Gregoire / Valentine Sampling Strategies for Natural Resources and the Environment

Erscheinungsjahr 2007
ISBN: 978-0-203-49888-0
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 496 Seiten

Reihe: Chapman & Hall/CRC Applied Environmental Statistics

Written by renowned experts in the field, Sampling Strategies for Natural Resources and the Environment covers the sampling techniques used in ecology, forestry, environmental science, and natural resources. The book presents methods to estimate aggregate characteristics on a per unit area basis as well as on an elemental basis. In addition to common sampling designs such as simple random sampling and list sampling, the authors explore more specialized designs for sampling vegetation, including randomized branch sampling and 3P sampling.

One of the book's unique features is the emphasis on areal sampling designs, including plot/quadrat sampling, Bitterlich sampling, line intersect sampling, and several lesser known designs. The book also provides comprehensive solutions to the problem of edge effect. Another distinguishing aspect is the inclusion of sampling designs for continuums, focusing on the methods of Monte Carlo integration.

By presenting a conceptual understanding of each sampling design and estimation procedure as well as mathematical derivations and proofs in the chapter appendices, this text promotes a deep understanding of the underpinnings of sampling theory, estimation, and inference. Moreover, it will help you reliably sample natural populations and continuums.

Zielgruppe

Students and professionals in biology, biometrics, ecology, environmental science, forestry, natural resources, and statistics.

Autoren/Hrsg.

Gregoire, Timothy G.

Valentine, Harry T.

Fachgebiete

• Naturwissenschaften Chemie Chemie Allgemein
• Naturwissenschaften Biowissenschaften Biowissenschaften Biowissenschaften, Biologie: Sachbuch, Naturführer
• Geowissenschaften Umweltwissenschaften Umweltschutz, Umwelterhaltung
• Mathematik | Informatik Mathematik Stochastik

Inhaltsverzeichnis

PREFACE

INTRODUCTION
The need for sampling strategies

A medley of sampling scenarios
Probability sample
Inference

Population descriptive parameters
Historical note

Terms to remember

Appendix

SAMPLING DISTRIBUTION OF AN ESTIMATOR

Distribution of values

Estimation

Interval estimation

The role of simulated sampling

Other considerations

Terms to remember

Exercises
Appendix

SAMPLING DESIGNS FOR DISCRETE POPULATIONS

Introduction

Equal probability designs
Unequal probability designs
Terms to remember

Exercises

Appendix

SAMPLING DESIGNS FOR CONTINUOUS POPULATIONS

Introduction

Crude Monte Carlo
Importance sampling

Control variate estimation

Sampling in two or three dimensions

General notation

Terms to remember

Exercises and projects

Appendix

STRATIFIED SAMPLING DESIGNS

Introduction

Rationale for stratified sampling

Estimation with stratified sampling
Sample allocation among strata
Incorrect assignment of population elements into strata

Double sampling for stratification

Poststratification
Stratified sampling of a continuous population
Terms to Remember

Exercises

Appendix

USING AUXILIARY INFORMATION TO IMPROVE ESTIMATION

Generalized ratio estimator

Bias of the generalized ratio estimator

Variance of the generalized ratio estimator

Estimated variance of the generalized ratio estimator

Confidence interval estimation

Ratio estimation with systematic sampling design

Generalized ratio estimation with stratified sampling
Generalized regression estimator
Double sampling with ratio and regression estimation
Terms to Remember

Exercises

Appendix

SAMPLING WITH FIXED AREA PLOTS

Introduction

Notation
Sampling protocol

Estimation
Edge effect
Plot size and shape

Estimating change

Terms to remember
Exercises

Appendix

BITTERLICH SAMPLING

Introduction

Fundamental concepts
Estimation following Bitterlich sampling
Edge effect

Double sampling
Sampling to estimate change in stock
Terms to remember
Exercises

LINE INTERSECT SAMPLING

Introduction

LIS with straight-line transects
Unit area estimators

Estimation with an auxiliary variate

Estimating the mean attribute

Nesting transects of different lengths

Dealing with edge effect in LIS
Transects with multiple segments
Parallel transects of uneven length
Terms to remember

Exercises

Appendix

A MONTE CARLO INTEGRATION APPROACH TO AREAL SAMPLING

Areal sampling
Plot sampling

Bitterlich sampling

Point relascope sampling

Line intersect sampling

Perpendicular distance sampling

Edge correction

Redux: Continuous versus discrete

Terms to Remember

Exercises

Appendix

MISCELLANEOUS METHODS
Introduction

Point relascope sampling

Horizontal line sampling

Transect relascope sampling

Ranked set sampling
Adaptive cluster sampling

3P sampling

Terms to Remember
Exercises

Appendix

TWO-STAGE SAMPLING

Customary two-stage sampling
General two-stage sampling

Three-stage sampling

Terms to Remember

RANDOMIZED BRANCH SAMPLING
Terminology

Path selection
Estimation

Selection probabilities

Tools and tricks of the trade

Subsampling a path
Terms to remember

Exercises and projects

Appendix

SAMPLING WITH PARTIAL REPLACEMENT

Introduction

Estimation with partially replaced sampling units
Estimation of change
SPR with stratification

SPR for three occasions

Concluding remarks

Terms to remember

Appendix

BIBLIOGRAPHY

INDEX