Integration of multi‐source NDVI data for the estimation of Mediterranean forest productivity

Abstract

This paper presents the development and testing of different integration procedures aimed at producing Normalized Difference Vegetation Index (NDVI) datasets with high spatial and temporal resolutions. In particular, two methods were considered, which both used higher spatial resolution information to increase the spatial detail of more frequent low resolution NDVI data. The first method was based on the extraction of per‐class NDVI end‐member values from low spatial resolution images (NOAA‐AVHRR), followed by a combination of these values with a reference land cover map. Starting from the same end‐members, the second method introduced further high resolution information by means of regression analyses applied per‐pixel to the multitemporal dataset. The performances of the two methods were evaluated by means of two experiments carried out in a Mediterranean study area (San Rossore, central Italy). First, the images produced were compared on a per‐pixel basis to higher spatial resolution Landsat TM/ETM+ data. Next, the NDVI temporal profiles were transformed into Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) estimates, which were combined with standard meteorological (radiation) data to compute forest Gross Primary Productivity (GPP). The validation of these GPP estimates was performed by comparison with the outputs of a more complex model of bio‐geochemical processes (FOREST‐BGC), already calibrated in the study area. The results of both tests indicated the greater accuracy of the more advanced per‐pixel integration method, which was capable of reproducing NDVI data with high spatial and temporal details.

Acknowledgments

The activity of Marta Chiesi within the present research was partially funded by an ASI (Agenzia Spaziale Italiana) grant, under contract ASI 1/R/073/01. The authors want to thank Professor Marco Bindi, Dr Paolo Cherubini, Dr Giorgio Matteucci and Dr Guenther Seufert for their assistance in the calibration of the FOREST‐BGC model. Thanks are finally due to two anonymous referees whose comments improved the quality of the original manuscript.