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Academic & Professional Books  Reference  Data Analysis & Modelling  Data Analysis & Statistics

Sampling Techniques for Forest Inventories

By: Daniel Mandallaz(Author)
272 pages, 27 b/w illustrations
Publisher: CRC Press
Sampling Techniques for Forest Inventories
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  • Sampling Techniques for Forest Inventories ISBN: 9780367388430 Paperback Sep 2019 Not in stock: Usually dispatched within 1 week
  • Sampling Techniques for Forest Inventories ISBN: 9781584889762 Hardback Oct 2007 Not in stock: Usually dispatched within 1 week
Selected version: £110.00
About this book Contents Customer reviews Related titles

About this book

Paperback reprint of a 2007 book.

Sound forest management planning requires cost-efficient approaches to optimally utilize the 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.



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
Sampling finite populations: advanced topics
      Three-stage element sampling
      Abstract nonsense and elephants
      Model-assisted estimation procedures
Forest Inventory: one-phase sampling schemes
      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
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
Forest Inventory: advanced topics
      The model-dependent approach
      Model-assisted approach
      Small-area estimation
      Modeling relationships
      Ordinary Kriging
      Kriging with sampling error
      Double Kriging for two-phase sampling schemes

Optimal sampling schemes for forest inventory
      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
The Swiss National Forest Inventory
      Estimating change and growth
Transect Sampling
      IUR transect sampling
      PPL transect sampling
      Transects with fixed length
      Buffon’s needle problem

APPENDIX A: Simulations
      Simple random sampling
      Systematic cluster sampling
      Two-phase simple systematic sampling
APPENDIX B: Conditional expectations and variances
APPENDIX C: Solutions to selected exercises


Customer Reviews

By: Daniel Mandallaz(Author)
272 pages, 27 b/w illustrations
Publisher: CRC Press
Media reviews

"[...] the text is an excellent addition to the forest and natural resource inventory literature, and nicely compliments classic and contemporary texts focused broadly on applied concepts and tools but lacking in rigorous statistical treatment. [...] this text is an important contribution to the literature, as it provides a unique, mathematically rigorous tour of classical and modern topics on forest sampling theory. Of particular importance is the text's emphasis on model-based methods, which are becoming increasingly important within forest and natural resources inventory."
The American Statistician, Vol. 63, No. 3, August 2009, and JASA, Winter 2008

:[...] In this field, the author is a leading expert who presents the modern state of the art, in particular his own work of the last two decades. [...] a valuable, up-to-date reference book for the theoretical aspects of forest inventories and sampling [...] ."
– Dietrich Stoyan, Biometrical Journal, Vol. 51, 2009

"This compact little volume is packed with important and useful ideas."
– Donald E. Myers, University of Arizona, Technometrics, May 2009

"This is an important reference for those wanting to understand the theory of sampling in forest inventory, and also for those with graduate- or postgraduate-level skills in statistics who apply these techniques in the forestry industry. Despite its length, the book provides reasonably thorough coverage of the theory of statistics applied to forest inventories. [...] a very useful, up-to-date reference book on the theory of statistics as it should be applied to forest inventory."
International Statistical Review, 2008

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