lucasjcc / sdsr

Spatial Data Science: With Applications in R

quarto sources for "Spatial Data Science: With Applications in R"

The print version of this book is available from CRC/Chapman and Hall. A complete online version of this book is available.

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"))

Daily rendered version on GA

The entire book is recreated from source nightly with the latest released R and all updated CRAN packages by a Github Action using this script. The online version thus rendered is found here. As this output is not checked daily it is not automatically copied to the "official" online version, at https://r-spatial.org/book/ .

Python version

A version "With Applications in R and Python" is under construction; the sources are in the python branch of this repository, a rendered online version is found at https://r-spatial.org/python/ .