Containing many recent developments available for the first time in book form, this concise and up-to-date work presents the statistical concepts and tools needed to conduct a modern forest inventory. It develops the Monte Carlo approach for both simple and complex sampling schemes and explores design-based, model-assisted, and model-dependent inference, including geostatistics and Kriging procedures. The book also explains the design of optimal sampling schemes based on anticipated variance, introduces the g-weight technique for variance estimation, and presentsthe stereological approach to transect sampling. In addition, it includes numerous case studies, simulations, and instructive problems with solutions.
