Geocomputation with R

This book provides essential tools for analyzing and modeling geographic data using R, making it ideal for data scientists and geospatial analysts.

The book Geocomputation with R is designed for individuals eager to analyze, visualize, and model geographic data using open-source software. In its second edition, it incorporates numerous updates, including the integration of the high-performance terra package for efficient raster data processing. This edition enhances the learning experience by providing a solid foundation for addressing a wide array of geographic data analysis challenges in a reproducible and scientifically rigorous manner.

Geocomputation with R goes beyond basic concepts, offering detailed insights into advanced topics such as the spherical geometry engine s2, coordinate reference systems, and new technologies like openEO, STAC, COG, and gdalcubes. The data visualization chapter has been completely overhauled to align with version 4 of the tmap package, ensuring readers can create publication-quality maps directly from the command line. Additionally, a new foreword by Edzer Pebesma underscores the significance of this work in the field of geocomputation.

This book is particularly beneficial for data scientists and engineers looking to enhance their skills in spatial data analysis, as well as for those already familiar with geographic data who wish to develop robust geosolutions through programming. The structure of Geocomputation with R is divided into three parts: Foundations, Extensions, and Applications, allowing readers to progressively tackle more complex topics. Each chapter concludes with exercises designed to build the necessary skills to solve various geospatial problems, with solutions and additional resources available online.