Description

Book Synopsis

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.

Environmental Data Analysis: Methods and Applications

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    £123.50

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    RRP £130.00 – you save £6.50 (5%)

    Order before 4pm today for delivery by Mon 15 Jun 2026.

    A Hardback by Zhihua Zhang

    15 in stock


      View other formats and editions of Environmental Data Analysis: Methods and Applications by Zhihua Zhang

      Publisher: De Gruyter
      Publication Date: 20/02/2023
      ISBN13: 9783111012544, 978-3111012544
      ISBN10:

      Description

      Book Synopsis

      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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