适于ALOS图像植被信息提取的新植被指数

New vegetation index for extracting vegetation information from ALOS image

针对现有植被指数不适用于ALOS图像植被信息提取的问题,从分析植被的光谱特征入手,提出了一种基于植被样本的植被指数(vegetation sample-based vegetation index,VSVI),并通过数学公式推导证明了VSVI仅与植被的光谱信息有关,与土壤背景无关,具有一定的消除土壤背景影响的能力。利用该植被指数和采用阈值分割方法提取了南京市某区域ALOS图像中的植被信息,并与差值植被指数,比值植被指数、归一化差值植被指数及土壤调节植被指数等其他植被指数的植被信息提取结果进行了比较。研究结果表明,该文提出的VSVI植被指数能够克服其他植被指数的缺点,植被信息提取精度分别提高了21.7%,27.5%,14%和9.5%。

In view of the phenomenon that the existing vegetation indexes are not suitable for vegetation extraction of ALOS image, this paper, starting with an analysis of the spectral characteristics of the vegetation, puts forward a new vegetation index （ vegetation sample - based vegetation index, VSVI ） based on the analysis of vegetation samples and proves that this vegetation index is only associated with the spectral information of vegetation but not related to the soil background, thus having a certain capability of eliminating the soil background image with mathematical derivation. The vegetation of ALOS image is extracted by the vegetation index with the method of threshold segmentation and compared with the vegetation indexes（DVI, RVI, NDVI and SAVI）. The results show that the vegetation index is capable of overcoming the shortcomings of other vegetation indexes, and the vegetation extraction accuracy can be raised by 21.7%, 27.5%, 14% and 9.5% respectively.