Getting started with R and R-spatial
About
Introduction
Schedule
Pre-requisites
What is
love
R ?
Why an R workshop in a FOSS4G conference ?
Coding paradigms
1
Data handling with R
1.1
Data types
1.2
Assignment
1.3
Not only a calculator
1.4
Packages
1.5
Load data
1.6
In the beginning was the Verb
1.7
Filter data
Exercise
1.8
Select columns
1.9
Create new variables
1.10
Agregate data
Exercise
1.11
Join data
1.12
Piping
2
Introduction to the R-spatial ecosystem
2.1
R’s spatial ecosystem(s)
2.2
Vector data
2.3
Raster data
3
Making maps in R
3.1
Mapping tools in R
3.2
Basic example
3.3
Shapes and layers
3.4
Attributes layers
3.5
Other map elements
3.6
Interactive mode
3.7
Saving maps
3.8
What else?
3.9
More resources
3.10
Exercises
4
Manipulating vector data
4.1
Read spatial data
4.1.1
Cycle hire dataset
4.1.2
Boroughs of London
4.2
Reprojection
4.3
Joins
4.3.1
Join by attributes
4.3.2
Spatial join
4.4
Aggregation
4.4.1
Count
4.4.2
Sum
4.5
Centroids
4.6
Geometric binary predicates
4.7
Saving results
4.7.1
Writing data
4.7.2
Check data
5
Manipulating raster data
5.1
Example data
5.2
Map algebra
5.2.1
Local operations
5.2.2
Focal operations
5.2.3
Zonal operations
5.2.4
Global operations
5.3
Transformations
5.3.1
Resampling
5.3.2
Reprojecting
5.4
Raster-vector interactions
5.4.1
Raster cropping and masking
5.4.2
Raster extraction
5.5
Raster analysis
5.5.1
Predictions
5.5.2
Segmentations
5.6
Raster writing
5.7
Exercises
Summary
References
Nicolas Roelandt
Jakub Nowosad
Published with bookdown
Getting started with R and R-spatial
References
Wickham, Hadley, and Jennifer Bryan. 2022.
R Packages
. 2nd ed.
https://r-pkgs.org/
.