Spatial properties of design-based versus model-based approaches to environmental sampling

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.