Derivation and Evaluation of Global 1-km Fractional Vegetation Cover Data for Land Modeling

Abstract

Fractional vegetation cover (συ) is needed in the modeling of the land–atmosphere exchanges of momentum, energy, water, and trace gases. From global 1-km, 10-day composite Advanced Very High Resolution Radiometer normalized difference vegetation index (NDVI) data from April 1992 to March 1993, global 1-km συ is derived based on the annual maximum NDVI value for each pixel in comparison with the NDVI value that corresponds to 100% vegetation cover for each International Geosphere–Biosphere Program land cover type. This dataset is pixel dependent but season independent, with the seasonal variation of vegetation greenness in a pixel accounted for by the leaf area index. The authors’ algorithm is found to be insensitive to the use of a specific land cover classification. In comparison with an independent dataset derived by DeFries et al. by using a more sophisticated statistical approach, the current dataset has a similar spatial distribution but systematically smaller συ (particularly over shrublands and barren land cover). It also gives συ values that overall are consistent with those derived from higher-resolution aircraft and satellite data over Arizona and field-survey data over Germany.