Environmental data analysis : methods and applications / Zhihua Zhang.

Format:

Book

Author/Creator:

Zhang, Zhihua, author.

Language:

English

Subjects (All):

Environmental sciences--Data processing.

Environmental sciences.

Environmental sciences--Mathematics.

Physical Description:

1 online resource : illustrations

Edition:

2nd Edition

Place of Publication:

Berlin ; Boston : De Gruyter, [2023]

Summary:

With the dramatic development of air-space-ground-sea environmental monitoring networks and large-scale high-resolution Earth simulators, Environmental science is facing opportunities and challenges of big data. Environmental Data Analysis focuses on state-of-the-art models and methods for big environmental data and demonstrates their applications through various case studies in the real world. It covers the comprehensive range of topics in data analysis in space, time and spectral domains, including linear and nonlinear environmental systems, feature extraction models, data envelopment analysis, risk assessments, and life cycle assessments. The 2nd Edition adds emerging network models, including neural networks, complex networks, downscaling analysis and streaming data on network. This book is a concise and self-contained work with enormous amount of information. It is a must-read for environmental scientists who struggle to conduct big data mining and data scientists who try to find the way into environmental science.

Contents:

Frontmatter

Preface of the 2nd edition

Preface

Contents

1 Time series analysis

2 Chaos and dynamical systems

3 Approximation

4 Interpolation

5 Patterns

6 Estimates

7 Optimization

8 Data envelopment analysis

9 Risk assessments

10 Life cycle assessments

11 Networks

Index

Notes:

Includes bibliographical references and index.

Description based on online resource; title from PDF title page (publisher's Web site, viewed 28. Feb 2023)

Description based on publisher supplied metadata and other sources.

Other Format:

Online version: Zhang, Zhihua, 1979- Environmental Data Analysis.

ISBN:

9783111012681

9783111012919

OCLC:

1371573598