In this paper we present the results obtained in the framework of a regional-scale analysis of the carbon budget of poplar plantations in the northern Italy. We explored the ability of the processbased model BIOME-BGC to estimate the gross primary production (GPP) of these agro-forestry ecosystems exploiting eddy covariance and satellite data using an inverse modeling approach.
We present a modified version of BIOME-BGC (named PROSAILH-BGC) which was coupled with the radiative transfer models PROSPECT and SAILH with the aims of i) improving the BIOME-BGC description of the radiative transfer regime within the canopy and ii) allowing the assimilation of remotely-sensed vegetation indexes time series, such as MODIS NDVI, into the BIOME-BGC.
In summary, this study showed that assimilation of eddy covariance and remote sensing data in a process model can provide important information for estimating the carbon budget at regional scale.JRC.H.2 - Climate chang
