"The book's tone and technical focus ... suits well its intended audience: advanced or intermediate users of R wanting to improve their spatial analysis skills. ... this book is the authoritative resource on R's spatial capabilities. I heartily recommend ASDAR to all existing R users interested in spatial data and adventurous R beginners with a strong grounding in GIS." (Robin Lovelace, Applied Spatial Analysis and Policy, Vol. 8, 2015) Preface 2nd edition.- Preface 1st edition.- Hello World: Introducing Spatial Data.- Classes for Spatial Data in R.- Visualising Spatial Data.- Spatial Data Import and Export.- Further Methods for Handling Spatial Data.- Classes for spatio-temporal Data.- Spatial Point Pattern Analysis.- Interpolation and Geostatistics.- Modelling Areal Data.- Disease Mapping .This book first presents R packages, functions, classes and methods for handling spatial data. It then showcases more specialised kinds of spatial data analysis, including spatial point pattern analysis, interpolation and geostatistics and disease mapping.Applied Spatial Data Analysis with R, second edition, is divided into two basic parts, the first presenting R packages, functions, classes and methods for handling spatial data. This part is of interest to users who need to access and visualise spatial data. Data import and export for many file formats for spatial data are covered in detail, as is the interface between R and the open source GRASS GIS and the handling of spatio-temporal data. The second part showcases more specialised kinds of spatial data analysis, including spatial point pattern analysis, interpolation and geostatistics, areal data analysis and disease mapping. The coverage of methods of spatial data analysis ranges from standard techniques to new developments, and the examples used are largely taken from the spatial statistics literature. All the examples can be run using R contributed packages available from the CRAN website, with code and additional data sets from the book's own website. Compared to the first edition, the second edition covers the more systematic approach towards handling spatial data in R, as well as a number of important and widely used CRAN packages that have appeared since the first edition. This book will be of interest to researchers who intend to use R to handle, visualise, and analyse spatial data. It will also be of interest to spatial data analysts who do not use R, but who are interested in practical aspects of implementing software for spatial data analysis. It is a suitable companion book for introductory spatial statistics courses and for applied methods courses in a wide range of subjects using spatial data, including human and physical geography, geographical information science and geoinformatics, the environmental sciences, ecology, public health and disease control, economics, publicadministration and political science. The book has a website where complete code examples, data sets, and other support material may be found: http://www.asdar-book.org. The authors have taken part in writing and maintaining software for spatial data handling and analysis with R in concert since 2003. Roger Bivand is Professor of Geography in the Department of Economics at the Norwegian School of Economics, Bergen, Norway. Edzer Pebesma is Professor of Geoinformatics at Westfälische Wilhelms-Universität, Münster, Germany. Virgilio Gómez-Rubio is Associate Professor in the Department of Mathematics at Universidad de Castilla-La Mancha, Albacete, Spain