抽样法估算影像植被覆盖度

Estimating Fractional Vegetation Cover of Images by Sampling Method

植被覆盖度是反映地表植物群落覆盖程度的一个重要参数,无论是用照相法还是用卫星遥感图像提取,都是通过依次计算每个像元来获取整张图像的覆盖度,这种方式在处理大尺度遥感图像或者像元数量较多的遥感图像时,会耗费较多的时间。为此,提出一种利用抽样法估算遥感图像植被覆盖度的新方法,即在每张图像中随机选取一定数量的像元,计算所选像元的植被覆盖度来表示整张影像的植被覆盖度,利用误差概率模型进行精度控制,使结果误差在合理范围内。通过控制图像数和抽样像元数验证了该方法的精度。对于照相法而言,当采样数超过384个时,误差基本稳定在0.005以内,相比逐像元法计算的误差可以忽略;对于遥感影像二分法,当处理的遥感影像为100张、采样点数为300个时,均方根误差基本稳定在0.02以内,同时耗时仅为逐像元法的1%以下。试验表明,利用抽样法估算影像植被覆盖度可以在满足精度的条件下,大大降低计算时间,提高工作效率。

Fractional vegetation cover is an important parameter to reflect the extent of vegetation community coverage on the surface. No matter using photographic method or remote sensing images to extract fractional vegetation cover,it should calculate each pixel to obtain the vegetation coverage of an image. This method is time-consuming when process large-size remote sensing images or remote sensing images with many pixels. Thus,it put forward a new method to estimate the vegetation coverage of a remote sensing image by using sampling method,i.e. to randomly select certain number pixels from each image to calculate the vegetation coverage of the selected pixel for representing the whole image and control the precision by using error probability model,making the error within a reasonable range. The accuracy of this method was controlled by the numbers of images and sampling pixels. As for the photographic method,when the sampling number was more than 348,the error was basically less than 0.005. The error could be neglected comparing with the calculation of pixel by pixel method. As for the dichotomy method of remote sensing images,when the processed image was 100 and the number of sampling was 300,the RMSE was basically less than 0.02 and time-consuming was only less than 1% of the pixel by pixel method. The results show that estimating vegetation coverage by using sampling method can not only greatly reduce time-consuming and increase work efficiency,but also meet the precision.