Geographic Data Science with R: Visualizing and Analyzing Environmental Change

The book "Geographic Data Science with R" is a comprehensive guide to using geospatial data with R, covering topics such as data screening, handling missing data, harmonization, summarization, and visualization. It is designed for students and professionals and focuses on developing practical workflows for processing and analyzing diverse spatial and non-spatial data.

Format: Hardback
Length: 284 pages
Publication date: 08 May 2023
Publisher: Taylor & Francis Ltd

The field of data science has revolutionized the analysis of large and complex geospatial datasets, offering a wide range of techniques such as descriptive, explanatory, and predictive analytics. However, the process of geographic data science extends beyond the application of these methods. It involves a series of critical steps, including data screening, handling missing data, harmonizing data from different sources, summarizing the data, and visualizing data and analysis results. While numerous books exist on statistical and machine learning methods, there is a scarcity of resources that cover the broader topic of scientific workflows for geospatial data processing and analysis.

Geographic Data Science with R aims to bridge this gap by providing a comprehensive tutorial series focused on teaching best practices for utilizing geospatial data to address environmental geography problems. Built upon the powerful R language and environment, this book offers a versatile platform for working with diverse spatial and non-spatial data in a single framework. Fundamental techniques for processing and visualizing tabular, vector, and raster data are introduced through practical examples, accompanied by case studies that combine multiple data types to tackle complex challenges.

Designed with a broad audience in mind, this book caters to students and professionals alike. It serves as a valuable workbook for learning advanced geospatial data processing and analysis techniques with R, while also functioning as a textbook suitable for classroom use. While not intended as a comprehensive introduction to R, the book is designed to be accessible to readers with a basic understanding of coding but limited experience with R.

Key Features:
1. Emphasis on Developing Practical Workflows for Processing and Integrating Multiple Sources of Geospatial Data.
2. Comprehensive Coverage of Data Screening, Handling Missing Data, Harmonization, Summarization, and Visualization.
3. Accessible to Readers with Basic Coding Knowledge and Limited Experience with R.
4. Case Studies and Practical Examples to Illustrate Key Concepts and Techniques.
5. Broad Audience Appeal, Suitable for Students, Professionals, and Classroom Use.
6. Integration of R Language and Environment for Efficient Data Processing and Analysis.
7. Coverage of Diverse Spatial and Non-Spatial Data Types and Analysis Methods.
8. Practical Applications in Environmental Geography and Related Fields.

In conclusion, Geographic Data Science with R is a valuable resource for anyone seeking to leverage geospatial data for environmental research and analysis. By providing a comprehensive tutorial series and emphasizing practical workflows, this book equips readers with the skills and knowledge necessary to effectively process, integrate, and analyze geospatial data using R. Whether you are a student, professional, or researcher, this book will be an indispensable tool in your pursuit of understanding and addressing environmental challenges.

Weight: 634g
Dimension: 162 x 241 x 20 (mm)
ISBN-13: 9781032347714