https://github.com/kadyb/stars-parallel

Tutorial on parallel processing of raster data in the {stars} package
https://github.com/kadyb/stars-parallel

clustering geospatial gis parallel-computing performance r raster tutorial

Last synced: 10 months ago
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Tutorial on parallel processing of raster data in the {stars} package

• Host: GitHub
• URL: https://github.com/kadyb/stars-parallel
• Owner: kadyb
• Created: 2023-08-16T19:47:51.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2023-09-22T11:24:09.000Z (over 2 years ago)
• Last Synced: 2024-01-27T03:41:38.498Z (almost 2 years ago)
• Topics: clustering, geospatial, gis, parallel-computing, performance, r, raster, tutorial
• Language: HTML
• Homepage: https://kadyb.github.io/stars-parallel/
• Size: 7.65 MB
• Stars: 11
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Parallel raster processing in the {stars} package 

The following tutorial demonstrates the parallel processing of huge (out-of-memory) raster

data in the [**stars**](https://github.com/r-spatial/stars) package. The discussed example

concerns the unsupervised classification of multispectral satellite images. The used technique

allows you to divide the image into smaller blocks and process them simultaneously (rather

than sequentially), so you will notice an increase in performance.

### [Tutorial](https://kadyb.github.io/stars-parallel/Tutorial.html)

![gif](gif.gif)