Statistical Methods and Applications in Forestry and Environmental Sciences

  • Girish Chandra
  • Raman Nautiyal
  • Hukum Chandra

Part of the Forum for Interdisciplinary Mathematics book series (FFIM)

Table of contents

  1. Front Matter
    Pages i-xii
  2. Anoop Singh Chauhan, Girish Chandra, Y. P. Singh
    Pages 1-11
  3. S. B. Lal, Anu Sharma, K. K. Chaturvedi, M. S. Farooqi, Anil Rai
    Pages 35-45
  4. Raosaheb V. Latpate
    Pages 47-55
  5. Ehsan Zamanzade, Xinlei Wang
    Pages 57-77
  6. Zhiqing Xu, Balgobin Nandram, Binod Manandhar
    Pages 79-103
  7. S. Suresh Ramanan, T. K. Kunhamu, Deskyong Namgyal, S. K. Gupta
    Pages 151-160
  8. Manish Sharma, Banti Kumar, Vishal Mahajan, M. I. J. Bhat
    Pages 181-191
  9. Krishan Lal, Upendra Kumar Pradhan, V. K. Gupta
    Pages 193-212
  10. Anoop Chaturvedi, Ashutosh Kumar Dubey
    Pages 231-240
  11. Chiara Bocci, Emanuela Dreassi, Alessandra Petrucci, Emilia Rocco
    Pages 241-253
  12. M. Sivaram, K. K. Ramachandran, E. A. Jayson, P. V. Nair
    Pages 267-281
  13. Back Matter
    Pages 283-288

About this book


This book presents recent developments in statistical methodologies with particular relevance to applications in forestry and environmental sciences. It discusses important methodologies like ranked set sampling, adaptive cluster sampling, small area estimation, calibration approach-based estimators, design of experiments, multivariate techniques, Internet of Things, and ridge regression methods. It also covers the history of the implementation of statistical techniques in Indian forestry and the National Forest Inventory of India.

The book is a valuable resource for applied statisticians, students, researchers, and practitioners in the forestry and environment sector. It includes real-world examples and case studies to help readers apply the techniques discussed. It also motivates academicians and researchers to use new technologies in the areas of forestry and environmental sciences with the help of software like R, MATLAB, Statistica, and Mathematica.


Indian Forestry Nonparametric Estimation Bayesian Inference Stratified Random Sampling Joint Calibration Estimator Fusing Classical Theories Statistical Multivariate Methods Cluster Analysis

Editors and affiliations

  • Girish Chandra
    • 1
  • Raman Nautiyal
    • 2
  • Hukum Chandra
    • 3
  1. 1.Indian Council of Forestry Research and EducationDehradunIndia
  2. 2.Indian Council of Forestry Research and EducationDehradunIndia
  3. 3.Indian Agricultural Statistics Research InstituteNew DelhiIndia

Bibliographic information

  • DOI
  • Copyright Information Springer Nature Singapore Pte Ltd. 2020
  • Publisher Name Springer, Singapore
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-981-15-1475-3
  • Online ISBN 978-981-15-1476-0
  • Series Print ISSN 2364-6748
  • Series Online ISSN 2364-6756
  • Buy this book on publisher's site
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