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中文摘要：
地形的自相似特性在整个尺度空间上并非恒定的，而与度量的尺度范围相关。该文通过将自相似特性曲线划分为若干个线性区间，依据信息熵的定义提出了一个新的参数——自相似程度指数SSD（Self-Similarity Degree）来表征地形自相似的程度。进而采用距离度量和模糊c均值聚类分析，表明SSD是地形识别的一个有效特征，此特征的加入丰富了传统单-Hurst特征对分类对象的描述，提高了地形分类感知的精度。
英文摘要：
Terrain surface is not always so perfect that it keeps invariable self-similar characteristic in whole scale space. To describe the degree of the self-similarity, the self-similarity curve is divided into several linear parts and then a new parameter called Self-Similarity Degree （SSD） is presented in the similitude of information entropy. Furthermore, the simulation in which distance measurement and fuzzy c mean clustering are adopted and it shows that the new parameter is the effective feature for terrain recognition. As the presented feature provides more information than traditional single Hurst feature, the precision of terrain classing is improved.
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