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Sampling Techniques for Forest Inventories by Daniel MandallazReview by: Stephen HaslettInternational Statistical Review / Revue Internationale de Statistique, Vol. 76, No. 2 (August2008), pp. 326-327Published by: International Statistical Institute (ISI)Stable URL: http://www.jstor.org/stable/27919645 .
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326 Short Book Reviews
medicine, biomedicine, and highway safety. There is also material on construction of list frames and administrative lists, and good information is provided on currently available computer packages. Paradoxically perhaps, this emphasis seems just as it needs to be to help ensure that the mathematical and statistical aspects of databases and their management are not relegated to the status of 'esoteric curiosity'.
The core problem the book does much to remedy is that the principles it explores are too often perceived as of little importance or use by commercial database designers and managers, and even sometimes by official statisticians. In order to reach this wider audience, the book is a
considerably lighter read than I was expecting (which was not a disappointment) and I think this
impression would be shared by any graduate in statistics, and even by many whose statistical skills were rather below this level.
The book provides a good, sound, verbal introduction and summary, and a useful point of
departure into the more technical side of database quality and record linkage problems. In
summary, it should be a core sourcebook for non-mathematical statisticians in official statistics
agencies, and database designers and managers in government and commerce. It also provides a useful introduction to this important topic, and a comprehensive reference list for further study, for professional statisticians and academics.
Stephen Haslett: [email protected] Institute of Fundamental Sciences - Statistics
Massey University, PO Box 11222, Palmerston North, New Zealand
Sampling Techniques for Forest Inventories Daniel Mandallaz
Chapman and Hall/CRC, 2007, xv + 256 pages, ? 42.99/US$ 79.95, hardcover ISBN: 978-1-58488-976-2
Table of contents
1. Introduction and terminology 2. Sampling finite populations: the essentials
3. Sampling finite populations: advanced topics 4. Forest inventory: one stage sampling schemes
5. Forest inventory: two stage sampling schemes
6. Forest inventory: advanced topics 7. Geostatistics
8. Case study 9. Optimal sampling schemes for forest inventory
10. The Swiss National Forest Inventory 11. Estimating change and growth 12. Transect-sampling
Appendices A. Simulations
B. Conditional expectations and variances
C. Solutions to selected exercises
Readership: Graduates and professionals in forestry and forestry management, applied statisti
cians, survey statisticians, statisticians interested in the statistical theory of sampling for forest
inventory.
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.
International Statistical Review (2008), 76, 2, 300-328 ?2008 The Author. Journal compilation ? 2008 International Statistical Institute
This content downloaded from 194.29.185.145 on Wed, 18 Jun 2014 02:02:09 AMAll use subject to JSTOR Terms and Conditions
Short Book Reviews 327
The general topic is a very broad one. The author has consequently been forced to choose to some extent, and has opted for mathematical rigour over coverage of a wider range of forestry related topics or an extensive collection of case studies to illustrate principles. Applied statistics books in specified application areas often do not indicate how formulae have been derived, so this focus makes the book a welcome and useful addition to the forest inventory literature, even if its rigour may restrict readership. As the author states in the preface, "This exposition is as general and concise as possible". The approach does however have some disadvantages, as it makes practical points more difficult to see, and the need for brevity means that some terms (e.g. stochastic integral, order of approximation, convergence in probability, asymptotic equivalence) remain essentially undefined. To extend readership, explicit definitions of or at least more references to these concepts would have been a useful addition. A certain level of
knowledge of forest inventory is also assumed. The book has a nice treatment of design-based, model-based and model-assisted survey sampling, including the Horvitz-Thompson estimator and more advanced topics such as three-stage element sampling and model-based and model assisted estimation procedures such as GREG (generalised regression estimation). Use is made of anticipated variance for optimal design of forest inventories, and this is illustrated using data from the Swiss National Forest Inventory. Estimation of growth and transect sampling using a
stereological approach is outlined. There is also material on methods of sampling, developed by the author, that involve using locally observed density as a random function. As noted in
Chapter 6, ".. .microscopic models at tree level and macroscopic models at point level are
generally incompatible...", so that while local observed density models hold promise, further research is warranted before they should become common as an alternative to more standard
forestry sampling schemes. The book makes extensive and generally careful use of matrix algebra, although I would have
liked to see matrix properties more clearly stated in some places, e.g. equation (3.24) involves covariance matrix that is itself the product of a covariance matrix and a sample weighting
matrix (since the product can only be symmetric, as required, if both matrices in the product are
diagonal or share (or where eigenvalues are equal can be constructed to share) all eigenvectors). The coverage of small area estimation is brief and limited to situations where all small areas
contain sampled elements. Although the emphasis is on estimating summary statistics (e.g. totals and means), there is also material on analysis of complex survey data and on modelling of relationships between variables. Additional references to all three topics would have been useful. The assumption is made (p54) that all responses (i.e. measurements) are "assumed to be error free". This is a rather strong assumption in forest inventory, where height, volume, and even DBH (diameter at breast height) can sometimes be difficult to measure, and extension of the methods to situations where there is measurement error would possibly be a useful future addition (especially since, even if height and DBH are unbiased, estimated volume need not be). In summary however, this is a very useful, up-to-date reference book on the theory of statistics as it should be applied to forest inventory.
Stephen Haslett: [email protected] Institute of Fundamental Sciences - Statistics
Massey University, PO Box 11222, Palmerston North, New Zealand
International Statistical Review (2008), 76, 2, 300-328 ?2008 The Author. Journal compilation ? 2008 International Statistical Institute
This content downloaded from 194.29.185.145 on Wed, 18 Jun 2014 02:02:09 AMAll use subject to JSTOR Terms and Conditions
