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
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Zhihua Zhang, Beijing Normal University, Beijing, China.
Zhihua Zhang is a Full Professor in Beijing Normal University, China. His research interests are Global Environmental Change, Time Series Analysis, Carbon Emissions, etc. Recently, he has published more than 50 first-authored papers and two first-authored monographs. Zhihua Zhang is an Editor-in-Chief of American Journal of Climate Change, an associate editor of Arabian Journal of Geosciences (Springer), an Associate Editor of EURASIP Journal on Advances in Signal Processing (Springer), an Editorial Board Member of International Journal of Global Warming, and an Editorial Board Member of Journal of Cleaner Production (Elsevier).
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