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中文摘要：
针对子集区域划分方案对DEM地形信息量计算的不确定性影响问题,提出了一种基于最大熵定理的子集划分算法。新算法较好地避免了人为指定分级标准带来的DEM信息熵计算的主观性与随意性,为实现DEM地形信息量的有效评价提供了客观的理论依据。
英文摘要：
Entropy is a key index on measuring DEM terrain information content. According to the uncertainty of the influence of subset partition strategies on DEM information content, we present a new algorithm of subset partition based on the maximum entropy theory. Firstly a standard maximum entropy response curve is constructed. Then the optimal classification strategy is analyzed and calculated based on the differences between standard logarithm model and original information entropy model through the statistic characteristics of the linear slope vary and the stability of the curve. The new algorithm is proved to be efficient to avoid the subjectivity and arbitrariness in DEM artificial classifications, which provides an objective theoretical basis for DEM information entropy calculation.
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