Self-similarity Degree of Terrain Surface and Class Perception
地形表面的自相似程度与分类感知

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.