quarto sources for "Spatial Data Science: with applications in R"

The print version of this book is available from CRC/Chapman and Hall. A rendered (html) version of this book is available online.

To recreate/reproduce this book:

• git clone this repository
• download the data used in Ch 13, and extract the contents of the aq subdirectory into sdsr/aq
• install R package dependencies listed below
• install quarto
• run quarto render --to html

See also the Dockerfile; building the (18 Gb) image with

docker build . -t sdsr

and running it with

docker run -p 8787:8787 -e DISABLE_AUTH=true -ti --rm sdsr

will serve an Rstudio server instance on http://localhost:8787/, without authentication.

Compiling the whole book

After running the docker image and opening rstudio in the browser:

• click on 01-hello.qmd in the bottom-right pane
• click on the Render button of the top-left pane to compile the whole book

this should open a new browser window with the full book rendered (you may need to switch off popup blockers for localhost)

Running selected chunks

To run a selected code section, possibly after modification, find the selected code section in the corresponding .qmd file, and click the small green arrow symbols on the top-right corner of the code blocks:

• to prepare, first click Run All Chunks Above,
• to run a selected code chunk: click Run Current Chunk

Dependencies

To locally process the book, download (clone) this repository and install the following R packages from CRAN:

install.packages(c(
  "dbscan",
  "gstat",
  "hglm",
  "igraph",
  "lme4",
  "lmtest",
  "maps",
  "mapview",
  "matrixStats",
  "mgcv",
  "R2BayesX",
  "rgeoda",
  "rnaturalearth",
  "rnaturalearthdata",
  "sf",
  "spatialreg",
  "spdep",
  "spData",
  "stars",
  "tidyverse",
  "tmap"))

Install INLA:

install.packages("INLA", repos = c(getOption("repos"), INLA="https://inla.r-inla-download.org/R/stable"))

Install spDataLarge:

options(timeout = 600); install.packages("spDataLarge", repos = "https://nowosad.github.io/drat/",type = "source")

Install starsdata:

options(timeout = 1200); install.packages("starsdata", repos = "http://cran.uni-muenster.de/pebesma", type = "source")

Install spatialreg from source from github, either from source:

install.packages("remotes")
remotes::install_github("r-spatial/spatialreg")

or as binary from r-universe:

options(repos = c(
  rspatial = "https://r-spatial.r-universe.dev",
  CRAN = "https://cloud.r-project.org"))
install.packages(c("spatialreg"))