSA experiment, held at the border of USA and Mexico, were used to prepare the use of VEGETATIOn for calibrating a vegetation functioning model coupled to a SVAT. The coupled models are used to predict leaf area index (LAI), from which specral reflectances are estimated and compared to actual ones. Consistent results are obtained over this semi-arid area, even if further work is require to better understand the driving parameters of SWIR reflectances. Despite the weak vegetation cover in the SALSA area, VEGETATION data allowed to monitor the seasonal variation of LAI.

The main benefit of VEGETATION data relies in its high geometric and radiometric quality and its capability to maintain nearly constant space resolution in the field of view, resulting in an important saving of time when handling the data. In addition, parallel studies indicate that the blue channel could help to improve atmospheric correction, while overall quality of the system should shortly lead to operational normalization of bidirectional effects.