A Review of Spatial Interpolation Methods for Environmental Scientists

This review aims to provide some guidelines and suggestions in relation to the application of the methods to environmental data by comparing the features of the commonly applied methods that fall into three categories, namely: non-geostatistical interpolators, geostatistical interpolators and combined methods. Commonly used assessment measures are summarised and the criteria used to judge each measurement are also discussed. Two new measurements are proposed and a procedure is developed to compare the performance of the methods for different variables and from various disciplines. A total of 51 comparative studies on the performance of various methods in environmental sciences are summarised. The performance of 62 methods and sub-methods in the 51 comparative studies is compared. Several factors that affect the performance are discussed, including sampling design, sample spatial distribution, data quality, correlation between primary and secondary variable, and interaction among various factors. The impacts of sample density, variation in the data, sampling design and stratification on the estimations of the methods are quantified using data from 77 cases. A total of 26 methods are then classified based on their features to provide an overview of relationships among these methods. These features are quantified and a cluster analysis is conducted to show similarities among these spatial interpolators. A decision tree for selecting an appropriate method from these 26 methods is developed based on data availability and nature. Finally, a list of software packages for spatial interpolation is provided. Some important factors for spatial interpolation in marine environmental science are discussed, and recommendations are made for applying the methods to marine environmental data.

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