A novel adaptive algorithm for spatial interpolation

The spatial distributions of soil heavy metals are not continuous with landscape heterogeneity. In the context, the existing spatial interpolation methods cannot obtain accurate estimation of contents of soil heavy metals in unknown locations. In this paper, we present a novel adaptive algorithm for spatial interpolation of soil heavy metals under spatial heterogeneity background. The core idea of our algorithm is to impose a constraint on spatial interpolation, which spatial estimation of soil heavy metals is processed in the context of spatial homogeneity. Our algorithm consists of extracting land patches, polygon merging, minimum unit partitioning and interpolation operator. The experimental results on real soil data show that the performance of our algorithm is more reliable than ordinary kriging method.