Geocomputation with R

Geocomputation with R is a comprehensive guide that explores the integration of geographic information systems (GIS) and computational methods using the flexible and powerful programming language R. The book is written for researchers and practitioners in the fields of geography, environmental science, urban planning, and related disciplines who are interested in applying computational methods to analyze and visualize spatial data.

The book begins by introducing the basics of GIS and R programming, providing an overview of the various packages and libraries available for geospatial analysis in R. The authors then delve into more advanced topics, such as spatial data manipulation and visualization, spatial modeling, and geostatistics. Throughout the book, readers are provided with practical examples and case studies that demonstrate how to apply these methods to real-world problems.

One of the strengths of Geocomputation with R is its focus on reproducibility and open science. The authors emphasize the importance of using open data and open-source software, and provide guidance on how to share code and data to facilitate collaboration and transparency. This approach not only promotes scientific integrity, but also enables researchers to build on each other’s work and make new discoveries.

In addition to its practical focus, Geocomputation with R is also a valuable resource for those interested in the theoretical foundations of geospatial analysis. The authors provide clear explanations of key concepts, such as spatial autocorrelation and variogram analysis, and show how these concepts can be applied using R.

Throughout the book, the authors use a hands-on approach to learning, providing readers with plenty of opportunities to practice coding and apply the concepts they have learned. The book is filled with code snippets, exercises, and data sets, making it an ideal resource for self-guided learning or as a textbook for a graduate-level course.

Overall, Geocomputation with R is an essential resource for anyone interested in using computational methods to analyze and visualize spatial data. The book’s practical focus, emphasis on reproducibility and open science, and hands-on approach make it a valuable addition to any geospatial analyst’s toolkit.