A statistical prediction technique for deriving contour maps from geophysical data

Abstract

A technique for preparing contour maps is presented which has particular applicability for geophysical data. This technique derives from the assumption that each measured value is a sample from a statistical distribution which is taken to be valid in the area around that sample location. This distribution may be specified in the manner which best defines the relationship between the data and its spatial environment. Extending this principle to cover all areas to be mapped, and not just those measured, it is possible to predict values over a grid array of locations and hence to produce a contour map. Inherent in this simple procedure is: (i) the ability to adjust to the nature of the data being contoured; (ii) the elimination of edge effects; (iii) visual indication of the relative accuracy with which contours are located, at all points of the map; (iv) the automatic downgrading of data values which are in error; (v) the ability to contour combinations of measured data values without compounding errors; and (vi) a relatively simple extension to data spatially distributed in three dimensions.