Sound forest management planning requires cost-efficient approaches
to optimally utilize given resources. Emphasizing the mathematical
and statistical features of forest sampling to assess classical
dendrometrical quantities, Sampling Techniques for Forest
Inventories presents the statistical concepts and tools needed to
conduct a modern forest inventory. The book first examines
design-based survey sampling and inference for finite populations,
covering inclusion probabilities and the Horvitz-Thompson
estimator, followed by more advanced topics, including three-stage
element sampling and the model-assisted estimation procedure. The
author then develops the infinite population model/Monte Carlo
approach for both simple and complex sampling schemes. He also uses
a case study to reveal a variety of estimation procedures, relies
on anticipated variance to tackle optimal design for forest
inventories, and validates the resulting optimal schemes with data
from the Swiss National Forest Inventory. The last chapters outline
facts pertaining to the estimation of growth and introduce transect
sampling based on the stereological approach. Containing many
recent developments available for the first time in book form, this
concise and up-to-date work provides the necessary theoretical and
practical foundation to analyze and design forest inventories.
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