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Integral field spectroscopy (IFS) provides a spectrum simultaneously for each spatial sample of an extended, two-dimensional field.
Therefore, methods and guidelines need to be developed that assist users in designing spatial sample configurations for use in digital soil mapping.
The uncertainty for spatial sample estimation propagates along a chain from spatial variation in the stochastic field to sample distribution and statistical tools used to obtain an estimate.
Figure 6 depicts a spatial sample of the SAGE results.
Decorrelation steps are converting those spatial sample values into a set of coefficients.
The spatial sample values are represented by a set of weighted superposition of 8 × 8 cosine functions.
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Spatial sampling is undertaken to estimate an attribute of a spatially distributed population.
However, those methods usually require high spatial sampling.
There are two approaches to spatial sampling.
The combined InSAR and GPS dataset provides a much improved spatial sampling density, revealing spatial patterns in the deformation field.
Achieving a similar level of spatial sampling and bandwidth using conventional piezoelectric-based detection methods would be extremely challenging.
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