An evaluation of automated mapping algorithms for the analysis of Quaternary pollen data

Abstract The methodology of isopoll-map construction and the advantages of an automated quantitative mapping approach are discussed. Three mapping algorithms (distance weighted averaging, trend-surfaces, and universal kriging) are used to construct isopoll maps for a network of modern pollen surface samples from Alberta, Canada. The mapped isopoll surfaces are examined, compared, and evaluated. Distance weighted average maps provide faithful representations of pollen frequencies and isopoll gradients. However, the method provides little data generalisation and offers no modelling capability. While trend surfaces provide a high degree of data generalisation and offer modelling capability, the resulting surfaces are prone to significant distortion of pollen frequencies and isopoll gradients. Kriging provides an intermediate solution to the goals of faithful representation and useful generalisation. In addition, kriging provides certain modelling capabilities.

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