- A short history of handling spatial data in R
- Simple feature access in R: package
`sf`

- Tidyverse, list-columns
- Reference systems
- sf: handling real data
- Methods for simple features
- book keeping, low-level I/O
- logical binary geometry predicates
- geometry generating logical operators
- higher-level intersections and differences
- higher-level operations: summarise, interpolate, aggregate, st_join
- manipulating geometries
- convenience functions
- handling mixes:
`GEOMETRY`

,`GEOMETRYCOLLECTION`

- empty geometries

- Pipe-based workflows and tidyverse
- Array data: rasters, spatial time series
- Summary/outlook

The R-markdown source of the tutorial is found here.

Required packages:

`install.packages(c("sf", "tidyverse", "devtools"))`

- pre-2003: several people doing spatial statistics or map manipulation with S-Plus, and later R (e.g. spatial in MASS; spatstat, maptools, geoR, splancs, gstat, …)
- 2003: workshop at DSC, concensus that a package with base classes should be useful; this ended up being a multiplicator
- 2003: start of r-sig-geo
- 2003: rgdal released on CRAN
- 2005: sp released on CRAN; sp support in rgdal
- 2008: Applied Spatial Data Analysis with R
- 2011: rgeos released on CRAN
- 2013: second edition of Applied Spatial Data Analysis with R
- 2016-7: simple features for R, R consortium support (considered pretty much “finished”)
- 2017-8: spatiotemporal tidy arrays for R, R consortium support (design phase)
- 2018: ggplot2 3.0.0 supports plotting of simple features