Mapping the diversity of forest attributes: a design-based approach

What is it about?

Spatially explicit estimates are needed in many environmental and ecological applications for making maps: the increasing practical demand is for information on the spatial distribution of environmental and ecological attributes within the area of interest. Here, diversity index values at single nonsampled points are estimated by means of a spatial interpolation usually referred to as inverse distance weighting.

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Why is it important?

Usually, methods adopted to reconstruct population maps lie in the realm of model-dependent inference, i.e., the sampled sites are held fixed (as if they were purposively selected) and the diversity index values at these sites are supposed to be random variables generated from a continuous spatial process (superpopulation). Here, we follow an alternative criterion for attempting the diversity map reconstruction in a design-based framework, i.e., the diversity surface is viewed as constant and uncertainty stems from the probabilistic sampling scheme adopted to select points.

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