Interpolation methods comparison

In many fields, spatial interpolation is used to evaluate physical data in a continuous domain. The many different techniques offer different performances, according to the characteristics of initial data points. The aim of this paper is to provide help in choosing and evaluating the technique that best suits the data set: a few indices measure the quality of interpolation by different viewpoints. An extensive test-case is reported, involving four different interpolation methods. Data sets are generally connected with environmental topics or taken from literature.