What is it about?
The estimation of individual values (marks) in a finite population of units (e.g., trees) scattered onto a survey region is considered under 3P sampling. For each unit, the mark is estimated by means of an inverse distance weighting interpolator. Conditions ensuring the design‐based consistency of maps are considered under 3P sampling.
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Why is it important?
Because 3P sampling involves the prediction of marks for each unit in the population, prediction errors rather than marks can be interpolated. Then, marks are estimated by the predictions plus the interpolated errors. If predictions are good, prediction errors are more smoothed than raw marks so that the procedure is likely to better meet consistency requirements.
Perspectives
The purpose of this paper is to provide theoretical and empirical evidence on the effectiveness of the interpolation based on prediction errors to prove that the proposed strategy is a tool of general validity for mapping forest stands.
Piermaria Corona
CREA Research Centre for Forestry and Wood
Read the Original
This page is a summary of: Design‐based mapping of tree attributes by 3P sampling, Biometrical Journal, June 2020, Wiley,
DOI: 10.1002/bimj.201900377.
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