Analyzing the effect of vegetation biochemical and biophysical variables to canopy reflectance and defining the importance of variables are useful in constructing reasonable spectral indices and inverse vegetation biochemical and biophysical variables accurately. In this study

we qualitatively calculated the sensitivity of canopy reflectance to leaf biochemical variables（ chloro-phyll

carotenoid

water content

and dry matter）

canopy structure parameter（ Leaf Area Index（ LAI））

and the background of soil（ soil moisture）. Considering that canopy reflectance easily becomes saturated with the increase of LAI

the sensitivity change of those parameters in different canopy density scenes is analyzed. We also discussed the precision of a priori knowledge used in vegetation biophysical and biochemical parameter inversion.In this study

PROSAIL model（ coupled with PROSPECT-5 leaf optical model and 4SAIL canopy radiative transfer model）was used to obtain adequate data

including vegetation variables and the corresponding canopy reflectance spectrum

which are impossible to obtain with in-site measurement. The adopted sensitivity analysis method was the extended Fourier amplitude sensitivity test（ EFAST）. This method first defined a search curve to scan the multidimensional space of model input parameters

and then the samples of model input parameters were generated by searching each axis of the multidimensional space at different frequencies.These samples were entered into the models to obtain the model output value. Fourier decomposition was used to compute the firstorder and total-order index.The result shows that the sensitivity of canopy reflectance to vegetation parameters is strongly related to canopy density. For medium and high canopy density

the canopy reflectance of VIS is mainly affected by Cab

and Cmand Cwexplain the bulk variation of canopy reflectance in NIR and SWIR. The canopy reflectance is slightly responsive to the variation in LAI and soil moisture.Results indicate that the requirement for accurate estimation of LAI is particularly urgent for very thick vegetation. For low canopy density

LAI is the most important variable that influences the canopy reflectance in NIR and SWIR regions

and the contribution of Cmand Cwis covered by LAI. Results show that estimating equivalent water thickness and dry matter content is difficult when LAI is low. Given that the canopy is sparse

the background of soil has a significant effect on canopy reflectance.With regard to the accuracy requirement of priori knowledge

the result shows that the priori knowledge

which may be able to distinguish dry or wet condition of soil

is enough to obtain the valid inversion result of vegetation biochemical and biophysical variables for low canopy density.In this study

we quantitatively analyzed the effect of canopy density on the sensitivity of canopy reflectance on various vegetation and background parameters with PROSAIL radiative transfer model and EFAST global sensitivity analysis method. Results obtained in this study can be used to choose and improve the inverse methods according to the real condition of the study area. In addition

we discussed in general terms the accuracy requirement of priori knowledge only for the spare canopy region.