Combining remote sensing and ancillary data to monitor the gross productivity of water-limited forest ecosystems
Author(s)
Maselli, Fabio
Papale, Dario
Puletti, Nicola
Chirici, Gherardo
Corona, Piermaria
Date Issued
2009
Type
Article
Abstract
This paper describes the development and testing of a procedure which combines remotely sensed and ancillary data to monitor forest productivity in Italy. The procedure is based on a straightforward parametric model (C-Fix) that uses the relationship between the fraction of photosynthetically active radiation absorbed by plant canopies (fAPAR) and relevant gross primary productivity (GPP). Estimates of forest fAPAR are derived from Spot-VGT NDVI images and are combined with spatially consistent data layers obtained by the elaboration of ground meteorological measurements. The original version of C-Fix is first applied to estimate monthly GPP of Italian forests during eight years (1999–2006). Next, a modification of the model is proposed in order to simulate the short-term effect of summer water stress more efficiently. The accuracy of the original and modified C-Fix versions is evaluated by comparison with GPP data taken at eight Italian eddy covariance flux tower sites. The experimental results confirm the capacity of C-Fix to monitor national forest GPP patterns and indicate the utility of considering the short-term effect of water stress during Mediterranean dry months.
Additional information
L'articolo è disponibile sul sito dell'editore www.sciencedirect.com
Citation
Maselli, F. et al. 2009. Combining remote sensing and ancillary data to monitor the gross productivity of water-limited forest ecosystems. "Remote Sensing of Environment" 113 ( 3): 657-667.
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