Marta Chiesi

Learn More
A daily 1-km Pan-European weather dataset can drive the BIOME-BGC model for the estimation of current and future beech gross primary production (GPP). Annual beech GPP is affected primarily by spring temperature and more irregularly by summer water stress. The spread of beech forests in Europe enhances the importance of modelling and monitoring their growth(More)
Our research group has recently proposed a strategy to simulate net forest carbon fluxes based on the coupling of a NDVI-driven parametric model, Modified C-Fix, and of a biogeochemical model, BIOME-BGC. The outputs of the two models are combined through the use of a proxy of ecosystem distance from equilibrium condition which accounts for the occurred(More)
In arid and semi-arid environments, the characterization of the inter-annual variations of the light use efficiency ε due to water stress still relies mostly on meteorological data. Thus the GPP estimation based on procedures exclusively driven by remote sensing data has not found yet a widespread use. In this work, the potential to characterize the water(More)
Keywords: Olive Eddy covariance C-Fix MODIS NDVI GPP a b s t r a c t We developed and tested a methodology to estimate olive (Olea europaea L.) gross primary production (GPP) combining ground and multi-sensor satellite data. An eddy-covariance station placed in an olive grove in central Italy provided carbon and water fluxes over two years (2010–2011),(More)
The assessment of net forest production is important for both scientific and practical purposes. The current paper presents the application of a recently developed strategy to estimate the net primary productivity of an even-aged Mediterranean pine forest (Natural Park of San Rossore, Central Italy). The strategy is based on the use of two models, C-Fix and(More)
A ten-year data-set descriptive of Italian forest gross primary production (GPP) has been recently constructed by the application of Modified C-Fix, a parametric model driven by remote sensing and ancillary data. That data-set is currently being used to develop multivariate regression models which link the inter-year GPP variations of five forest types(More)