Environmental Data Analysis

Methods and Applications

Zhihua Zhang

• Publisher: De Gruyter
• Year: 2016
• eBook ISBN: 9783110424980
• Edition: 1
• Topic: Matematica
• Subtopic: Matematica applicata

Most environmental data involve a large degree of complexity and uncertainty. Environmental Data Analysis is created to provide modern quantitative tools and techniques designed specifically to meet the needs of environmental sciences and related fields. This book has an impressive coverage of the scope. Main techniques described in this book are models for linear and nonlinear environmental systems, statistical & numerical methods, data envelopment analysis, risk assessments and life cycle assessments. These state-of-the-art techniques have attracted significant attention over the past decades in environmental monitoring, modeling and decision making. Environmental Data Analysis explains carefully various data analysis procedures and techniques in a clear, concise, and straightforward language and is written in a self-contained way that is accessible to researchers and advanced students in science and engineering. This is an excellent reference for scientists and engineers who wish to analyze, interpret and model data from various sources, and is also an ideal graduate-level textbook for courses in environmental sciences and related fields.

Contents:
Preface
Time series analysis
Chaos and dynamical systems
Approximation
Interpolation
Statistical methods
Numerical methods
Optimization
Data envelopment analysis
Risk assessments
Life cycle assessments
Index

1Time series analysis

The main objectives of environmental time series analysis are to describe environmental change, explain the mechanisms underlying these changes, predict future environmental change under given perturbation and avoid undesired environmental impacts. In environmental time series analysis, autoregressive moving average (ARMA)models and state-space models are two most useful tools to discover the dynamical characteristics of environmental change through fitting them to environmental time series with complex dynamics.

1.1Stationary time series

A time series is a set of observations {xt},whereeach t is a specific time. Time series are encountered in a variety of fields such as temperatu...

Table of contents

• Cover
• Title
• Copyright
• Preface
• Contents
• 1 Time series analysis
• 2 Chaos and dynamical systems
• 3 Approximation
• 4 Interpolation
• 5 Statistical methods
• 6 Numerical methods
• 7 Optimization
• 8 Data envelopment analysis
• 9 Risk assessments
• 10 Life cycle assessments
• Index