Towards Progressive Strategies for Spatial Sampling in the Field

The geostatistical basis for adaptive/progressive sampling is discussed,following an introduction to the necessary statistical background and developments in geographic information technologies.Where computational resources are limited,as they are in the field,strategies that combine heuristic and numerical approaches are the key to successful field implementation.A sequential algorithm for rapid location of further samples is formulated,using the criterion of maximum global reduction in Kriging variance.Results from a test confirm the effectiveness of the proposed algorithms.