Author Description
Forest Biometrics presents the methods of mathematical statistics and biometrics that are significant to forestry. This book explores other fields related to forestry, which are explained with the help of a large number of practical examples. Organized into 25 chapters, this book starts with an overview of the variety of data that play a significant role in forest management, including the age of trees, the damage caused by storms, the fluctuation of timber prices, bark beetle infestation, and timber volume. This text then examines the factors that are responsible for a random distribution of the values in biological experimentation. Other chapters consider the important advantages of sample surveys compared to complete enumerations, include cheaper samples, wider applicability, quick results, and greater accuracy. The final chapter deals with the factors to be considered in determining the best time for harvesting of timber. This book is a valuable resource for students, research project leaders, and practical workers.
Menrva's Summary
THE THESIS
This text investigates the application of mathematical statistics and biometrics to the management and analysis of forestry data. Michail Prodan, an expert in forest mensuration, synthesizes complex biological and economic variables into a structured framework for forest management. The book utilizes a combination of theoretical statistical principles and practical forestry examples to provide a comprehensive methodology for researchers and practitioners.
THE SCOPE MAP
What You Will Find
- Statistical analysis of tree age, timber volume, and storm damage
- Methodologies for sample surveys versus complete enumerations
- Economic variables including timber price fluctuations
- Biological factors such as bark beetle infestation
- Decision-making frameworks for optimal timber harvesting
Scope Limits
- Does not cover modern digital remote sensing or satellite-based forest monitoring
- Focuses primarily on traditional biometric and statistical methods rather than contemporary machine learning approaches
THE AUTHORITY PERSPECTIVE
Experts recognize this work as a foundational text for understanding the statistical underpinnings of forest management. Readers frequently note the academic density of the prose, which serves as a rigorous reference for students and research professionals in the field.
Page Count:
447
Publication Date:
1968-01-01
Publisher:
Pergamon
ISBN-10:
0080033164
ISBN-13:
9780080033167
Science
Mathematics
Forestry
Biometrics
Statistics