Please use this identifier to cite or link to this item: http://hdl.handle.net/2067/2080
Title: Use of remotely sensed and ancillary data for estimating forest gross primary productivity in Italy
Authors: Maselli, Fabio
Barbati, Anna
Chiesi, Marta
Chirici, Gherardo
Corona, Piermaria
Keywords: Forest ecosystems;Gross primary productivity;Carbon uptake;C-Fix model;NOAA-AVHRR;SPOT-VGT
Issue Date: 2006
Publisher: Elsevier
Source: Maselli, F. et al. 2006. Use of remotely sensed and ancillary data for estimating forest gross primary productivity in Italy. "Remote Sensing of Environment" 100: 563–575
Abstract: 
The current paper describes the development and testing of a procedure which can use widely available remotely sensed and ancillary data to assess large-scale patterns of forest productivity in Italy. To reach this objective a straightforward model (C-Fix) was applied which is based on the relationship between photosynthetically active radiation absorbed by plant canopies and relevant gross primary productivity (GPP). The original C-Fix methodology was improved by using more abundant ancillary information and more efficient techniques for NDVI data processing. In particular, two extraction methods were applied to NDVI data, derived from two sensors (NOAA-AVHRR and SPOT-VGT) to feed C-Fix. The accuracy of the model outputs was assessed through comparison with annual and monthly values of forest GPP derived from eight eddy covariance flux towers. The results obtained indicated the superiority of SPOT-VGT over NOAA-AVHRR data and a higher efficiency of the more advanced NDVI extraction method. Globally, the procedure was proved to be of easy and objective implementation and allowed the evaluation of mean productivity levels of existing forests on the national scale.
Description: 
L'articolo è disponibile sul sito dell'editore www.sciencedirect.com
URI: http://hdl.handle.net/2067/2080
ISSN: 0034-4257
DOI: 10.1016/j.rse.2005.11.010
Appears in Collections:DiSAFRi - Archivio della produzione scientifica

Files in This Item:
File Description SizeFormat
RSE_masellichirici_GPP 1.pdf61.48 kBAdobe PDFView/Open
Show full item record

Page view(s)

1
Last Week
0
Last month
0
checked on Oct 20, 2020

Download(s)

1
checked on Oct 20, 2020

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.