Numerical Methods in Environmental Data Analysis

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

Research students and professionals in environmental science. Research students and professionals in civil and chemical engineering, environmental chemistry, atmospheric physics, space physics, environmental biology, and renewable energy

CHAPTER ONE: The concept of Data in Environmental Modeling
General Outline of Environmental Models
Data Sources in Environmental Science
Special Case Study: Data Processing Models

CHAPTER TWO: Introduction to Numerical Methods
General Outline of Numerical Methods
Special Cases on Numerical Methods
Numerical Methods in Environmental Modelling

CHAPTER THREE: Introduction to Computational and Statistical Techniques
General Outline of Computational Techniques in Environmental Science
Open Source Scientific Packages (Deleted)
Open-Source Library (Deleted)

CHAPTER FOUR: Overview on Existing Data Analytics
Description of Data Sources
Application of Numerical Methods in Data Analysis
Designing Computations Codes to Analyze Big Data

CHAPTER FIVE: Data Treatment
Shortcoming on Data treatment Methods
Statistical Data Treatment Processes
Computational Data Treatment Processes
Numerical Data Treatment Processes

CHAPTER SIX: Conclusion