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.