Fractional vegetation cover estimation over large regions using GF-1 satellite data

This paper evaluates the usefulness of the WFV (Wide Field View) imager onboard GF-1 satellite in vegetation mapping. Fractional vegetation cover (FVC) is an important surface microclimate parameter for characterizing land surface vegetation cover. Three kinds of remote sensing inversion models (NDVI regression model, spectral mixture analysis (SMA) model and dimidiate pixel model) were used to derive FVC with the GF-1/WFV data. The verification indicates that the FVC results based on the dimidiate pixel model are well agreement with the in situ measurements. And the estimated FVC result in Beijing-tianjin-hebei region demonstrate that the GF-1/WFV data are fit for studying vegetation over large regions.