Computer Simulation Model of Fractional Vegetation Cover and Its Pa-rameters Sensitivity

Fractional Vegetation Cover (FVC) is an important ecology parameter, which is essential in the studies of hydrology, ecology, and global variation.Currently, the estimation methods used for FVC, including eyeballing method and digital camera imagery interpretation method, are obviously subjective and uncertain.Furthermore, it is rather difficult for the statistical relationship between FVC and leaf area index (LAI) to establish by measurement of millions of samples that have similar vegetation structure parameters.Thus, it is an effective way for the estimation of FVC to develop a statistical model between FVC and LAI.In the paper, we simulated the soybean leaves using ellipses, and determined the position, orientation and size with random distribution function by choosing the key parameters in the soybean structure to obtain the FVC per area under different vegetation structure parameters.The model was validated with data measured in situ and the theoretical conclusion.The analysis of parameter sensitivity of the simulation model showed that the length of stem is not a sensitive parameter when it was longer than foliage interval; wheresa the angle of stem is not a sensitive parameter until it reache a threshold.The leaf tilt angle and foliage interval were in inverse portion to the fractional vegetation cover, while the semimajor and semiminor axis of leaf were in direct portion to the fractional vegetation cover.The semiminor axis of leaf was a much more sensitive parameter than semimajor axis of leaf.It suggested that it was a novel and feasible way for FVC.