ABSTRACT
Spatial sampling design plays an important role in many applications such as environmental monitoring, natural resource survey, ecological studies, and water resource management. For example, in the National Resources Inventory survey conducted by the Natural Resources Conservation Service at USDA to monitor the status and change of the soil, water, and related resources on nonfederal land in the United States, sample segments were selected in space in the first stage of a two-stage area sample, and spatial sampling design techniques were used to achieve geographic spread, which greatly increased the design efficiency (Nusser et al. 1998). In another example described by Zidek et al. (2000), the authors considered the problem of extending an existing pollutant monitoring network in Southern Ontario by adding monitoring stations at new spatial locations. To reduce the uncertainty in predicting multiple pollutants at unobserved locations, a model-based spatial sampling design method was used that maximized an entropy criterion based on a
of Design and Analysis of
Gaussian model. In both applications, spatial information is an important part of the data and has to be taken into account in design.
