地形熵聚类下利用多面函数拟合高程异常

A Polyhedral Function Fitting Method of Elevation Anomaly with Terrain Entropy and Clustering

提出了利用地形熵确定高程异常点分类数的方法,以距离与地形熵的比值作为指标,从高程异常点中选择中心点,利用多面函数拟合了高程异常曲面。结果显示,利用地形熵聚类拟合的高程异常,比单独采用聚类分析和地形熵的方法在外符合精度上分别提高了28%和48%。

A method is put forward to determine the classification number of elevation anomaly with terrain entropy.The ratio of distance and terrain entropy is taken as an index to select the center points of polyhedral function.On this basis,height anomaly surface is fitted with the selected center points.In order to compare the advantages and disadvantages of various methods,the outside precision is taken as an index to evaluate the accuracy of various methods.The results show that the accuracy of surface fitting using terrain entropy and clustering is 28% higher than that using clustering analysis alone,is 48% higher than that using terrain entropy alone.