Integrazione di dati telerilevati e ancillari per la simulazione della resa olivicola in Toscana.

The current paper presents the development and testing of a multi-step approach which integrates remotely sensed and ancillary data to estimate olive (Olea europaea L.) yield in Tuscany (Central Italy). The process combines olive NDVI values with meteorological data in a standard parametric model modified (C-Fix) that allows the estimation of daily gross primary productivity (GPP) for a period of ten years (2000-2009). Estimates of GPP together joint to estimates of respiration obtained through the biogeochemical model BIOME-BGC, can simulate net primary productivity (NPP), which is then cumulated over the whole growing season and then converted onto olive yield by using proper conversion factors. The accuracy of these estimates is finally assessed by comparison with the provincial statistics. The methodology can accurately reproduce inter-year olive yield variation over the entire region.