Assimilation of satellite observations for the estimation of Savanna gross primary production

Abstract

Monitoring vegetation gross primary production (GPP) is required for both carbon balance studies and early warning systems aiming to detect unfavorable crop and pasture conditions. This manuscript describes the assimilation of MODIS observations by a simple process model, fed by meteorological data (temperature, incident radiation and rainfall) and linked with a canopy reflectance model, to estimate GPP. GPP simulations are benchmarked against eddy covariance data collected in a semi-arid environment of a sparse Savanna in the Sudan.