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https://github.com/joheisig/Spatial_Data_in_R
🌌 SWIRL-course on spatial data in R :globe_with_meridians:
https://github.com/joheisig/Spatial_Data_in_R
course gis r r-studio remote-sensing spatial-data-analysis swirl
Last synced: 3 months ago
JSON representation
🌌 SWIRL-course on spatial data in R :globe_with_meridians:
- Host: GitHub
- URL: https://github.com/joheisig/Spatial_Data_in_R
- Owner: joheisig
- License: other
- Created: 2018-12-07T12:52:17.000Z (almost 6 years ago)
- Default Branch: master
- Last Pushed: 2019-03-27T11:35:49.000Z (over 5 years ago)
- Last Synced: 2024-05-16T12:29:51.556Z (6 months ago)
- Topics: course, gis, r, r-studio, remote-sensing, spatial-data-analysis, swirl
- Language: R
- Homepage:
- Size: 19.1 MB
- Stars: 6
- Watchers: 0
- Forks: 1
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE.txt
Awesome Lists containing this project
- awesome-earthobservation-code - Spatial_Data_in_R - SWIRL-course on spatial data in `R` (Resources for `R` / Testing your code)
README
# Spatial Data in R
This is an interactive course on spatial data in R :globe_with_meridians:. It can be run inside e.g. RStudio with the [`swirl`](https://github.com/swirldev)-package 🌌. The project is in its development stage. Lessons listed below are already open for learning and testing. Suggestions and contributions are very welcome.
## Installation
Install `swirl` and the current version of this course by running the following lines:
```s
install.packages("swirl")
library(swirl)
install_course_github("joheisig", "Spatial_Data_in_R")
```
## Getting started
When the `swirl`-package is loaded, activate the course environment:
```s
swirl()
```
`swirl` will ask for your name and present you with the course menu. After you selected 'Spatial Data in R' you can choose from all lessons availible.
## Lessons
* Raster Basics: plot, crop and subset rasters, get basic meta data and stats
* Vector Basics: explore point, line and polygon features, subset by attribute, create an overview map, calculate intersections
* Import & Export: read and write raster files, load shapefiles, import point features from csv, write shapefiles
* Coordinate Reference Systems: awareness for spatial reference, query CRS, reproject/transform data
## Lessons planned
* Advanced Plotting
* Working With Multiple Layers
* Access Spatial Data
* Timeseries Basics
* Land Cover Classifications
## Want to contribute?
If you find this course a useful resource for learning to use spatial data in R, then that's great. If you like it so much you want to help building the course and contribute your R skills, knowledge and ideas to the community, that's even better! Just send me a pull request and/or a message.