Crown cover fraction is an important ecological and environmental parameter. It's very important for the study of global environment change and observation. How to estimate crown cover fraction from remote sensing data and how to improve its precision are key work for the developing of global or regional climatic and ecological models. In the study

the authors developed a new method to estimate crown cover fraction according to the characters of soil and vegetation spectra and the definition of crown cover fraction. Furthermore

they also put forward a more simple method on that basis

which is called maximal gradient difference method. Once the crown cover fraction is known

the background spectra for pixels that are partly covered by vegetation can be rebuilt easily under the assumption of linear spectra mixing. Using the above method

the authors have successfully retrieved background information of a TM image of Colorado State. The introduced methods are simple

easy to performance

and can separate the effect of soil and vegetation effectively

so it's possible for them to replace the method of estimating crown cover fraction from NDVI

which is used widely at present. The authors also pointed out that if noise is removed from data before performing the method

the result will be much perfect.