V-代约束的结构保持空间插值算法

针对现有空间插值方法对样点空间分布及结构约束考虑较少,难以保真原有空间数据的统计参量等问题,利用Voronoi和Delaunay的相互关系,建立了基于样点分布V-邻域结构的插值控制点自适应生成方法,构建了顾及样点分布结构与分布密度的结构保持空间插值方法。基于中国气象台站日均气温数据的方法验证与对比表明,相比于常用的空间插值算法,本文算法具有更好的结构自适应性,且对原始数据的空间统计特征具有更好的保持性。

V-Neighborhood Interation-Constrained Structure-Preserving Spatial Interpolation Method

Existing spatial interpolation methods make little consideration of the irregular spatial distri-bution and structural constraints of sampling points,and rarely maintain the accuracy of spatial statis-tical parameters.In this paper,the correlation between Voronoi and Delaunay is used to construct aself-adaptive control point generating method based on the V-neighborhood structure of samplingpoints.On this basis,a structure-preserving interpolation method,which takes the structure con-straints of spatial and density distribution of sample points into consideration,was established.Themethod was validated with Chinese weather station network data.The results suggest that the algo-rithm has better structural self-adaptability and maintains more precisely statistical spatial features ascompared with the commonly used spatial interpolation algorithms.