# R for Spatial Data Science

The second part of this book explains how the concepts introduced in part I are dealt with using R. Chapter 7 deals with basic handling of spatial data: reading, writing, subsetting, selecting by spatial predicates, geometry transformers like buffers or intersections, raster-vector and vector-raster conversion, handling of data cubes, spherical geometry, coordinate transformations and conversions. This is followed by a chapter dedicated to plotting of spatial and spatiotemporal data with base plot, and packages `ggplot2`

, `tmap`

and `mapview`

. The chapter deals with projection, colours, color breaks, graticules, graphic elements on maps like legends, and interactive maps. Chapter 9 discusses approaches to handle large vector or raster data sets or data cubes, where “large” either means too large to fit in memory or too large to download locally.