Springer celebrates 175 years of publishing excellence! Join us >>

Use R!

Forest Analytics with R

An Introduction

Authors: Robinson, Andrew P., Hamann, Jeff D.

  • Uses  real datasets that provide detailed and realistic examples of forestry data handling and analysis
  • Offers a problem-driven approach in which statistical and mathematical tools are introduced in the context of the forestry problem that they can help to resolve
  • Combines practical, down-to-earth forestry data analysis solutions with state-of-the-art statistical functionality
see more benefits

Buy this book

eBook $49.99
price for USA (gross)
  • ISBN 978-1-4419-7762-5
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $64.95
price for USA
  • ISBN 978-1-4419-7761-8
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Rent the ebook  
  • Rental duration: 1 or 6 month
  • low-cost access
  • online reader with highlighting and note-making option
  • can be used across all devices
About this Textbook

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 introduced in the context of the forestry problem that they can help to resolve. All the tools are introduced in the context of real forestry datasets, which provide compelling examples of practical applications. The modeling challenges covered within the book include imputation and interpolation for spatial data, fitting probability density functions to tree measurement data using maximum likelihood, fitting allometric functions using both linear and non-linear least-squares regression, and fitting growth models using both linear and non-linear mixed-effects modeling. The coverage also includes deploying and using forest growth models written in compiled languages, analysis of natural resources and forestry inventory data, and forest estate planning and optimization using linear programming. The book would be ideal for a one-semester class in forest biometrics or applied statistics for natural resources management. The text assumes no programming background, some introductory statistics, and very basic applied mathematics. Andrew Robinson has been associate professor of forest mensuration and forest biometrics at the University of Idaho, and is currently senior lecturer in applied statistics at the University of Melbourne. He received his PhD in forestry from the University of Minnesota. Robinson is author of the popular and freely-available "icebreakeR" document. Jeff Hamann has been a software developer, forester, and financial analyst. He is currently a consultant specializing in forestry, operations research, and geographic information sciences. He received his PhD in forestry from Oregon State University. Both authors have presented numerous R workshops to forestry professionals and scientists, and others.

About the authors

Andrew Robinson has been associate professor of forest mensuration and forest biometrics at the University of Idaho, and is currently senior lecturer in applied statistics at the University of Melbourne. He received his PhD in forestry from the University of Minnesota. Robinson is author of the popular and freely-available "icebreakeR" document.  Jeff Hamann has been a software developer, forester, and financial analyst. He is currently a consultant specializing in forestry, operations research, and geographic information sciences. He received his PhD in forestry from Oregon State University.  Both authors have presented numerous R workshops to forestry professionals and scientists, and others.

Reviews

From the reviews:

“The material presented in this text is more than sufficient for a dedicated module of an applied statistics course … . The authors develop, and demonstrate, solutions to common forestry data handling and analysis challenges … . Whilst much of the text may be regarded as standard for the topic, the last chapter addresses an area harvest strategy which is well worth reading on its own … . The text is well written, easy to read and I recommend it to anyone interested in biometrics.” (Carl M. O’Brien, International Statistical Review, Vol. 80 (1), 2012)


Table of contents (9 chapters)

  • Introduction

    Robinson, Andrew P. (et al.)

    Pages 3-17

  • Forest Data Management

    Robinson, Andrew P. (et al.)

    Pages 19-72

  • Data Analysis for Common Inventory Methods

    Robinson, Andrew P. (et al.)

    Pages 75-115

  • Imputation and Interpolation

    Robinson, Andrew P. (et al.)

    Pages 117-151

  • Fitting Dimensional Distributions

    Robinson, Andrew P. (et al.)

    Pages 155-173

Buy this book

eBook $49.99
price for USA (gross)
  • ISBN 978-1-4419-7762-5
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $64.95
price for USA
  • ISBN 978-1-4419-7761-8
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Rent the ebook  
  • Rental duration: 1 or 6 month
  • low-cost access
  • online reader with highlighting and note-making option
  • can be used across all devices
Loading...

Recommended for you

Loading...

Bibliographic Information

Bibliographic Information
Book Title
Forest Analytics with R
Book Subtitle
An Introduction
Authors
Series Title
Use R!
Copyright
2011
Publisher
Springer-Verlag New York
Copyright Holder
Springer Science+Business Media, LLC
eBook ISBN
978-1-4419-7762-5
DOI
10.1007/978-1-4419-7762-5
Softcover ISBN
978-1-4419-7761-8
Series ISSN
2197-5736
Edition Number
1
Number of Pages
XIV, 354
Topics