Mandallaz Sampling Techniques for Forest Inventories

Erscheinungsjahr 2007
ISBN: 978-1-58488-977-9
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 272 Seiten

Reihe: Chapman & Hall/CRC Applied Environmental Statistics

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.

Zielgruppe

Biostatisticians, statisticians, ecologists, environmental scientists, governmental agencies and NGOs involved in forest inventories, and students of forest science.

Autoren/Hrsg.

Mandallaz, Daniel

Fachgebiete

• Naturwissenschaften Agrarwissenschaften Agrarwissenschaften

Inhaltsverzeichnis

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