Sampling Techniques for Forest Inventories

ISBN-13: 9780367388430 / Angielski / Miękka / 2019 / 272 str.

Daniel Mandallaz

Opis

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.

Spis treści

preface
Introduction and terminology
Sampling finite populations: the essentials
Sampling schemes and inclusion probabilities
The Horvitz–Thompson estimator
Simple random sampling without replacement
Poisson sampling
Unequal probability sampling with replacement
Estimation of ratios
Stratification and post-stratification
Two-stage sampling
Single-stage cluster-sampling
Systematic sampling
Exercises
Sampling finite populations: advanced topics
Three-stage element sampling
Abstract nonsense and elephants
Model-assisted estimation procedures
Exercises
Forest Inventory: one-phase sampling schemes
Generalities
One-phase one-stage simple random sampling scheme
One-phase one-stage cluster random sampling scheme
One-phase two-stage simple random sampling
One-phase two-stage cluster random sampling
Exercises
Forest Inventory: two-phase sampling schemes
Two-phase one-stage simple random sampling
Two-phase two-stage simple random sampling
Two-phase one-stage cluster random sampling
Two-phase two-stage cluster random sampling
Internal linear models in two-phase sampling
Remarks on systematic sampling
Exercises
Forest Inventory: advanced topics
The model-dependent approach
Model-assisted approach
Small-area estimation
Modeling relationships
Exercises
Geostatistics
Variograms
Ordinary Kriging
Kriging with sampling error
Double Kriging for two-phase sampling schemes
Exercises
CASE STUDY
Optimal sampling schemes for forest inventory
Preliminaries
Anticipated variance under the local Poisson model
Optimal one-phase one-stage sampling schemes
Discrete approximations of PPS
Optimal one-phase two-stage sampling schemes
Optimal two-phase sampling schemes
Exercises
The Swiss National Forest Inventory
Estimating change and growth
Exercises
Transect Sampling
Generalities
IUR transect sampling
PPL transect sampling
Transects with fixed length
Buffon’s needle problem
Exercises
APPENDIX A: Simulations
Preliminaries
Simple random sampling
Systematic cluster sampling
Two-phase simple systematic sampling
Figures
APPENDIX B: Conditional expectations and variances
APPENDIX C: Solutions to selected exercises
Bibliography
INDEX

O autorze

Mandallaz, Daniel