title: Assessment of forest net primary production through the elaboration of multisource ground and remote sensing data.
abstract: This paper builds on previous work by our research group which demonstrated the applicability of a parametric model, Modified C-Fix, for the monitoring of Mediterranean forests. Specifically, the model is capable of combining ground and remote sensing data to estimate forest gross primary production (GPP) on various spatial and temporal scales. Modified C-Fix is currently applied to all Italian forest areas using a previously produced data set of meteorological data and NDVI imagery descriptive of a ten-year period (1999-2008). The obtained GPP estimates are further elaborated to derive forest net primary production (NPP) averages for 20 Italian Regions. Such estimates, converted into current annual increment of standing volume (CAI) through the use of specific coefficients, are compared to the data of a recent national forest inventory (INFC). The results obtained indicate that the modelling approach tends to overestimate the ground CAI values for all forest types. The correction of a drawback in the current model implementation leads to reduce this overestimation to about 9% of the INFC increments. The possible origins of this overestimation are investigated by examining the results of previous studies and of older forest inventories. The implications of using different NPP estimation methods are finally discussed in view of assessing the forest carbon budget on a national basis.
authors.affiliation: IBIMET-CNR, Via Madonna del Piano 10, 50019 Sesto Fiorentino, FI, Italy. maselli@ibimet.cnr.it
authors.forename: Fabio
authors.initials: F
authors.lastname: Maselli
authors.forename: Marta
authors.initials: M
authors.lastname: Chiesi
authors.forename: Anna
authors.initials: A
authors.lastname: Barbati
authors.forename: Piermaria
authors.initials: P
authors.lastname: Corona
mesh_terms: D018533:Biomass; D017753:Ecosystem; D004784:Environmental Monitoring / Q000379:methods*; D007558:Italy; D008954:Models, Biological; D063245:Plant Development; D058998:Remote Sensing Technology; D014197:Trees / Q000254:growth & development*