Geocomputation with R

Geocomputation with R is a book that teaches how to analyze, visualize, and model geographic data with open-source software R. It is based on R, a statistical programming language with powerful data processing, visualization, and geospatial capabilities. The book is divided into three parts: Foundations, extensions, and applications, and covers topics such as spatial datasets, map making, bridges to GIS, sharing reproducible code, and cross-validation. It is written by three experts in the field, and includes exercises and solutions for each chapter.

\n Format: Paperback / softback
\n Length: 354 pages
\n Publication date: 18 December 2020
\n Publisher: Taylor & Francis Ltd
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Geocomputation with R is a comprehensive guide for individuals seeking to analyze, visualize, and model geographic data using open-source software. Built upon the powerful statistical programming language R, this book offers a wealth of knowledge and skills to address a diverse range of issues inherent in geographic data, encompassing scientific, societal, and environmental dimensions. Whether you are a Geographic Information Systems (GIS) user looking to leverage your domain-specific expertise in a robust open-source language for data science or an R user seeking to expand your skills to handle spatial data, this book will captivate your interest.

The book is structured into three parts: (I) Foundations, designed to provide a solid foundation in geographic data manipulation with R; (II) Extensions, which delves into advanced techniques; and (III) Applications to Real-World Problems. The chapters progress in complexity, with early chapters laying the groundwork for subsequent chapters to build upon. Part I explores the nature of spatial datasets in R, covering methods for their manipulation, import/export operations, and transformation of coordinate reference systems. Part II builds upon these foundations, introducing advanced map-making capabilities, integrating with GIS systems, promoting reproducible code practices, and addressing cross-validation in the presence of spatial autocorrelation. Part III applies the knowledge gained to tackle real-world geospatial challenges, such as representing and modeling transport systems, optimizing store or service locations, and conducting ecological modeling. Each chapter concludes with exercises to reinforce the skills acquired, enabling readers to apply their knowledge to a wide array of geospatial problems.

By leveraging the power of R and its extensive geospatial capabilities, Geocomputation with R empowers users to unlock the full potential of geographic data analysis and visualization. Whether you are a researcher, analyst, or practitioner in the fields of geography, environmental science, or urban planning, this book provides the essential tools and techniques to effectively handle, manipulate, and interpret geographic information, leading to informed decision-making and meaningful insights.

\n Weight: 600g\n
Dimension: 154 x 236 x 20 (mm)\n
ISBN-13: 9780367670573\n \n