Abstract
Vegetation fraction is mainly associated with the living environment of human being. Forest canopy density (FCD) model and sub-pixel model are applied to automatically estimate the vegetation fraction in Qingjiang river basin. FCD model uses the vegetation bare-soil shadow index (VBSI). The sub-pixel model method applies the normalized difference vegetation index (NDVI) based on the dimidiate pixel algorithm. The vegetation fraction of Qingjiang river area is estimated based on the Landsat enhanced thematic mapper (ETM+) imagery with the ENVI 4.0 and the EARDAS 8.7 image software. Results indicate that the estimate accuracy of two models exceeds 75%. Both the FCD model and the sub-pixel model are reliable to extract the vegetation fraction. The information of this study is useful for further study on the vegetation fraction automated estimation, especially in mountainous area.
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