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Numerical Methods in Environmental Data Analysis de Moses Eterigho Emetere

Numerical Methods in Environmental Data Analysis

Autor Moses Eterigho Emetere
en Limba Engleză Paperback – 19 iul 2022
Numerical Methods in Environmental Data Analysisintroduces environmental scientists to the numerical methods available to help answer research questions through data analysis. One challenge in data analysis is misrepresentation of datasets that are relevant directly or indirectly to the research. This book illustrates new ways of screening dataset or images for maximum utilization, introducing environmental modeling, numerical methods, and computations techniques in data analysis. Throughout the book, the author includes case studies that provide guidance on how to translate research questions into appropriate models.
Individuals working with data sets or images generated from environmental monitoring centers or satellites will find this book to be a concise guide for analyzing and interpreting their data.


  • Bridges the theoretical underpinnings of modeling to research
  • Illustrates the computational resolution of environmental issues alongside the use of open-source software
  • Provides information on the use of analogue versus digital data treatment processes
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Specificații

ISBN-13: 9780128189719
ISBN-10: 0128189711
Pagini: 240
Dimensiuni: 191 x 235 x 18 mm
Greutate: 0.42 kg
Editura: ELSEVIER SCIENCE

Public țintă

Primary: Research students and professionals in environmental scienceSecondary: Research students and professionals in civil and chemical engineering, environmental chemistry, atmospheric physics, space physics, environmental biology, and renewable energy

Cuprins

1. The concept of Data in Environmental Modeling 2. Introduction to Numerical Methods 3. Introduction to Computational and Statistical Techniques 4. Overview on Existing Data Analytics 5. Data Treatment 6. Conclusion

Recenzii

"...explores the complex interplay between environmental research and the indispensable data that drive it forward. By leveraging this significant association, Emetere’s scholarly contribution stands out as a seminal masterpiece, leading its audience to a profound exploration of environmental data’s intricate mathematical, computational, and statistical aspects. The book is effectively structured into nine chapters, each meticulously arranged, resulting in a remarkable voyage.... This book is a remarkable demonstration of Emetere’s deep-seated knowledge of his discipline.... In our view, immersing yourself in these works will broaden your understanding and heighten your appreciation for Emetere’s scholarly pursuits. We highly recommend Emetere’s book on environmental science. Its depth and breadth showcase the author’s profound expertise, making it more than just a textbook—it is a practical guide for both novices and experts. Despite the complexity of the subject matter, the book remains accessible, bridging the gap between theory and real-world application. In a time when accurate data analytics and integrity are paramount due to the pressing challenges of climate change, the book’s emphasis on these aspects is timely and invaluable." --Mudarris Mudarris and Desy Permatasari, Journal of Agricultural, Biological, and Environmental Statistics

Descriere

Numerical Methods in Environmental Data Analysis introduces environmental scientists to the numerical methods available to help answer research questions through data analysis. One challenge in data analysis is misrepresentation of datasets that are relevant directly or indirectly to the research. This book illustrates new ways of screening dataset or images for maximum utilization, introducing environmental modeling, numerical methods, and computations techniques in data analysis. Throughout the book, the author includes case studies that provide guidance on how to translate research questions into appropriate models.
Individuals working with data sets or images generated from environmental monitoring centers or satellites will find this book to be a concise guide for analyzing and interpreting their data.

 

 

 

  • Bridges the theoretical underpinnings of modeling to research
  • Illustrates the computational resolution of environmental issues alongside the use of open-source software
  • Provides information on the use of analogue versus digital data treatment processes