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Forest Analytics with R: An Introduction PDF

355 Pages·2011·2.95 MB·English
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Use R! Series Editors Robert Gentleman Kurt Hornik Giovanni Parmigiani For a complete list of titles published in this series, go to www.springer.com/series/6991 Use R! Albert: Bayesian Computation with R Bivand/Pebesma/Go´mez-Rubio: Applied Spatial Data Analysis with R Claude:Morphometrics with R Cook/Swayne: Interactive andDynamic Graphics for Data Analysis: With R and GGobi Hahne/Huber/Gentleman/Falcon:Bioconductor Case Studies Nason: Wavelet Methods in Statistics with R Paradis: Analysis of Phylogenetics and Evolution with R Peng/Dominici: Statistical Methods for Environmental Epidemiology with R: A Case Study in Air Pollution and Health Pfaff: Analysis ofIntegrated and Cointegrated Time Series with R, 2nd edition Sarkar: Lattice: MultivariateData Visualization with R Spector:Data Manipulation with R Andrew P. Robinson • Jeff D. Hamann Forest Analytics with R An Introduction 1 C Andrew P. Robinson Jeff D. Hamann Dept. Mathematics and Statistics Forest Informatics, Inc. University of Melbourne PO Box 1421 Parkville 3010 VIC 97339-1421 Corvallis Oregon Australia USA [email protected] [email protected] Series Editors: Robert Gentleman Kurt Hornik Program in Computational Biology Department of Statistik and Mathematik Division of Public Health Sciences Wirtschaftsuniversität Wien Augasse 2-6 Fred Hutchinson Cancer Research Center A-1090 Wien 1100 Fairview Avenue, N. M2-B876 Austria Seattle,Washington 98109 USA Giovanni Parmigiani The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins University 550 North Broadway Baltimore, MD 21205-2011 USA ISBN 978-1-4419-7761-8 e-ISBN 978-1-4419-7762-5 DOI 10.1007/978-1-4419-7762-5 Springer New York Dordrecht Heidelberg London © Springer Science+Business Media, LLC 2011 All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher (Springer Science+Business Media, LLC, 233 Spring Street, New York, NY 10013, USA), except for brief excerpts in connection with reviews or scholarly analysis. Use in connec- tion with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com) This book is dedicated to Grace, Felix, and M’Liss, (and Henry and Yohan) with grateful thanks for inspiration and patience. Preface R is an open-source and free software environment for statistical computing and graphics. R compiles and runs on a wide variety of UNIX platforms (e.g., GNU/Linux and FreeBSD), Windows, and Mac OSX. Since the late 1990s,Rhasbeendevelopedbyhundredsofcontributorsandnewcapabilities are added each month. The software is gaining popularity because: 1) it is platform independent, 2) it is free, and 3) the source code is freely available and can be inspected to determine exactly what R is doing. Our objectives for this book are to 1) demonstrate the use of R as a solid platform upon which forestry analysts can develop repeatable and clearly documentedmethods;2)provideguidanceinthebroadareaofdatahandling and analysis for forest and natural resources analytics; and 3) to use R to solve problems we face each day as forest data analysts. This book is intended for two broad audiences: students, researchers, and softwarepeoplewhocommonlyhandleforestrydata;andforestrypractition- erswhoneedtodevelopactionablesolutionstocommonoperational,tactical, and strategic problems. We often mention better and more complete treat- ments of specific subject material for further reference (e.g., forest sampling, spatial statistics, or operations research). Wehopethatthisbookwillserveasafieldmanualforpracticingforestan- alysts,managers,andresearchers.Wehopethatitwillbedog-eared,defaced, coffee/tea-stained, and sticky-noted to near destruction. We hope the reader will engage in the exercises, scrutinize its contents, forgive our weaknesses, possibly and carefully absorb suggestions, and constructively criticize. Acknowledgments This book would not have been possible without the patient and generous assistance of many people. We first thank all the authors of the literature we cite, who were willing to publish their data as part of their research. vii viii Preface Thesedataareoftenouronlylinkbetweenrepeatableresearchandanecdotal opinion. WethankValerieLeMayandTimothyGregoirefortheirkindcontribution of tree measurement data and for their encouragement and leadership in the field. We thank Boris Zeide for his generous contribution of the von Guttenberg data. We thank Don Wallace and Bruce Alber for supplying an interesting dataset to demonstrate the data management, plotting, and file functions in Chapter 2. We thank the Oregon State University College of Forestry Research Forests web site for posting a publicly available forest inventory for Chapters 2 and 4. Without those data, many of the examples and topics in this book would have to have been performed using simulated data and frankly would have been much less interesting. We thank Martin Ritchieforprovidingdata,funding,andsnippetsofcodeoncelostandfound againduringthedevelopmentoftherconiferspackage,usedinChapter8.We thankDavidHannfor,yearsago,providinganoriginalcopyofthemanuscript that we used to generate the shared library example (chambers-1980.so) in Chapter 8 (Chambers, 1980). We have received considerable constructive criticism via the review pro- cess, only some of which we can source. We especially thank John Kershaw for generous and detailed comments on Chapter 3, Jeff Gove for his support and useful commentary on Chapter 5, and David Ratkowsky and Graham Hepworth for their thoughtful and thought-provoking comments on Chap- ters 6 and 7, respectively. Numerous other useful comments were made by anonymous reviewers. The collection of review comments improved the book immeasurably. WethankRCore,theRcommunity,andallthepackageauthorsandmain- tainerswehavecometorelyupon.Specifically,wethankthefollowingpeople, in no particular order: David B. Dahl (xtable); Lopaka Lee (R-GLPK); An- drew Makhorin (GLPK); Roger Bivand (maptools); Deepayan Sarkar (lat- tice); Hadley Wickham (ggplot2); Brian Ripley (MASS, class, boot); Jose PinheiroandDouglasBates(nlme);FrankHarrell(Hmisc);AlvaroNovoand JoeSchafer(norm);GregWarnes(gmodelsetal.);ReinhardFurrer,Douglas Nychka, and Stephen Sain (fields); Thomas Lumley (survey); and Nicholas J. Lewin-Koh and Roger Bivand (maptools). We thank John Kimmel, our managing editor at Springer, for showing in- crediblepatienceandHalHenglein,ourcopyeditor,forkeepingusconsistent. ARwishestothankMarkBurgmanforprovidingspacetofinishthisbook within a packed ACERA calendar, and for his substantial support and guid- ance. AR also wishes to thank Geoff Wood, Brian Turner, Alan Ek, and Albert Stage for their kindness and intellectual support along the way. JH wishes to thank Martin Ritchie, David Marshall, Kevin Boston, and John Sessions for their support along the way. Finally, we wish to thank our wives, children, and friends for cheerful perseverance and support in the face of a task that seemed at times like a little slice of Sisyphus. Preface ix Melbourne and Corvallis Andrew Robinson August 16, 2010 Jeff D. Hamann

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Forest Analytics with R combines practical, down-to-earth forestry data analysis and solutions to real forest management challenges with state-of-the-art statistical and data-handling functionality. The authors adopt a problem-driven approach, in which statistical and mathematical tools are introduc
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