Spatial Interpolation

As an integral component of risk assessment, spatial interpolation techniques for predicting values at unsampled locations has been widely used to map environmental variables for identifying geographic areas for targeting of management interventions. The spatial interpolation methods can be largely classified into two broad groups:

• Deterministic or Non-geostatistical methods

  e.g., inverse distance squared: IDS), and

• Stochastic or Geostatistical methods

  e.g., ordinary kriging: OK) and All methods rely on the similarity of nearby sample points to create the surface

This section we will provide an overview of brief theory behind deterministic, and geostatistical interpolation techniques and we will explore these methods through example in R.

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