The RStudio environment in relation to geospatial data (e.g., geometry columns for vector data, formal raster data classes visible in the Environment pane).
Specifics of geospatial data processing using pipeline-supporting functions (particularly regarding geometry and associated measurement units).
Importing geospatial data into R from saved files (vector and raster data using the sf and terra packages), server-based services (esri2sf, arcgislayers, ows4R packages), or using specialized packages designed for downloading online geodata (RCzechia, geodata).
Working with vector geodata (using the sf package):
- review of fundamental tidyverse functions,
- specific geometry-related operations (merging, spatial queries and selections, spatial joins),
- calculating polygon areas and perimeters, line lengths,
- working with measurement units and conversions,
- defining and transforming coordinate reference systems (CRS),
- saving data into files (including property settings such as character encoding for shapefiles),
- extracting coordinates from point vector layers.
Working with raster geodata (using the terra package):
- extracting raster values for points, lines, and polygons (zonal statistics),
- aggregating data across raster layers (e.g., temporal aggregation),
- setting and defining coordinate reference systems (authority codes, WKT),
- raster reprojection and adjusting horizontal resolution,
- raster file operations: saving to files (e.g., TIFF, netCDF), setting layer names, and specifying dates/times for individual layers,
- converting raster data into tabular formats,
- creating raster objects from lists,
- removing raster values to obtain an empty raster structure.
Creating static maps (using ggplot2, tidyterra, ggspatial, tmap):
- fundamentals of map creation in R,
- adding raster and vector layers,
- working with color palettes, legends, and labels,
- adding scale bars and north arrows,
- changing localization settings (e.g., Czech) and reverting to default,
- saving maps to files.
Creating dynamic maps (using mapview and tmap):
- generating interactive maps in the Viewer pane,
- changing base maps,
- importance of WMS services as base layers.
Geodata and functional programming in R (using purrr, furrr, tidyr):
- importance of nesting data,
- understanding and applying the map() family of functions (with explanation of differences),
- options for parallel processing using futures.
