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Combining remote sensing and ancillary data to monitor the gross productivity of water-limited forest ecosystems
- Source :
-
Remote Sensing of Environment . Mar2009, Vol. 113 Issue 3, p657-667. 11p. - Publication Year :
- 2009
-
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. [Copyright &y& Elsevier]
Details
- Language :
- English
- ISSN :
- 00344257
- Volume :
- 113
- Issue :
- 3
- Database :
- Academic Search Index
- Journal :
- Remote Sensing of Environment
- Publication Type :
- Academic Journal
- Accession number :
- 36193144
- Full Text :
- https://doi.org/10.1016/j.rse.2008.11.008