Don L. Stevens, Jr.
_{Department of Statistics, 44 Kidder Hall
Oregon State University, Corvallis, OR 97333 USA
Tel.: +001 541 737 3587; Fax +001 541 737 3489
stevens@stat.oregonstate.edu}

Abstract
It is widely recognized that an efficient sample of a spatially distributed resource will have some degree of regularity.  For example, locating sample points at the nodes of a regular grid is an optimal model-based design for some  semivariograms and domain shapes.  Locating points becomes more complicated if the domain has an irregular shape or if the design incorporates existing sample points.  In this talk, I review some model-based techniques, such as simulated spatial annealing, for incorporating prior knowledge in locating new sample points.  These techniques are contrasted with design-based techniques, such as generalized random tessellation stratification, that can also incorporate prior knowledge and existing sample points.

Keywords: spatial simulated annealing, optimal spatial design

In: Caetano, M. and Painho, M. (eds). Proceedings of the 7th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, 5 – 7 July 2006, Lisboa, Instituto Geográfico Português