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.