This presentation/tutorial explains how to use GIS software from within R for statistical geocomputing. Specifically, we will execute QGIS and SAGA algorithms from within R to compute terrain attributes which we will use as predictors when modeling the floristic composition of Mt. Mongón in the next tutorial ("The importance of spatial cross-validation in predictive modeling).
Materials: Find the code and the presentations in the r_gis_bridges folders of https://github.com/geocompr/geostats_18.
Software requirements: RStudio, R and its packages RQGIS, RSAGA, sf, raster, dplyr and mapview. Please use our install guide (http://jannes-m.github.io/RQGIS/articles/install_guide.html) to install QGIS, SAGA and GRASS on various platforms. Make sure to install QGIS LTR 2.18 since RQGIS so far does not support QGIS 3.
- Muenchow, J., Schratz, P., and A. Brenning. 2017. RQGIS: Integrating R with QGIS for statistical geocomputing. The R Journal 9, 2, 409-428. https://rjournal.github.io/archive/2017/RJ-2017-067/RJ-2017-067.pdf.
- Lovelace, R., Nowosad, J., and J. Muenchow (forthcoming). Geocomputation with R. Chapter 9: Bridges to GIS software. https://geocompr.robinlovelace.net/gis.html. CRC Press.