An algorithm for the construction of spatial coverage designs with implementation in SPLUS

Abstract

Space-filling “coverage” designs are spatial sampling plans which optimize a distance-based criterion. Because they do not depend on the covariance structure of the process to be sampled, coverage designs are computed more efficiently than designs that are optimal for mean-squared-error criteria. This paper presents an efficient algorithm for the construction of coverage designs and evaluates its performance in terms of computation time and effectiveness at finding “good” designs. Results suggest that near-optimal designs for reasonably large problems can be computed efficiently. The algorithm is implemented in the statistical programming language SPLUS and examples of the construction of coverage designs are given involving an existing network of ozone monitoring sites.