植被覆盖度是地表生态系统中的重要参数，获取地面真实的植被覆盖度是遥感植被覆盖度反演的基础。通常植被覆盖度的测量方法主要有地面实地测量以及利用遥感数据进行估算两种方式。其中地面测量植被覆盖度的方法有人工目估法、传统采样法和照相法等，其中人工目估法精度不高，传统采样法操作复杂，照相法成像高度受限制，且针对枯落物并没有较好的算法能够求解其植被覆盖度。在利用遥感影像估算植被覆盖度时，当遥感影像尺寸较大或者处理影像数量较多时，传统逐像元法求解效率较低，耗时较长。针对上述问题，本文提出一种抽样法计算植被覆盖度的方法。根据抽样法的思想，对于地面植被覆盖度获取的情况，利用手持式激光测距仪对低矮灌木或高大乔木进行采样，从而实现快速植被覆盖度测量。该方法利用测量误差概率分布模型，计算出不同采样点条件下的植被覆盖度的误差，按照测量精度要求约束采样点数，进而获取满足各种精度条件下的植被覆盖度。通过室内室外实验测量、计算机模拟两种方式对该方法进行了测试。结果显示，与照相法获得的真实值相比，利用手持式激光测距仪可以获得满足精度条件的植被覆盖度测量，相比于传统地面测量方法具有精度高、操作便捷、测量效率高等优点。此外，抽样法还可以用于数码相片或者遥感影像的植被覆盖度提取算法中，即基于一种传统算法，选择数码相片或者遥感影像的部分随机像元，计算这一部分像元的植被覆盖度，以计算结果作为整幅影像的植被覆盖度。通过对数码相片、Google Earth图像以及TM影像进行实验，证明抽样法计算影像植被覆盖度可以在满足精度的条件下，大大提高计算效率，并且可以较好地估算枯落物的植被覆盖度，具有较高的应用价值。

Fractional vegetation cover is an important parameter in the ecosystem. Getting real ground vegetation cover is the basis of remote sensing of vegetation cover inversion. Typical methods for getting vegetation cover are ground field measurements and the use of remote sensing data. The former includes manual visual estimation, sampling and radiography, etc. But there are many problems of the methods such as low precision in the use of manual visual estimation, complex operations in the traditional sampling methods and height restriction in photographical estimating. Moreover, there are no vegetation cover algorithms for dead litter things. there are many images to be processed or an image of target is large, the traditional methods using each pixel to estimate the fractional vegetation cover of the whole image seem to be inefficient and time-consuming. To solve this problem, a sampling method is proposed in this paper to calculate fractional vegetation cover. In this paper, the use of hand-held laser range finder to estimate the fractional vegetation cover of low shrubs or tall trees is first introduced. The proposed method employs a measurement error probability distribution model to calculate the error of vegetation cover under different conditions of sampling points and meet a variety of precision by different constraints of sampling points. The method was tested in indoor and outdoor experiments, as well as computer simulation. The results show that, compared with the photography method, using a hand-held laser range finder can be obtained to meet different accuracy of vegetation coverage measurement with high precision, easy operation and high efficiency. In addition, the sampling method can also be used for estimating fractional vegetation cover of digital or remote sensing image，which means to choice some random pixels of the image and calculate vegetation cover of this part to replace the result of the whole image. This process is based on a traditional algorithm. Through the experiment of digital photos, Google Earth image and TM image, the sampling method to calculate the vegetation coverage is proved to be able to satisfy the precision condition, greatly improve the computational efficiency, and can be used to estimate the litter fall of vegetation cover. So it has high value for application.