Further resources

Packages:

Books:

Spatial Data Science with Applications in R by Pebesma and Bivand (2023a)
Geocomputation with R by Lovelace, Nowosad, and Muenchow (2019)
sits: Satellite Image Time Series Analysis on Earth Observation Data Cubes by Câmara et al. (2023)

Blogs, Courses, Workshops & Articles:

R-spatial blog
geocompx blog
Getting started with R and R-Spatial by Nicolas Roelandt and Jakub Nowosad for a FOSS4G 2022 workshop.
Introduction to Spatial Data Programming with R by Michael Dorman
Spatial Data Science with R and “terra” by Robert J. Hijmans
Intro to GIS and Spatial Analysis - Appendix by Manuel Gimond
Introduction to Geospatial Raster and Vector Data with R by the Carpentries
“Potential use of R-statistical programming in the field of geoscience” by Bishwal (2017) in International Conference for Convergence of Technology (I2CT).
“Using R in hydrology: a review of recent developments and future directions” by Slater et al. (2019) in Hydrology and Earth System Sciences.
Remote sensing in R resources and discussion

Bridges to GIS software:

GRASS with {rgrass} by Bivand (2024)
SAGA with {RSAGA} by Brenning, Bangs, and Becker (2022)
QGIS with {qgisprocess} by Dunnington et al. (n.d.)
ArcGIS with {arcgisbinding} by Aydin et al. (2024)
CLI interface to various GIS software {link2GI} by Reudenbach (2023)

Allaire, JJ. 2023. Quarto: R Interface to Quarto Markdown Publishing System. https://github.com/quarto-dev/quarto-r.

Appelhans, Tim, Florian Detsch, Christoph Reudenbach, and Stefan Woellauer. 2022. Mapview: Interactive Viewing of Spatial Data in r. https://github.com/r-spatial/mapview.

Aydin, Orhun, Dmitry Pavlushko, Shaun Walbridge, Steve Kopp, and Mark V. Janikas. 2024. “Arcgisbinding: An r Package for Integrating r and ArcGIS.” Environmental Modelling &Amp; Software 172 (January): 105904. https://doi.org/10.1016/j.envsoft.2023.105904.

Bishwal, R. M. 2017. “Potential Use of r-Statistical Programming in the Field of Geoscience.” In 2017 2nd International Conference for Convergence in Technology (I2CT), 979–82. https://doi.org/10.1109/I2CT.2017.8226275.

Bivand, Roger. 2024. Rgrass: Interface Between ’GRASS’ Geographical Information System and ’r’. https://rsbivand.github.io/rgrass/.

Brenning, Alexander, Donovan Bangs, and Marc Becker. 2022. RSAGA: SAGA Geoprocessing and Terrain Analysis. https://CRAN.R-project.org/package=RSAGA.

Câmara, Gilberto, Rolf Simoes, Felipe Souza, Charlotte Pelletier, Alber Sanchez, Pedro Andrade, Karine Ferreira, and Gilberto Queiroz. 2023. “sits: Satellite Image Time Series Analysis on Earth Observation Data Cubes.” 2023. https://e-sensing.github.io/sitsbook/index.html.

Dunnington, Dewey, Floris Vanderhaeghe, Jan Caha, and Jannes Muenchow. n.d. “R Package Qgisprocess: Use QGIS Processing Algorithms.” https://github.com/r-spatial/qgisprocess/.

Hijmans, Robert. 2020. “Terra and Luna: New r Packages Scalable Geospatial Data Analysis.” Big Data in Agriculture - 2020 Convention. 2020. https://www.youtube.com/watch?v=5b2xhqlH49I&t=690s.

Hijmans, Robert J. 2024. Terra: Spatial Data Analysis. https://rspatial.org/.

Lovelace, Robin, Jakub Nowosad, and Jannes Muenchow. 2019. Geocomputation with R. CRC Press.

Pebesma, Edzer. 2018. “Simple Features for R: Standardized Support for Spatial Vector Data.” The R Journal 10 (1): 439–46. https://doi.org/10.32614/RJ-2018-009.

———. 2023a. Sf: Simple Features for r. https://r-spatial.github.io/sf/.

———. 2023b. Stars: Spatiotemporal Arrays, Raster and Vector Data Cubes. https://r-spatial.github.io/stars/.

Pebesma, Edzer, and Roger Bivand. 2023b. Spatial Data Science: With applications in R. Chapman and Hall/CRC. https://doi.org/10.1201/9780429459016.

———. 2023a. Spatial Data Science: With applications in R. London: Chapman; Hall/CRC. https://doi.org/10.1201/9780429459016.

Pebesma, Edzer, Thomas Mailund, and James Hiebert. 2016. “Measurement Units in R.” R Journal 8 (2): 486–94. https://doi.org/10.32614/RJ-2016-061.

Pebesma, Edzer, Thomas Mailund, Tomasz Kalinowski, and Iñaki Ucar. 2023. Units: Measurement Units for r Vectors. https://r-quantities.github.io/units/.

R Core Team. 2023. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/.

Reudenbach, Chris. 2023. link2GI: Linking Geographic Information Systems, Remote Sensing and Other Command Line Tools. https://CRAN.R-project.org/package=link2GI.

Slater, Louise J., Guillaume Thirel, Shaun Harrigan, Olivier Delaigue, Alexander Hurley, Abdou Khouakhi, Ilaria Prosdocimi, Claudia Vitolo, and Katie Smith. 2019. “Using r in Hydrology: A Review of Recent Developments and Future Directions.” Hydrology and Earth System Sciences 23 (7): 2939–63. https://doi.org/10.5194/hess-23-2939-2019 .

Tennekes, Martijn. 2018. “tmap: Thematic Maps in R.” Journal of Statistical Software 84 (6): 1–39. https://doi.org/10.18637/jss.v084.i06.

———. 2023. Tmap: Thematic Maps. https://github.com/r-tmap/tmap.

Wickham, Hadley. 2016. Ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York. https://ggplot2.tidyverse.org.

Wickham, Hadley, Winston Chang, Lionel Henry, Thomas Lin Pedersen, Kohske Takahashi, Claus Wilke, Kara Woo, Hiroaki Yutani, Dewey Dunnington, and Teun van den Brand. 2024. Ggplot2: Create Elegant Data Visualisations Using the Grammar of Graphics. https://ggplot2.tidyverse.org.

Xie, Yihui. 2014. “Knitr: A Comprehensive Tool for Reproducible Research in R.” In Implementing Reproducible Computational Research, edited by Victoria Stodden, Friedrich Leisch, and Roger D. Peng. Chapman; Hall/CRC.

———. 2015. Dynamic Documents with R and Knitr. 2nd ed. Boca Raton, Florida: Chapman; Hall/CRC. https://yihui.org/knitr/.

———. 2023. Knitr: A General-Purpose Package for Dynamic Report Generation in r. https://yihui.org/knitr/.