Environmental Data Analysis

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.

• Provides modern quantitative tools and techniques designed specifically to meet the needs of environmental sciences.
• Explains carefully various data analysis procedures and techniques.
• Includes a new chapter on networks.

Zhihua Zhang is a Taishan Distinguished Professor at Shandong University, China. His research interests are Big Data Mining, Climate Change Mechanisms, Environmental Evolution and Sustainability. He has published 6 first-authored books in Elsevier/Springer/DeGruyter and published more than 60 first-authored articles, some of which were reported by New Scientist (UK), China Science Daily, and China Social Science Daily. Prof. Zhang is serving as the Editor-in-Chief of Int J Big Data Mining for Global Warming (World Scientific), Topical Chief Editor of Arab J Geosci (Springer), Associate Editor of Environ Dev Sustain (Springer), Associate Editor of EURASIP J Adv Signal Process (Springer), Associate Editor of Int J Climate Change Strat & Manag (Emerald), etc.