Sampling Techniques for Forest Inventories

✍ Scribed by Daniel Mandallaz

• Publisher: Chapman & Hall/CRC
• Year: 2007
• Tongue: English
• Leaves: 273
• Series: Applied Environmental Statistics
• Edition: 1
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

Cover......Page 1
Semi-Title......Page 2
Series Title......Page 3
Title......Page 4
Copyright......Page 5
Dedication......Page 6
Contents......Page 8
Preface......Page 12
Acknowledgments......Page 16
1. Introduction and terminology......Page 18
2.1 Sampling schemes and inclusion probabilities......Page 20
2.2 The Horvitz-Thompson estimator......Page 21
2.3 Simple random sampling without replacement......Page 25
2.4 Poisson sampling......Page 27
2.5 Unequal probability sampling with replacement......Page 28
2.6 Estimation of ratios......Page 29
2.7 Stratification and post-stratification......Page 33
2.8 Two-stage sampling......Page 36
2.9 Single-stage cluster-sampling......Page 40
2.11 Exercises......Page 44
3.1 Three-stage element sampling......Page 48
3.2 Abstract nonsense and elephants......Page 55
3.3 Model-assisted estimation procedures......Page 57
3.4 Exercises......Page 67
4.1 Generalities......Page 70
4.2 One-phase one-stage simple random sampling scheme......Page 72
4.3 One-phase one-stage cluster random sampling scheme......Page 82
4.4 One-phase two-stage simple random sampling......Page 86
4.5 One-phase two-stage cluster random sampling......Page 90
4.6 Exercises......Page 92
5.1 Two-phase one-stage simple random sampling......Page 96
5.2 Two-phase two-stage simple random sampling......Page 98
5.3 Two-phase one-stage cluster random sampling......Page 103
5.4 Two-phase two-stage cluster random sampling......Page 104
5.5 Internal linear models in two-phase sampling......Page 106
5.6 Remarks on systematic sampling......Page 109
5.7 Exercises......Page 111
6.1 The model-dependent approach......Page 114
6.2 Model-assisted approach......Page 126
6.3 Small-area estimation......Page 136
6.4 Modeling relationships......Page 138
6.5 Exercises......Page 151
7.1 Variograms......Page 152
7.2 Ordinary Kriging......Page 155
7.3 Kriging with sampling error......Page 158
7.4 Double Kriging for two-phase sampling schemes......Page 159
7.5 Exercises......Page 162
8. Case Study......Page 164
9.1 Preliminaries......Page 172
9.2 Anticipated variance under the local Poisson model......Page 173
9.3 Optimal one-phase one-stage sampling schemes......Page 176
9.4 Discrete approximations of PPS......Page 178
9.5 Optimal one-phase two-stage sampling schemes......Page 181
9.6 Optimal two-phase sampling schemes......Page 184
9.7 Exercises......Page 191
10. The Swiss National Forest Inventory......Page 194
11. Estimating change and growth......Page 202
11.1 Exercises......Page 211
12.1 Generalities......Page 212
12.2 IUR transect-sampling......Page 213
12.3 PPL transect-sampling......Page 218
12.4 Transects with fixed length......Page 222
12.5 Buffon’s needle problem......Page 223
12.6 Exercises......Page 226
back-matter......Page 227
A.2 Simple random sampling......Page 228
A.4 Two-phase simple systematic sampling......Page 230
A.5 Figures......Page 232
B. Conditional expectations and variances......Page 238
Problem 2.3......Page 242
Problem 2.4......Page 243
Problem 2.5......Page 244
Problem 2.9......Page 245
Problem 3.2......Page 246
Problem 4.2......Page 247
Problem 4.4......Page 248
Problem 4.6......Page 249
Problem 4.8......Page 250
C.5 Chapter 6......Page 251
Problem 6.1......Page 252
Problem 7.1......Page 253
Problem 9.1......Page 254
Problem 9.3......Page 257
Problem 11.1......Page 260
Problem12.2......Page 261
Bibliography......Page 264
Index......Page 270