植被覆盖度是评估生态环境的一个重要参数，其对于全球环境变化和监测研究具有重要意义．如何从遥感资料估算植被覆盖度，并提高估算精度是建立全球或区域气候、生态模型的基础工作．该文从分析土壤、植被光谱信号的特点出发，根据植被覆盖度的定义，推导出计算植被覆盖度的方法，并进一步提出了计算植被覆盖度的三波段最大梯度差法．在此基础上，对部分植被覆盖下的土壤光谱实现重建．上述方法实现简单，适用范围广，并可有效分离植被、土壤的影响，因而有望替代常用的通过NDVI估算植被覆盖度的方法．

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.