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
aqsubdirectory intosdsr/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.
After running the docker image and opening rstudio in the browser:
- click on
01-hello.qmdin the bottom-right pane - click on the
Renderbutton 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)
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
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",
"viridis",
"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"))
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/ .
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/ .