
- 400 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
About this book
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.
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Information
Table of contents
- Title Page
- Copyright
- Contents
- 1âTime series analysis
- 2âChaos and dynamical systems
- 3âApproximation
- 4âInterpolation
- 5âPatterns
- 6âEstimates
- 7âOptimization
- 8âData envelopment analysis
- 9âRisk assessments
- 10âLife cycle assessments
- 11âNetworks
- Subject Index