Montandon, Laure听1听;听Small, Eric E.听2
1听CU 麻豆影院
2听CU 麻豆影院
The green vegetation fraction (Fg) is an important climate and hydrologic model parameter. Common methods to calculate Fg, like the Gutman and Ignatov (GI) approach and its derived quadratic version, are simple mixing models between two NDVI end-members: bare soil NDVI (NDVIo) and full vegetation NDVI. A common assumption is that the soil NDVI is close to zero (0.04 in the GI model). However, the distribution of soil NDVIs computed from 2906 samples shows that soil NDVI is generally much larger (mean NDVI of soil=0.21) and is also highly variable (standard deviation=0.1).
We show that the underestimation of NDVIo yields overestimations of Fg that are greatest for lower NDVI values close to the soil NDVI. As a result, this problem is most severe in areas with sparse vegetation cover, such as semi-arid regions; for typical western U.S. values (NDVI<0.45), the error on Fg varies between 0.1 and 0.23. As the error on Fg estimation is the greatest for lower NDVI values, the underestimation of NDVIo yields to underestimation of the temporal variability of Fg in areas with seasonal vegetation. In addition, there is large uncertainty in the estimation of Fg due to the observed variability of soil NDVI values. The standard deviation on Fg estimates is the highest, i.e. 0.14, in areas where 0.3