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: about 1 month 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 (over 5 years ago)
• Default Branch: master
• Last Pushed: 2019-03-27T11:35:49.000Z (over 5 years ago)
• Last Synced: 2024-02-07T18:35:58.456Z (5 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

Lists

• 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.